12996 lines
1.9 MiB
12996 lines
1.9 MiB
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
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"\n",
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"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
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" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
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"Fusing layers... \n",
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"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
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]
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"barcode: 8935024140147\n",
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"goodsPic: /home/ieemoo0337/projects/datasets/FP/8935024140147/9421029085228.jpg\n",
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"video: /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4\n"
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]
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},
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
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"video 1/1 (1/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 6.4ms\n",
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"video 1/1 (2/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.3ms\n",
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"video 1/1 (3/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.3ms\n",
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"video 1/1 (4/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.3ms\n",
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"video 1/1 (5/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.2ms\n",
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"video 1/1 (6/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.3ms\n",
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"video 1/1 (7/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.4ms\n"
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]
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},
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||
{
|
||
"name": "stdout",
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||
"output_type": "stream",
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"text": [
|
||
"load model resnet18 \n"
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||
]
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},
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{
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"name": "stderr",
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"output_type": "stream",
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"video 1/1 (9/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.4ms\n",
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"video 1/1 (10/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.4ms\n",
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||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
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||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"{'item1': {'Text': 'Farm Milk Powder', 'Color': '红色', 'Shape': '长方体', 'Material': '金属', 'Category': '乳制品'}, 'item2': {'Text': '未知', 'Color': '未知', 'Shape': '未知', 'Material': '未知', 'Category': '未知'}, 'is_Same': False}\n",
|
||
"barcode: 9310072012599\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/9310072012599/9415007004585.jpg\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/9310072012599/9310072012599_20241017-181911_back_addGood_5478c9a48c3e_215_13586533739.mp4\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n",
|
||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
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|
||
"video 1/1 (2/66) /home/ieemoo0337/projects/datasets/FP/9310072012599/9310072012599_20241017-181911_back_addGood_5478c9a48c3e_215_13586533739.mp4: 640x512 5.2ms\n",
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||
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||
"video 1/1 (4/66) /home/ieemoo0337/projects/datasets/FP/9310072012599/9310072012599_20241017-181911_back_addGood_5478c9a48c3e_215_13586533739.mp4: 640x512 5.3ms\n",
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||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"load model resnet18 \n"
|
||
]
|
||
},
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||
{
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||
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"/home/ieemoo0337/projects/detecttracking/tracking/traclus.py:163: RuntimeWarning: divide by zero encountered in scalar divide\n",
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" tan_theta0 = (shorter_slope - longer_slope) / (1 + shorter_slope * longer_slope)\n",
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||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
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||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
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||
]
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},
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||
{
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||
"name": "stdout",
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||
"output_type": "stream",
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||
"text": [
|
||
"{'item1': {'Text': 'Anchor Cheddar Processed Cheese', 'Color': '蓝色', 'Shape': '长方形', 'Material': '塑料', 'Category': '奶酪'}, 'item2': {'Text': 'Tim Tam Dark', 'Color': '黑色', 'Shape': '长方形', 'Material': '塑料', 'Category': '饼干'}, 'is_Same': False}\n",
|
||
"barcode: 9345521001152\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/9345521001152/8993175537391.jpg\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/9345521001152/9345521001152_20241018-112702_back_returnGood_5478c9a48c02_5_13586533739.mp4\n"
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||
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||
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||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
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||
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||
},
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||
{
|
||
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|
||
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||
"text": [
|
||
"load model resnet18 \n"
|
||
]
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||
},
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||
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||
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||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
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||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"{'item1': {'Text': 'nabati Cheese Wafer', 'Color': '黄色', 'Shape': '长方形', 'Material': '饼干', 'Category': '零食'}, 'item2': {'Text': '未知', 'Color': '白色', 'Shape': '圆柱形', 'Material': '塑料', 'Category': '清洁用品'}, 'is_Same': False}\n",
|
||
"barcode: 8850511321499\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/8850511321499/8851016000513.jpg\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/8850511321499/8850511321499_20241014-153139_back_returnGood_5478c9a49bfc_570_18133699824.mp4\n"
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||
]
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||
},
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||
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||
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||
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||
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|
||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
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|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
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||
"text": [
|
||
"load model resnet18 \n"
|
||
]
|
||
},
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||
{
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||
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||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
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||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"{'item1': {'Text': 'Calbee', 'Color': '绿色', 'Shape': '长方形', 'Material': '塑料', 'Category': '零食'}, 'item2': {'Text': '未知', 'Color': '未知', 'Shape': '未知', 'Material': '未知', 'Category': '未知'}, 'is_Same': False}\n",
|
||
"barcode: 9551010541867\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/9551010541867/9551010541867_20241017-162002_back_addGood_5478c9a51ba6_395_18358205530.mp4\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/9551010541867/9345521003781.jpg\n"
|
||
]
|
||
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|
||
{
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||
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||
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||
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|
||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
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||
]
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||
},
|
||
{
|
||
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|
||
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||
"text": [
|
||
"load model resnet18 \n"
|
||
]
|
||
},
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||
{
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||
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"video 1/1 (56/60) /home/ieemoo0337/projects/datasets/FP/9551010541867/9551010541867_20241017-162002_back_addGood_5478c9a51ba6_395_18358205530.mp4: 640x512 5.3ms\n",
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"video 1/1 (57/60) /home/ieemoo0337/projects/datasets/FP/9551010541867/9551010541867_20241017-162002_back_addGood_5478c9a51ba6_395_18358205530.mp4: 640x512 5.4ms\n",
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"video 1/1 (58/60) /home/ieemoo0337/projects/datasets/FP/9551010541867/9551010541867_20241017-162002_back_addGood_5478c9a51ba6_395_18358205530.mp4: 640x512 5.3ms\n",
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"video 1/1 (59/60) /home/ieemoo0337/projects/datasets/FP/9551010541867/9551010541867_20241017-162002_back_addGood_5478c9a51ba6_395_18358205530.mp4: 640x512 5.3ms\n",
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"video 1/1 (60/60) /home/ieemoo0337/projects/datasets/FP/9551010541867/9551010541867_20241017-162002_back_addGood_5478c9a51ba6_395_18358205530.mp4: 640x512 5.3ms\n",
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||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
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||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
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||
]
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||
},
|
||
{
|
||
"name": "stdout",
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||
"output_type": "stream",
|
||
"text": [
|
||
"{'item1': {'Text': '实力解决肌肤问题\\n全新海盐净油系列\\nSEA SALT\\nGreenKosy\\nSEA SALT REFRESHING\\nSHOWER GEL\\nFeel Cool\\n700g/24.8 fl.oz', 'Color': '蓝色', 'Shape': '长方形', 'Material': '塑料', 'Category': '洗护用品'}, 'item2': {'Text': 'Mico', 'Color': '蓝色', 'Shape': '长方形', 'Material': '塑料', 'Category': '零食'}, 'is_Same': False}\n",
|
||
"barcode: 9315090208504\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/9315090208504/8859468700319.jpg\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/9315090208504/9315090208504_20241020-142822_back_addGood_5478c9a53be2_3645_18058629568.mp4\n"
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||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
"video 1/1 (1/95) /home/ieemoo0337/projects/datasets/FP/9315090208504/9315090208504_20241020-142822_back_addGood_5478c9a53be2_3645_18058629568.mp4: 640x512 (no detections), 6.2ms\n",
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]
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||
},
|
||
{
|
||
"name": "stdout",
|
||
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||
"text": [
|
||
"load model resnet18 \n"
|
||
]
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||
},
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||
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"/home/ieemoo0337/projects/detecttracking/tracking/traclus.py:163: RuntimeWarning: divide by zero encountered in scalar divide\n",
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||
" tan_theta0 = (shorter_slope - longer_slope) / (1 + shorter_slope * longer_slope)\n",
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||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
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"\n"
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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||
"{'item1': {'Text': 'Hello Kitty Drinking Water', 'Color': '透明', 'Shape': 'Hello Kitty', 'Material': '塑料', 'Category': '饮料'}, 'item2': {'Text': 'A2β-casein PURE MILK', 'Color': '红色', 'Shape': '长方体', 'Material': '纸箱', 'Category': '乳制品'}, 'is_Same': False}\n",
|
||
"barcode: 8850813311020\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/8850813311020/9421016150199.jpg\n",
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||
"video: /home/ieemoo0337/projects/datasets/FP/8850813311020/8850813311020_20241019-183308_back_addGood_5478c9a53be2_50_14785332147.mp4\n"
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||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n",
|
||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
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||
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||
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||
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|
||
"load model resnet18 \n"
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||
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||
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||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
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||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"{'item1': {'Text': 'Westgold 牧恩 Pure New Zealand Butter', 'Color': '黄色', 'Shape': '长方体', 'Material': '黄油', 'Category': '食品'}, 'item2': {'Text': '未知', 'Color': '橙色', 'Shape': '长条形', 'Material': '未知', 'Category': '未知'}, 'is_Same': False}\n",
|
||
"barcode: 9421029085075\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/9421029085075/9421029085075_20241016-163745_back_returnGood_5478c9a49bfc_995_18358205530.mp4\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/9421029085075/9311493002572.jpg\n"
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||
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||
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||
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||
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||
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||
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||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
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||
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|
||
},
|
||
{
|
||
"name": "stdout",
|
||
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||
"text": [
|
||
"load model resnet18 \n"
|
||
]
|
||
},
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||
{
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||
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"video 1/1 (102/112) /home/ieemoo0337/projects/datasets/FP/9421029085075/9421029085075_20241016-163745_back_returnGood_5478c9a49bfc_995_18358205530.mp4: 640x512 5.4ms\n",
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"video 1/1 (103/112) /home/ieemoo0337/projects/datasets/FP/9421029085075/9421029085075_20241016-163745_back_returnGood_5478c9a49bfc_995_18358205530.mp4: 640x512 5.4ms\n",
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"video 1/1 (107/112) /home/ieemoo0337/projects/datasets/FP/9421029085075/9421029085075_20241016-163745_back_returnGood_5478c9a49bfc_995_18358205530.mp4: 640x512 5.4ms\n",
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"video 1/1 (108/112) /home/ieemoo0337/projects/datasets/FP/9421029085075/9421029085075_20241016-163745_back_returnGood_5478c9a49bfc_995_18358205530.mp4: 640x512 5.3ms\n",
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"video 1/1 (109/112) /home/ieemoo0337/projects/datasets/FP/9421029085075/9421029085075_20241016-163745_back_returnGood_5478c9a49bfc_995_18358205530.mp4: 640x512 5.8ms\n",
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"video 1/1 (110/112) /home/ieemoo0337/projects/datasets/FP/9421029085075/9421029085075_20241016-163745_back_returnGood_5478c9a49bfc_995_18358205530.mp4: 640x512 5.4ms\n",
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"video 1/1 (111/112) /home/ieemoo0337/projects/datasets/FP/9421029085075/9421029085075_20241016-163745_back_returnGood_5478c9a49bfc_995_18358205530.mp4: 640x512 5.5ms\n",
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"video 1/1 (112/112) /home/ieemoo0337/projects/datasets/FP/9421029085075/9421029085075_20241016-163745_back_returnGood_5478c9a49bfc_995_18358205530.mp4: 640x512 5.3ms\n",
|
||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
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||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"{'item1': {'Text': 'Bundaberg PASSIONFRUIT SPARKLING DRINK', 'Color': '橙色', 'Shape': '圆柱形', 'Material': '玻璃', 'Category': '饮料'}, 'item2': {'Text': '未知', 'Color': '未知', 'Shape': '未知', 'Material': '未知', 'Category': '未知'}, 'is_Same': False}\n",
|
||
"barcode: 9345521003774\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/9345521003774/9345521003774_20241014-134529_back_addGood_5478c9a48b8c_800_18358205530.mp4\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/9345521003774/9311493002527.jpg\n"
|
||
]
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||
},
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||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
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"text": [
|
||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
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||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
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||
"text": [
|
||
"load model resnet18 \n"
|
||
]
|
||
},
|
||
{
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||
"name": "stderr",
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"video 1/1 (62/86) /home/ieemoo0337/projects/datasets/FP/9345521003774/9345521003774_20241014-134529_back_addGood_5478c9a48b8c_800_18358205530.mp4: 640x512 5.3ms\n",
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"video 1/1 (83/86) /home/ieemoo0337/projects/datasets/FP/9345521003774/9345521003774_20241014-134529_back_addGood_5478c9a48b8c_800_18358205530.mp4: 640x512 5.3ms\n",
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"video 1/1 (85/86) /home/ieemoo0337/projects/datasets/FP/9345521003774/9345521003774_20241014-134529_back_addGood_5478c9a48b8c_800_18358205530.mp4: 640x512 5.3ms\n",
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"/home/ieemoo0337/projects/detecttracking/tracking/traclus.py:163: RuntimeWarning: divide by zero encountered in scalar divide\n",
|
||
" tan_theta0 = (shorter_slope - longer_slope) / (1 + shorter_slope * longer_slope)\n",
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||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
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||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
|
||
]
|
||
},
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||
{
|
||
"name": "stdout",
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||
"output_type": "stream",
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"text": [
|
||
"{'item1': {'Text': 'Farm Milk Powder', 'Color': '白色', 'Shape': '圆柱形', 'Material': '金属', 'Category': '乳制品'}, 'item2': {'Text': '未知', 'Color': '未知', 'Shape': '未知', 'Material': '未知', 'Category': '未知'}, 'is_Same': False}\n",
|
||
"barcode: 9344949000136\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/9344949000136/9344949000136_20241017-155118_back_returnGood_5478c9a48c3e_1205_13586533739.mp4\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/9344949000136/9556041614047.jpg\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
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||
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|
||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
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||
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|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
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||
"text": [
|
||
"load model resnet18 \n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
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"video 1/1 (50/54) /home/ieemoo0337/projects/datasets/FP/9344949000136/9344949000136_20241017-155118_back_returnGood_5478c9a48c3e_1205_13586533739.mp4: 640x512 5.5ms\n",
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"video 1/1 (51/54) /home/ieemoo0337/projects/datasets/FP/9344949000136/9344949000136_20241017-155118_back_returnGood_5478c9a48c3e_1205_13586533739.mp4: 640x512 5.5ms\n",
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"video 1/1 (52/54) /home/ieemoo0337/projects/datasets/FP/9344949000136/9344949000136_20241017-155118_back_returnGood_5478c9a48c3e_1205_13586533739.mp4: 640x512 5.4ms\n",
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"video 1/1 (53/54) /home/ieemoo0337/projects/datasets/FP/9344949000136/9344949000136_20241017-155118_back_returnGood_5478c9a48c3e_1205_13586533739.mp4: 640x512 5.4ms\n",
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"video 1/1 (54/54) /home/ieemoo0337/projects/datasets/FP/9344949000136/9344949000136_20241017-155118_back_returnGood_5478c9a48c3e_1205_13586533739.mp4: 640x512 5.4ms\n",
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||
"/home/ieemoo0337/projects/detecttracking/tracking/traclus.py:163: RuntimeWarning: divide by zero encountered in scalar divide\n",
|
||
" tan_theta0 = (shorter_slope - longer_slope) / (1 + shorter_slope * longer_slope)\n",
|
||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
|
||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
|
||
]
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||
},
|
||
{
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||
"name": "stdout",
|
||
"output_type": "stream",
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||
"text": [
|
||
"{'item1': {'Text': '雄鸡标', 'Color': '绿色', 'Shape': '圆形', 'Material': '金属', 'Category': '罐头'}, 'item2': {'Text': 'Full Cream', 'Color': '白色', 'Shape': '圆形', 'Material': '塑料', 'Category': '护肤品'}, 'is_Same': False}\n",
|
||
"barcode: 9415262030039\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/9415262030039/9415262030039_20241020-101645_back_addGood_5478c9a48c3e_270_18058629568.mp4\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/9415262030039/8996001356326.jpg\n"
|
||
]
|
||
},
|
||
{
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||
"name": "stderr",
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||
"output_type": "stream",
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"text": [
|
||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
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|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"load model resnet18 \n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
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"video 1/1 (69/73) /home/ieemoo0337/projects/datasets/FP/9415262030039/9415262030039_20241020-101645_back_addGood_5478c9a48c3e_270_18058629568.mp4: 640x512 5.5ms\n",
|
||
"video 1/1 (70/73) /home/ieemoo0337/projects/datasets/FP/9415262030039/9415262030039_20241020-101645_back_addGood_5478c9a48c3e_270_18058629568.mp4: 640x512 5.5ms\n",
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||
"video 1/1 (71/73) /home/ieemoo0337/projects/datasets/FP/9415262030039/9415262030039_20241020-101645_back_addGood_5478c9a48c3e_270_18058629568.mp4: 640x512 5.5ms\n",
|
||
"video 1/1 (72/73) /home/ieemoo0337/projects/datasets/FP/9415262030039/9415262030039_20241020-101645_back_addGood_5478c9a48c3e_270_18058629568.mp4: 640x512 5.5ms\n",
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||
"video 1/1 (73/73) /home/ieemoo0337/projects/datasets/FP/9415262030039/9415262030039_20241020-101645_back_addGood_5478c9a48c3e_270_18058629568.mp4: 640x512 5.5ms\n",
|
||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
|
||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"{'item1': {'Text': '爱时乐ASTick', 'Color': '红色', 'Shape': '圆柱形', 'Material': '金属', 'Category': '零食'}, 'item2': {'Text': '未知', 'Color': '未知', 'Shape': '未知', 'Material': '未知', 'Category': '未知'}, 'is_Same': False}\n",
|
||
"barcode: 8993175537391\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/8993175537391/9345521001152.jpg\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/8993175537391/8993175537391_20241017-120052_back_addGood_5478c9a51ba6_5_18358205530.mp4\n"
|
||
]
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||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
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||
"text": [
|
||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
"video 1/1 (1/49) /home/ieemoo0337/projects/datasets/FP/8993175537391/8993175537391_20241017-120052_back_addGood_5478c9a51ba6_5_18358205530.mp4: 640x512 6.0ms\n",
|
||
"video 1/1 (2/49) /home/ieemoo0337/projects/datasets/FP/8993175537391/8993175537391_20241017-120052_back_addGood_5478c9a51ba6_5_18358205530.mp4: 640x512 5.4ms\n",
|
||
"video 1/1 (3/49) /home/ieemoo0337/projects/datasets/FP/8993175537391/8993175537391_20241017-120052_back_addGood_5478c9a51ba6_5_18358205530.mp4: 640x512 5.5ms\n",
|
||
"video 1/1 (4/49) /home/ieemoo0337/projects/datasets/FP/8993175537391/8993175537391_20241017-120052_back_addGood_5478c9a51ba6_5_18358205530.mp4: 640x512 5.5ms\n",
|
||
"video 1/1 (5/49) /home/ieemoo0337/projects/datasets/FP/8993175537391/8993175537391_20241017-120052_back_addGood_5478c9a51ba6_5_18358205530.mp4: 640x512 5.6ms\n",
|
||
"video 1/1 (6/49) /home/ieemoo0337/projects/datasets/FP/8993175537391/8993175537391_20241017-120052_back_addGood_5478c9a51ba6_5_18358205530.mp4: 640x512 5.4ms\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"load model resnet18 \n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
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"output_type": "stream",
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"video 1/1 (8/49) /home/ieemoo0337/projects/datasets/FP/8993175537391/8993175537391_20241017-120052_back_addGood_5478c9a51ba6_5_18358205530.mp4: 640x512 5.5ms\n",
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"video 1/1 (9/49) /home/ieemoo0337/projects/datasets/FP/8993175537391/8993175537391_20241017-120052_back_addGood_5478c9a51ba6_5_18358205530.mp4: 640x512 5.5ms\n",
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"video 1/1 (10/49) /home/ieemoo0337/projects/datasets/FP/8993175537391/8993175537391_20241017-120052_back_addGood_5478c9a51ba6_5_18358205530.mp4: 640x512 5.4ms\n",
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"video 1/1 (12/49) /home/ieemoo0337/projects/datasets/FP/8993175537391/8993175537391_20241017-120052_back_addGood_5478c9a51ba6_5_18358205530.mp4: 640x512 5.4ms\n",
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"video 1/1 (14/49) /home/ieemoo0337/projects/datasets/FP/8993175537391/8993175537391_20241017-120052_back_addGood_5478c9a51ba6_5_18358205530.mp4: 640x512 5.4ms\n",
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"video 1/1 (15/49) /home/ieemoo0337/projects/datasets/FP/8993175537391/8993175537391_20241017-120052_back_addGood_5478c9a51ba6_5_18358205530.mp4: 640x512 5.5ms\n",
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"video 1/1 (21/49) /home/ieemoo0337/projects/datasets/FP/8993175537391/8993175537391_20241017-120052_back_addGood_5478c9a51ba6_5_18358205530.mp4: 640x512 5.6ms\n",
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"video 1/1 (22/49) /home/ieemoo0337/projects/datasets/FP/8993175537391/8993175537391_20241017-120052_back_addGood_5478c9a51ba6_5_18358205530.mp4: 640x512 5.6ms\n",
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"video 1/1 (23/49) /home/ieemoo0337/projects/datasets/FP/8993175537391/8993175537391_20241017-120052_back_addGood_5478c9a51ba6_5_18358205530.mp4: 640x512 5.6ms\n",
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"video 1/1 (24/49) /home/ieemoo0337/projects/datasets/FP/8993175537391/8993175537391_20241017-120052_back_addGood_5478c9a51ba6_5_18358205530.mp4: 640x512 5.6ms\n",
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"video 1/1 (25/49) /home/ieemoo0337/projects/datasets/FP/8993175537391/8993175537391_20241017-120052_back_addGood_5478c9a51ba6_5_18358205530.mp4: 640x512 5.6ms\n",
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"video 1/1 (26/49) /home/ieemoo0337/projects/datasets/FP/8993175537391/8993175537391_20241017-120052_back_addGood_5478c9a51ba6_5_18358205530.mp4: 640x512 5.6ms\n",
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||
"video 1/1 (27/49) /home/ieemoo0337/projects/datasets/FP/8993175537391/8993175537391_20241017-120052_back_addGood_5478c9a51ba6_5_18358205530.mp4: 640x512 5.8ms\n",
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"video 1/1 (28/49) /home/ieemoo0337/projects/datasets/FP/8993175537391/8993175537391_20241017-120052_back_addGood_5478c9a51ba6_5_18358205530.mp4: 640x512 5.6ms\n",
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"video 1/1 (29/49) /home/ieemoo0337/projects/datasets/FP/8993175537391/8993175537391_20241017-120052_back_addGood_5478c9a51ba6_5_18358205530.mp4: 640x512 5.5ms\n",
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||
"video 1/1 (30/49) /home/ieemoo0337/projects/datasets/FP/8993175537391/8993175537391_20241017-120052_back_addGood_5478c9a51ba6_5_18358205530.mp4: 640x512 5.7ms\n",
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"video 1/1 (31/49) /home/ieemoo0337/projects/datasets/FP/8993175537391/8993175537391_20241017-120052_back_addGood_5478c9a51ba6_5_18358205530.mp4: 640x512 5.7ms\n",
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"video 1/1 (32/49) /home/ieemoo0337/projects/datasets/FP/8993175537391/8993175537391_20241017-120052_back_addGood_5478c9a51ba6_5_18358205530.mp4: 640x512 5.5ms\n",
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"video 1/1 (33/49) /home/ieemoo0337/projects/datasets/FP/8993175537391/8993175537391_20241017-120052_back_addGood_5478c9a51ba6_5_18358205530.mp4: 640x512 5.6ms\n",
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"video 1/1 (34/49) /home/ieemoo0337/projects/datasets/FP/8993175537391/8993175537391_20241017-120052_back_addGood_5478c9a51ba6_5_18358205530.mp4: 640x512 5.6ms\n",
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"video 1/1 (35/49) /home/ieemoo0337/projects/datasets/FP/8993175537391/8993175537391_20241017-120052_back_addGood_5478c9a51ba6_5_18358205530.mp4: 640x512 5.6ms\n",
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"video 1/1 (38/49) /home/ieemoo0337/projects/datasets/FP/8993175537391/8993175537391_20241017-120052_back_addGood_5478c9a51ba6_5_18358205530.mp4: 640x512 5.6ms\n",
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"video 1/1 (39/49) /home/ieemoo0337/projects/datasets/FP/8993175537391/8993175537391_20241017-120052_back_addGood_5478c9a51ba6_5_18358205530.mp4: 640x512 5.6ms\n",
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||
"video 1/1 (40/49) /home/ieemoo0337/projects/datasets/FP/8993175537391/8993175537391_20241017-120052_back_addGood_5478c9a51ba6_5_18358205530.mp4: 640x512 5.6ms\n",
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"video 1/1 (41/49) /home/ieemoo0337/projects/datasets/FP/8993175537391/8993175537391_20241017-120052_back_addGood_5478c9a51ba6_5_18358205530.mp4: 640x512 5.6ms\n",
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"video 1/1 (42/49) /home/ieemoo0337/projects/datasets/FP/8993175537391/8993175537391_20241017-120052_back_addGood_5478c9a51ba6_5_18358205530.mp4: 640x512 5.6ms\n",
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"video 1/1 (43/49) /home/ieemoo0337/projects/datasets/FP/8993175537391/8993175537391_20241017-120052_back_addGood_5478c9a51ba6_5_18358205530.mp4: 640x512 5.6ms\n",
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"video 1/1 (44/49) /home/ieemoo0337/projects/datasets/FP/8993175537391/8993175537391_20241017-120052_back_addGood_5478c9a51ba6_5_18358205530.mp4: 640x512 5.6ms\n",
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||
"video 1/1 (45/49) /home/ieemoo0337/projects/datasets/FP/8993175537391/8993175537391_20241017-120052_back_addGood_5478c9a51ba6_5_18358205530.mp4: 640x512 5.5ms\n",
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||
"video 1/1 (46/49) /home/ieemoo0337/projects/datasets/FP/8993175537391/8993175537391_20241017-120052_back_addGood_5478c9a51ba6_5_18358205530.mp4: 640x512 5.6ms\n",
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||
"video 1/1 (47/49) /home/ieemoo0337/projects/datasets/FP/8993175537391/8993175537391_20241017-120052_back_addGood_5478c9a51ba6_5_18358205530.mp4: 640x512 5.6ms\n",
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||
"video 1/1 (48/49) /home/ieemoo0337/projects/datasets/FP/8993175537391/8993175537391_20241017-120052_back_addGood_5478c9a51ba6_5_18358205530.mp4: 640x512 5.5ms\n",
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||
"video 1/1 (49/49) /home/ieemoo0337/projects/datasets/FP/8993175537391/8993175537391_20241017-120052_back_addGood_5478c9a51ba6_5_18358205530.mp4: 640x512 5.6ms\n",
|
||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
|
||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"{'item1': {'Text': 'GreenKosy', 'Color': '白色', 'Shape': '圆柱形', 'Material': '塑料', 'Category': '洗发水'}, 'item2': {'Text': '未知', 'Color': '未知', 'Shape': '未知', 'Material': '未知', 'Category': '未知'}, 'is_Same': False}\n",
|
||
"barcode: 8886001012295\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/8886001012295/9311493002534.jpg\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/8886001012295/8886001012295_20241019-142756_back_addGood_5478c9a49bfc_925_13773168720.mp4\n"
|
||
]
|
||
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|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
"video 1/1 (1/89) /home/ieemoo0337/projects/datasets/FP/8886001012295/8886001012295_20241019-142756_back_addGood_5478c9a49bfc_925_13773168720.mp4: 640x512 6.1ms\n",
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"video 1/1 (2/89) /home/ieemoo0337/projects/datasets/FP/8886001012295/8886001012295_20241019-142756_back_addGood_5478c9a49bfc_925_13773168720.mp4: 640x512 5.6ms\n",
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"video 1/1 (3/89) /home/ieemoo0337/projects/datasets/FP/8886001012295/8886001012295_20241019-142756_back_addGood_5478c9a49bfc_925_13773168720.mp4: 640x512 5.4ms\n",
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||
"video 1/1 (4/89) /home/ieemoo0337/projects/datasets/FP/8886001012295/8886001012295_20241019-142756_back_addGood_5478c9a49bfc_925_13773168720.mp4: 640x512 5.4ms\n",
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"video 1/1 (7/89) /home/ieemoo0337/projects/datasets/FP/8886001012295/8886001012295_20241019-142756_back_addGood_5478c9a49bfc_925_13773168720.mp4: 640x512 5.5ms\n"
|
||
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|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"load model resnet18 \n"
|
||
]
|
||
},
|
||
{
|
||
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|
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"video 1/1 (85/89) /home/ieemoo0337/projects/datasets/FP/8886001012295/8886001012295_20241019-142756_back_addGood_5478c9a49bfc_925_13773168720.mp4: 640x512 5.5ms\n",
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"video 1/1 (87/89) /home/ieemoo0337/projects/datasets/FP/8886001012295/8886001012295_20241019-142756_back_addGood_5478c9a49bfc_925_13773168720.mp4: 640x512 5.5ms\n",
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"video 1/1 (88/89) /home/ieemoo0337/projects/datasets/FP/8886001012295/8886001012295_20241019-142756_back_addGood_5478c9a49bfc_925_13773168720.mp4: 640x512 5.5ms\n",
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"video 1/1 (89/89) /home/ieemoo0337/projects/datasets/FP/8886001012295/8886001012295_20241019-142756_back_addGood_5478c9a49bfc_925_13773168720.mp4: 640x512 5.6ms\n",
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||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
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||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
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||
]
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||
},
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||
{
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||
"name": "stdout",
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||
"output_type": "stream",
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||
"text": [
|
||
"{'item1': {'Text': 'Bundaberg BLOOD ORANGE SPARKLING DRINK', 'Color': '红色', 'Shape': '圆柱形', 'Material': '玻璃', 'Category': '饮料'}, 'item2': {'Text': 'Danisa Traditional Butter Cookies', 'Color': '白色', 'Shape': '长方形', 'Material': '纸', 'Category': '饼干'}, 'is_Same': False}\n",
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||
"barcode: 8809713911410\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/8809713911410/6975573940135.jpg\n",
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||
"video: /home/ieemoo0337/projects/datasets/FP/8809713911410/8809713911410_20241018-175929_back_returnGood_5478c9a53be2_425_18996891184.mp4\n"
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||
]
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{
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"name": "stderr",
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"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
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"video 1/1 (1/62) /home/ieemoo0337/projects/datasets/FP/8809713911410/8809713911410_20241018-175929_back_returnGood_5478c9a53be2_425_18996891184.mp4: 640x512 6.0ms\n",
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]
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"load model resnet18 \n"
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]
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"video 1/1 (38/62) /home/ieemoo0337/projects/datasets/FP/8809713911410/8809713911410_20241018-175929_back_returnGood_5478c9a53be2_425_18996891184.mp4: 640x512 (no detections), 5.7ms\n",
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"video 1/1 (39/62) /home/ieemoo0337/projects/datasets/FP/8809713911410/8809713911410_20241018-175929_back_returnGood_5478c9a53be2_425_18996891184.mp4: 640x512 (no detections), 5.7ms\n",
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"video 1/1 (40/62) /home/ieemoo0337/projects/datasets/FP/8809713911410/8809713911410_20241018-175929_back_returnGood_5478c9a53be2_425_18996891184.mp4: 640x512 (no detections), 5.7ms\n",
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"video 1/1 (41/62) /home/ieemoo0337/projects/datasets/FP/8809713911410/8809713911410_20241018-175929_back_returnGood_5478c9a53be2_425_18996891184.mp4: 640x512 (no detections), 5.7ms\n",
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"video 1/1 (42/62) /home/ieemoo0337/projects/datasets/FP/8809713911410/8809713911410_20241018-175929_back_returnGood_5478c9a53be2_425_18996891184.mp4: 640x512 (no detections), 5.7ms\n",
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"video 1/1 (43/62) /home/ieemoo0337/projects/datasets/FP/8809713911410/8809713911410_20241018-175929_back_returnGood_5478c9a53be2_425_18996891184.mp4: 640x512 (no detections), 5.7ms\n",
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"video 1/1 (44/62) /home/ieemoo0337/projects/datasets/FP/8809713911410/8809713911410_20241018-175929_back_returnGood_5478c9a53be2_425_18996891184.mp4: 640x512 (no detections), 5.8ms\n",
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"video 1/1 (45/62) /home/ieemoo0337/projects/datasets/FP/8809713911410/8809713911410_20241018-175929_back_returnGood_5478c9a53be2_425_18996891184.mp4: 640x512 (no detections), 5.7ms\n",
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"video 1/1 (46/62) /home/ieemoo0337/projects/datasets/FP/8809713911410/8809713911410_20241018-175929_back_returnGood_5478c9a53be2_425_18996891184.mp4: 640x512 (no detections), 5.7ms\n",
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"video 1/1 (47/62) /home/ieemoo0337/projects/datasets/FP/8809713911410/8809713911410_20241018-175929_back_returnGood_5478c9a53be2_425_18996891184.mp4: 640x512 (no detections), 5.7ms\n",
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"video 1/1 (48/62) /home/ieemoo0337/projects/datasets/FP/8809713911410/8809713911410_20241018-175929_back_returnGood_5478c9a53be2_425_18996891184.mp4: 640x512 (no detections), 5.7ms\n",
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"video 1/1 (49/62) /home/ieemoo0337/projects/datasets/FP/8809713911410/8809713911410_20241018-175929_back_returnGood_5478c9a53be2_425_18996891184.mp4: 640x512 (no detections), 5.8ms\n",
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"video 1/1 (50/62) /home/ieemoo0337/projects/datasets/FP/8809713911410/8809713911410_20241018-175929_back_returnGood_5478c9a53be2_425_18996891184.mp4: 640x512 (no detections), 5.7ms\n",
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"video 1/1 (53/62) /home/ieemoo0337/projects/datasets/FP/8809713911410/8809713911410_20241018-175929_back_returnGood_5478c9a53be2_425_18996891184.mp4: 640x512 (no detections), 5.8ms\n",
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"video 1/1 (54/62) /home/ieemoo0337/projects/datasets/FP/8809713911410/8809713911410_20241018-175929_back_returnGood_5478c9a53be2_425_18996891184.mp4: 640x512 (no detections), 5.7ms\n",
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"video 1/1 (55/62) /home/ieemoo0337/projects/datasets/FP/8809713911410/8809713911410_20241018-175929_back_returnGood_5478c9a53be2_425_18996891184.mp4: 640x512 (no detections), 5.7ms\n",
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"video 1/1 (56/62) /home/ieemoo0337/projects/datasets/FP/8809713911410/8809713911410_20241018-175929_back_returnGood_5478c9a53be2_425_18996891184.mp4: 640x512 (no detections), 5.8ms\n",
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"video 1/1 (57/62) /home/ieemoo0337/projects/datasets/FP/8809713911410/8809713911410_20241018-175929_back_returnGood_5478c9a53be2_425_18996891184.mp4: 640x512 (no detections), 5.6ms\n",
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"video 1/1 (58/62) /home/ieemoo0337/projects/datasets/FP/8809713911410/8809713911410_20241018-175929_back_returnGood_5478c9a53be2_425_18996891184.mp4: 640x512 (no detections), 5.7ms\n",
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"video 1/1 (59/62) /home/ieemoo0337/projects/datasets/FP/8809713911410/8809713911410_20241018-175929_back_returnGood_5478c9a53be2_425_18996891184.mp4: 640x512 (no detections), 5.7ms\n",
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"video 1/1 (60/62) /home/ieemoo0337/projects/datasets/FP/8809713911410/8809713911410_20241018-175929_back_returnGood_5478c9a53be2_425_18996891184.mp4: 640x512 (no detections), 5.7ms\n",
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"video 1/1 (61/62) /home/ieemoo0337/projects/datasets/FP/8809713911410/8809713911410_20241018-175929_back_returnGood_5478c9a53be2_425_18996891184.mp4: 640x512 (no detections), 5.7ms\n",
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"video 1/1 (62/62) /home/ieemoo0337/projects/datasets/FP/8809713911410/8809713911410_20241018-175929_back_returnGood_5478c9a53be2_425_18996891184.mp4: 640x512 (no detections), 5.7ms\n",
|
||
"/home/ieemoo0337/projects/detecttracking/tracking/traclus.py:163: RuntimeWarning: divide by zero encountered in scalar divide\n",
|
||
" tan_theta0 = (shorter_slope - longer_slope) / (1 + shorter_slope * longer_slope)\n",
|
||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
|
||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"{'item1': {'Text': '小苏打果蔬洗洁精', 'Color': '白色', 'Shape': '长方形', 'Material': '塑料', 'Category': '清洁用品'}, 'item2': {'Text': 'OKI', 'Color': '绿色', 'Shape': '圆柱形', 'Material': '塑料', 'Category': '饮料'}, 'is_Same': False}\n",
|
||
"barcode: 9346506003406\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/9346506003406/8993083932943.jpg\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/9346506003406/9346506003406_20241019-112136_back_returnGood_5478c9a49bfc_1000_13773168720.mp4\n"
|
||
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||
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||
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||
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||
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|
||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
"video 1/1 (1/62) /home/ieemoo0337/projects/datasets/FP/9346506003406/9346506003406_20241019-112136_back_returnGood_5478c9a49bfc_1000_13773168720.mp4: 640x512 6.9ms\n",
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"video 1/1 (5/62) /home/ieemoo0337/projects/datasets/FP/9346506003406/9346506003406_20241019-112136_back_returnGood_5478c9a49bfc_1000_13773168720.mp4: 640x512 5.6ms\n"
|
||
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|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"load model resnet18 \n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
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"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
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||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
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||
]
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||
},
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||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
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||
"text": [
|
||
"{'item1': {'Text': 'Strawberry BEAR COOKIES', 'Color': '粉色', 'Shape': '熊的形状', 'Material': '饼干', 'Category': '零食'}, 'item2': {'Text': 'B Active LifeStyle Milk', 'Color': '绿色', 'Shape': '圆柱形', 'Material': '牛奶', 'Category': '乳制品'}, 'is_Same': False}\n",
|
||
"barcode: 9350013003071\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/9350013003071/9421902960826.jpg\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/9350013003071/9350013003071_20241019-163322_back_returnGood_5478c9a48c02_825_18996891184.mp4\n"
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||
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||
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||
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|
||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
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||
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|
||
},
|
||
{
|
||
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|
||
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||
"text": [
|
||
"load model resnet18 \n"
|
||
]
|
||
},
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||
{
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||
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||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
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||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"{'item1': {'Text': '至初较大婴儿配方奶粉(6-12月龄,2段)', 'Color': '紫色', 'Shape': '圆柱形', 'Material': '塑料', 'Category': '婴儿配方奶粉'}, 'item2': {'Text': '未知', 'Color': '未知', 'Shape': '未知', 'Material': '未知', 'Category': '未知'}, 'is_Same': False}\n",
|
||
"barcode: 9345521003767\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/9345521003767/9345521003767_20241018-184505_back_returnGood_5478c9a53bd4_795_15027299265.mp4\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/9345521003767/9415007301578.jpg\n"
|
||
]
|
||
},
|
||
{
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||
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||
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|
||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
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||
},
|
||
{
|
||
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|
||
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||
"text": [
|
||
"load model resnet18 \n"
|
||
]
|
||
},
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||
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||
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"video 1/1 (90/95) /home/ieemoo0337/projects/datasets/FP/9345521003767/9345521003767_20241018-184505_back_returnGood_5478c9a53bd4_795_15027299265.mp4: 640x512 5.5ms\n",
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"video 1/1 (91/95) /home/ieemoo0337/projects/datasets/FP/9345521003767/9345521003767_20241018-184505_back_returnGood_5478c9a53bd4_795_15027299265.mp4: 640x512 5.5ms\n",
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"video 1/1 (92/95) /home/ieemoo0337/projects/datasets/FP/9345521003767/9345521003767_20241018-184505_back_returnGood_5478c9a53bd4_795_15027299265.mp4: 640x512 5.4ms\n",
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"video 1/1 (93/95) /home/ieemoo0337/projects/datasets/FP/9345521003767/9345521003767_20241018-184505_back_returnGood_5478c9a53bd4_795_15027299265.mp4: 640x512 5.5ms\n",
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"video 1/1 (94/95) /home/ieemoo0337/projects/datasets/FP/9345521003767/9345521003767_20241018-184505_back_returnGood_5478c9a53bd4_795_15027299265.mp4: 640x512 5.5ms\n",
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"video 1/1 (95/95) /home/ieemoo0337/projects/datasets/FP/9345521003767/9345521003767_20241018-184505_back_returnGood_5478c9a53bd4_795_15027299265.mp4: 640x512 5.5ms\n",
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||
"/home/ieemoo0337/projects/detecttracking/tracking/traclus.py:163: RuntimeWarning: divide by zero encountered in scalar divide\n",
|
||
" tan_theta0 = (shorter_slope - longer_slope) / (1 + shorter_slope * longer_slope)\n",
|
||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
|
||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n"
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||
]
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||
},
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||
{
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||
"name": "stdout",
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||
"output_type": "stream",
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||
"text": [
|
||
"{'item1': {'Text': 'Anchor Salted Pure New Zealand Butter 安佳黄油', 'Color': '白色', 'Shape': '长方形', 'Material': '塑料', 'Category': '黄油'}, 'item2': {'Text': '未知', 'Color': '未知', 'Shape': '未知', 'Material': '未知', 'Category': '未知'}, 'is_Same': False}\n",
|
||
"barcode: 8850511311100\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/8850511311100/9310072000282.jpg\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/8850511311100/8850511311100_20241018-142900_back_returnGood_5478c9a49bfc_605_13867273486.mp4\n"
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||
]
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||
},
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||
{
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||
"name": "stderr",
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||
"output_type": "stream",
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||
"text": [
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n",
|
||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
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]
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},
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{
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"name": "stdout",
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||
"output_type": "stream",
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"text": [
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||
"load model resnet18 \n"
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]
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},
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"video 1/1 (71/73) /home/ieemoo0337/projects/datasets/FP/8850511311100/8850511311100_20241018-142900_back_returnGood_5478c9a49bfc_605_13867273486.mp4: 640x512 5.5ms\n",
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"video 1/1 (72/73) /home/ieemoo0337/projects/datasets/FP/8850511311100/8850511311100_20241018-142900_back_returnGood_5478c9a49bfc_605_13867273486.mp4: 640x512 5.6ms\n",
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"video 1/1 (73/73) /home/ieemoo0337/projects/datasets/FP/8850511311100/8850511311100_20241018-142900_back_returnGood_5478c9a49bfc_605_13867273486.mp4: 640x512 5.6ms\n",
|
||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
|
||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"{'item1': {'Text': 'Tim Tam Original', 'Color': '棕色', 'Shape': '长方形', 'Material': '纸', 'Category': '饼干'}, 'item2': {'Text': 'KFC', 'Color': '红色', 'Shape': '圆柱形', 'Material': '塑料', 'Category': '调味品'}, 'is_Same': False}\n",
|
||
"barcode: 9415007301585\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/9415007301585/9335390002121.jpg\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/9415007301585/9415007301585_20241018-162833_back_addGood_5478c9a48c3e_240_14785332147.mp4\n"
|
||
]
|
||
},
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||
{
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||
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|
||
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||
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|
||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
"video 1/1 (1/72) /home/ieemoo0337/projects/datasets/FP/9415007301585/9415007301585_20241018-162833_back_addGood_5478c9a48c3e_240_14785332147.mp4: 640x512 6.8ms\n",
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"video 1/1 (2/72) /home/ieemoo0337/projects/datasets/FP/9415007301585/9415007301585_20241018-162833_back_addGood_5478c9a48c3e_240_14785332147.mp4: 640x512 5.6ms\n",
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]
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},
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{
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"load model resnet18 \n"
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"video 1/1 (69/72) /home/ieemoo0337/projects/datasets/FP/9415007301585/9415007301585_20241018-162833_back_addGood_5478c9a48c3e_240_14785332147.mp4: 640x512 5.5ms\n",
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"video 1/1 (70/72) /home/ieemoo0337/projects/datasets/FP/9415007301585/9415007301585_20241018-162833_back_addGood_5478c9a48c3e_240_14785332147.mp4: 640x512 5.5ms\n",
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"video 1/1 (71/72) /home/ieemoo0337/projects/datasets/FP/9415007301585/9415007301585_20241018-162833_back_addGood_5478c9a48c3e_240_14785332147.mp4: 640x512 5.5ms\n",
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||
"/home/ieemoo0337/projects/detecttracking/tracking/traclus.py:163: RuntimeWarning: divide by zero encountered in scalar divide\n",
|
||
" tan_theta0 = (shorter_slope - longer_slope) / (1 + shorter_slope * longer_slope)\n",
|
||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
|
||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"{'item1': {'Text': 'a2 Milk® Full cream milk', 'Color': '绿色', 'Shape': '长方形', 'Material': '纸', 'Category': '乳制品'}, 'item2': {'Text': 'A2 New Zealand', 'Color': '白色', 'Shape': '长方形', 'Material': '纸', 'Category': '乳制品'}, 'is_Same': False}\n",
|
||
"barcode: 8859468700319\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/8859468700319/8859468700319_20241017-140211_back_returnGood_5478c9a48c3e_650_13586533739.mp4\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/8859468700319/9315090208504.jpg\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n",
|
||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
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{
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"name": "stdout",
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"load model resnet18 \n"
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"video 1/1 (50/52) /home/ieemoo0337/projects/datasets/FP/8859468700319/8859468700319_20241017-140211_back_returnGood_5478c9a48c3e_650_13586533739.mp4: 640x512 5.4ms\n",
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|
||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
|
||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"{'item1': {'Text': '澳牧纯牛奶', 'Color': '白色', 'Shape': '长方形', 'Material': '纸箱', 'Category': '乳制品'}, 'item2': {'Text': '未知', 'Color': '未知', 'Shape': '未知', 'Material': '未知', 'Category': '未知'}, 'is_Same': False}\n",
|
||
"barcode: 9421902960826\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/9421902960826/9350013003071.jpg\n"
|
||
]
|
||
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|
||
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|
||
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|
||
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|
||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
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|
||
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|
||
},
|
||
{
|
||
"name": "stdout",
|
||
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|
||
"text": [
|
||
"load model resnet18 \n"
|
||
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|
||
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|
||
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||
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"video 1/1 (28/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 5.4ms\n",
|
||
"video 1/1 (29/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 5.5ms\n",
|
||
"video 1/1 (30/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 5.4ms\n",
|
||
"video 1/1 (31/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 5.5ms\n",
|
||
"video 1/1 (32/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 5.5ms\n",
|
||
"video 1/1 (33/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 5.5ms\n",
|
||
"video 1/1 (34/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 5.6ms\n",
|
||
"video 1/1 (35/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 5.5ms\n",
|
||
"video 1/1 (36/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 5.5ms\n",
|
||
"video 1/1 (37/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 5.5ms\n",
|
||
"video 1/1 (38/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 6.0ms\n",
|
||
"video 1/1 (39/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 5.8ms\n",
|
||
"video 1/1 (40/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 6.0ms\n",
|
||
"video 1/1 (41/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 5.9ms\n",
|
||
"video 1/1 (42/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 5.9ms\n",
|
||
"video 1/1 (43/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 5.9ms\n",
|
||
"video 1/1 (44/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 5.8ms\n",
|
||
"video 1/1 (45/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 5.8ms\n",
|
||
"video 1/1 (46/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 5.9ms\n",
|
||
"video 1/1 (47/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 6.0ms\n",
|
||
"video 1/1 (48/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 6.0ms\n",
|
||
"video 1/1 (49/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 5.8ms\n",
|
||
"video 1/1 (50/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 6.0ms\n",
|
||
"video 1/1 (51/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 6.0ms\n",
|
||
"video 1/1 (52/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 5.9ms\n",
|
||
"video 1/1 (53/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 6.0ms\n",
|
||
"video 1/1 (54/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 6.0ms\n",
|
||
"video 1/1 (55/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 5.9ms\n",
|
||
"video 1/1 (56/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 5.9ms\n",
|
||
"video 1/1 (57/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 5.9ms\n",
|
||
"video 1/1 (58/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 5.8ms\n",
|
||
"video 1/1 (59/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 5.9ms\n",
|
||
"video 1/1 (60/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 5.9ms\n",
|
||
"video 1/1 (61/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 6.0ms\n",
|
||
"video 1/1 (62/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 5.9ms\n",
|
||
"video 1/1 (63/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 5.9ms\n",
|
||
"video 1/1 (64/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 5.8ms\n",
|
||
"video 1/1 (65/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 5.8ms\n",
|
||
"video 1/1 (66/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 5.8ms\n",
|
||
"video 1/1 (67/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 5.9ms\n",
|
||
"video 1/1 (68/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 5.9ms\n",
|
||
"video 1/1 (69/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 5.9ms\n",
|
||
"video 1/1 (70/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 5.9ms\n",
|
||
"video 1/1 (71/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 5.9ms\n",
|
||
"video 1/1 (72/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 6.0ms\n",
|
||
"video 1/1 (73/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 5.8ms\n",
|
||
"video 1/1 (74/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 6.1ms\n",
|
||
"video 1/1 (75/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 5.9ms\n",
|
||
"video 1/1 (76/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 7.3ms\n",
|
||
"video 1/1 (77/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 5.9ms\n",
|
||
"video 1/1 (78/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 5.8ms\n",
|
||
"video 1/1 (79/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 5.9ms\n",
|
||
"video 1/1 (80/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 5.9ms\n",
|
||
"video 1/1 (81/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 5.9ms\n",
|
||
"video 1/1 (82/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 5.9ms\n",
|
||
"video 1/1 (83/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 6.0ms\n",
|
||
"video 1/1 (84/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 5.9ms\n",
|
||
"video 1/1 (85/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 6.0ms\n",
|
||
"video 1/1 (86/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 5.8ms\n",
|
||
"video 1/1 (87/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 6.1ms\n",
|
||
"video 1/1 (88/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 5.9ms\n",
|
||
"video 1/1 (89/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 6.1ms\n",
|
||
"video 1/1 (90/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 5.8ms\n",
|
||
"video 1/1 (91/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 6.1ms\n",
|
||
"video 1/1 (92/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 5.8ms\n",
|
||
"video 1/1 (93/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 5.9ms\n",
|
||
"video 1/1 (94/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 5.9ms\n",
|
||
"video 1/1 (95/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 5.9ms\n",
|
||
"video 1/1 (96/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 6.0ms\n",
|
||
"video 1/1 (97/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 7.4ms\n",
|
||
"video 1/1 (98/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 6.0ms\n",
|
||
"video 1/1 (99/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 6.2ms\n",
|
||
"video 1/1 (100/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 6.2ms\n",
|
||
"video 1/1 (101/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 6.2ms\n",
|
||
"video 1/1 (102/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 6.0ms\n",
|
||
"video 1/1 (103/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 6.0ms\n",
|
||
"video 1/1 (104/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 6.1ms\n",
|
||
"video 1/1 (105/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 6.1ms\n",
|
||
"video 1/1 (106/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 6.1ms\n",
|
||
"video 1/1 (107/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 6.0ms\n",
|
||
"video 1/1 (108/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 7.6ms\n",
|
||
"video 1/1 (109/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 6.1ms\n",
|
||
"video 1/1 (110/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 6.1ms\n",
|
||
"video 1/1 (111/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 6.1ms\n",
|
||
"video 1/1 (112/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 6.0ms\n",
|
||
"video 1/1 (113/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 6.1ms\n",
|
||
"video 1/1 (114/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 6.1ms\n",
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"video 1/1 (115/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 6.1ms\n",
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"video 1/1 (116/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 6.0ms\n",
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"video 1/1 (117/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 5.9ms\n",
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"video 1/1 (118/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 6.1ms\n",
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"video 1/1 (119/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 6.0ms\n",
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"video 1/1 (120/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 5.9ms\n",
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"video 1/1 (121/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 5.9ms\n",
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"video 1/1 (122/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 5.9ms\n",
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"video 1/1 (123/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 5.9ms\n",
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"video 1/1 (124/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 5.9ms\n",
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"video 1/1 (125/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 5.9ms\n",
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"video 1/1 (126/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 5.9ms\n",
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"video 1/1 (127/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 5.9ms\n",
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"video 1/1 (128/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 5.9ms\n",
|
||
"video 1/1 (129/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 6.2ms\n",
|
||
"video 1/1 (130/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 5.7ms\n",
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||
"video 1/1 (131/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 5.7ms\n",
|
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"video 1/1 (132/132) /home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4: 640x512 (no detections), 5.7ms\n",
|
||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
|
||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
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||
"{'item1': {'Text': 'Plant voice', 'Color': '白色', 'Shape': '圆柱形', 'Material': '塑料', 'Category': '洗发水'}, 'item2': {'Text': '洗衣液', 'Color': '紫色', 'Shape': '长方形', 'Material': '塑料', 'Category': '洗衣液'}, 'is_Same': False}\n",
|
||
"barcode: 9551010540006\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/9551010540006/8809803536486.jpg\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/9551010540006/9551010540006_20241016-165426_back_returnGood_5478c9a48b8c_0_18133699824.mp4\n"
|
||
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"name": "stderr",
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||
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|
||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
"video 1/1 (1/49) /home/ieemoo0337/projects/datasets/FP/9551010540006/9551010540006_20241016-165426_back_returnGood_5478c9a48b8c_0_18133699824.mp4: 640x512 7.1ms\n",
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"video 1/1 (3/49) /home/ieemoo0337/projects/datasets/FP/9551010540006/9551010540006_20241016-165426_back_returnGood_5478c9a48b8c_0_18133699824.mp4: 640x512 5.9ms\n",
|
||
"video 1/1 (4/49) /home/ieemoo0337/projects/datasets/FP/9551010540006/9551010540006_20241016-165426_back_returnGood_5478c9a48b8c_0_18133699824.mp4: 640x512 5.7ms\n",
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"video 1/1 (5/49) /home/ieemoo0337/projects/datasets/FP/9551010540006/9551010540006_20241016-165426_back_returnGood_5478c9a48b8c_0_18133699824.mp4: 640x512 5.7ms\n",
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"video 1/1 (6/49) /home/ieemoo0337/projects/datasets/FP/9551010540006/9551010540006_20241016-165426_back_returnGood_5478c9a48b8c_0_18133699824.mp4: 640x512 5.6ms\n"
|
||
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|
||
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|
||
{
|
||
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|
||
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"text": [
|
||
"load model resnet18 \n"
|
||
]
|
||
},
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"video 1/1 (27/49) /home/ieemoo0337/projects/datasets/FP/9551010540006/9551010540006_20241016-165426_back_returnGood_5478c9a48b8c_0_18133699824.mp4: 640x512 5.7ms\n",
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"video 1/1 (35/49) /home/ieemoo0337/projects/datasets/FP/9551010540006/9551010540006_20241016-165426_back_returnGood_5478c9a48b8c_0_18133699824.mp4: 640x512 5.6ms\n",
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"video 1/1 (39/49) /home/ieemoo0337/projects/datasets/FP/9551010540006/9551010540006_20241016-165426_back_returnGood_5478c9a48b8c_0_18133699824.mp4: 640x512 5.7ms\n",
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"video 1/1 (40/49) /home/ieemoo0337/projects/datasets/FP/9551010540006/9551010540006_20241016-165426_back_returnGood_5478c9a48b8c_0_18133699824.mp4: 640x512 5.6ms\n",
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"video 1/1 (41/49) /home/ieemoo0337/projects/datasets/FP/9551010540006/9551010540006_20241016-165426_back_returnGood_5478c9a48b8c_0_18133699824.mp4: 640x512 5.7ms\n",
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"video 1/1 (43/49) /home/ieemoo0337/projects/datasets/FP/9551010540006/9551010540006_20241016-165426_back_returnGood_5478c9a48b8c_0_18133699824.mp4: 640x512 5.7ms\n",
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"video 1/1 (44/49) /home/ieemoo0337/projects/datasets/FP/9551010540006/9551010540006_20241016-165426_back_returnGood_5478c9a48b8c_0_18133699824.mp4: 640x512 5.6ms\n",
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"video 1/1 (45/49) /home/ieemoo0337/projects/datasets/FP/9551010540006/9551010540006_20241016-165426_back_returnGood_5478c9a48b8c_0_18133699824.mp4: 640x512 5.6ms\n",
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"video 1/1 (46/49) /home/ieemoo0337/projects/datasets/FP/9551010540006/9551010540006_20241016-165426_back_returnGood_5478c9a48b8c_0_18133699824.mp4: 640x512 5.6ms\n",
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||
"video 1/1 (47/49) /home/ieemoo0337/projects/datasets/FP/9551010540006/9551010540006_20241016-165426_back_returnGood_5478c9a48b8c_0_18133699824.mp4: 640x512 5.6ms\n",
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"video 1/1 (48/49) /home/ieemoo0337/projects/datasets/FP/9551010540006/9551010540006_20241016-165426_back_returnGood_5478c9a48b8c_0_18133699824.mp4: 640x512 5.6ms\n",
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"video 1/1 (49/49) /home/ieemoo0337/projects/datasets/FP/9551010540006/9551010540006_20241016-165426_back_returnGood_5478c9a48b8c_0_18133699824.mp4: 640x512 5.6ms\n",
|
||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
|
||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"{}\n",
|
||
"barcode: 9556041613866\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/9556041613866/9556041613866_20241017-142855_back_addGood_5478c9a49bfc_210_13773168720.mp4\n",
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||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/9556041613866/8993379257644.jpg\n"
|
||
]
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},
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{
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"name": "stderr",
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"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
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},
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{
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"name": "stdout",
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"text": [
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||
"load model resnet18 \n"
|
||
]
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},
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"video 1/1 (65/66) /home/ieemoo0337/projects/datasets/FP/9556041613866/9556041613866_20241017-142855_back_addGood_5478c9a49bfc_210_13773168720.mp4: 640x512 5.6ms\n",
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|
||
"/home/ieemoo0337/projects/detecttracking/tracking/traclus.py:163: RuntimeWarning: divide by zero encountered in scalar divide\n",
|
||
" tan_theta0 = (shorter_slope - longer_slope) / (1 + shorter_slope * longer_slope)\n",
|
||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
|
||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"{'item1': {'Text': 'Popular Laundry Soap', 'Color': '白色', 'Shape': '长方体', 'Material': '肥皂', 'Category': '洗衣皂'}, 'item2': {'Text': '未知', 'Color': '未知', 'Shape': '未知', 'Material': '未知', 'Category': '未知'}, 'is_Same': False}\n",
|
||
"barcode: 9421029080278\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029081985.jpg\n"
|
||
]
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||
},
|
||
{
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||
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|
||
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||
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|
||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
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||
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||
},
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||
{
|
||
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|
||
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||
"text": [
|
||
"load model resnet18 \n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
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"text": [
|
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|
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"video 1/1 (7/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.4ms\n",
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"video 1/1 (8/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.8ms\n",
|
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"video 1/1 (9/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.9ms\n",
|
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"video 1/1 (10/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.7ms\n",
|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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"video 1/1 (30/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.5ms\n",
|
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"video 1/1 (31/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.6ms\n",
|
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"video 1/1 (32/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.5ms\n",
|
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"video 1/1 (33/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.6ms\n",
|
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"video 1/1 (34/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.6ms\n",
|
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"video 1/1 (35/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.6ms\n",
|
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"video 1/1 (36/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.6ms\n",
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"video 1/1 (37/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.6ms\n",
|
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"video 1/1 (38/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.6ms\n",
|
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"video 1/1 (39/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.7ms\n",
|
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"video 1/1 (40/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.8ms\n",
|
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"video 1/1 (41/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.9ms\n",
|
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"video 1/1 (42/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.7ms\n",
|
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"video 1/1 (43/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.7ms\n",
|
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"video 1/1 (44/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.7ms\n",
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"video 1/1 (45/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.7ms\n",
|
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"video 1/1 (46/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.8ms\n",
|
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"video 1/1 (47/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.6ms\n",
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"video 1/1 (48/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.7ms\n",
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"video 1/1 (49/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.8ms\n",
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"video 1/1 (50/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.7ms\n",
|
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"video 1/1 (51/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.7ms\n",
|
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"video 1/1 (52/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.7ms\n",
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"video 1/1 (53/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.8ms\n",
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"video 1/1 (54/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.7ms\n",
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"video 1/1 (55/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.7ms\n",
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"video 1/1 (56/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.7ms\n",
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||
"video 1/1 (57/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.9ms\n",
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||
"video 1/1 (58/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.6ms\n",
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||
"video 1/1 (59/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.6ms\n",
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||
"video 1/1 (60/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.6ms\n",
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||
"video 1/1 (61/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.7ms\n",
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||
"video 1/1 (62/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.8ms\n",
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||
"video 1/1 (63/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.7ms\n",
|
||
"video 1/1 (64/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.7ms\n",
|
||
"video 1/1 (65/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.7ms\n",
|
||
"video 1/1 (66/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.6ms\n",
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||
"video 1/1 (67/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.8ms\n",
|
||
"video 1/1 (68/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.6ms\n",
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||
"video 1/1 (69/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.7ms\n",
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||
"video 1/1 (70/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.7ms\n",
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||
"video 1/1 (71/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.7ms\n",
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||
"video 1/1 (72/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.9ms\n",
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||
"video 1/1 (73/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.7ms\n",
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||
"video 1/1 (74/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.8ms\n",
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||
"video 1/1 (75/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.7ms\n",
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||
"video 1/1 (76/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.9ms\n",
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||
"video 1/1 (77/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.6ms\n",
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||
"video 1/1 (78/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.6ms\n",
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"video 1/1 (79/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.6ms\n",
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"video 1/1 (80/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.6ms\n",
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"video 1/1 (81/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.7ms\n",
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||
"video 1/1 (82/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.6ms\n",
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"video 1/1 (83/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.6ms\n",
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"video 1/1 (84/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.6ms\n",
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||
"video 1/1 (85/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.6ms\n",
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"video 1/1 (86/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.6ms\n",
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"video 1/1 (87/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.5ms\n",
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"video 1/1 (88/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.5ms\n",
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"video 1/1 (89/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.5ms\n",
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"video 1/1 (90/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.5ms\n",
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"video 1/1 (91/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.6ms\n",
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"video 1/1 (92/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.7ms\n",
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"video 1/1 (93/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.6ms\n",
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"video 1/1 (94/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.6ms\n",
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"video 1/1 (97/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.5ms\n",
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"video 1/1 (109/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.7ms\n",
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"video 1/1 (115/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.7ms\n",
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"video 1/1 (116/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.7ms\n",
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"video 1/1 (117/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.5ms\n",
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"video 1/1 (118/118) /home/ieemoo0337/projects/datasets/FP/9421029080278/9421029080278_20241018-115216_back_returnGood_5478c9a48b7e_10_15027299265.mp4: 640x512 5.6ms\n",
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"/home/ieemoo0337/projects/detecttracking/tracking/traclus.py:163: RuntimeWarning: divide by zero encountered in scalar divide\n",
|
||
" tan_theta0 = (shorter_slope - longer_slope) / (1 + shorter_slope * longer_slope)\n",
|
||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
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||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
|
||
]
|
||
},
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||
{
|
||
"name": "stdout",
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||
"output_type": "stream",
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||
"text": [
|
||
"{'item1': {'Text': 'New Zealand Farm Fresh Milk Powder', 'Color': '黑白', 'Shape': '长方形', 'Material': '纸质', 'Category': '乳制品'}, 'item2': {'Text': '新西兰农场新鲜奶粉', 'Color': '黑白', 'Shape': '长方形', 'Material': '纸质', 'Category': '乳制品'}, 'is_Same': True}\n",
|
||
"barcode: 8999178654332\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/8999178654332/8999178654332_20241017-144634_back_addGood_5478c9a4db2c_10_18133699824.mp4\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/8999178654332/8852756303353.jpg\n"
|
||
]
|
||
},
|
||
{
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||
"name": "stderr",
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"output_type": "stream",
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||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
"video 1/1 (1/56) /home/ieemoo0337/projects/datasets/FP/8999178654332/8999178654332_20241017-144634_back_addGood_5478c9a4db2c_10_18133699824.mp4: 640x512 (no detections), 6.6ms\n",
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]
|
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},
|
||
{
|
||
"name": "stdout",
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||
"output_type": "stream",
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||
"text": [
|
||
"load model resnet18 \n"
|
||
]
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||
},
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||
{
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||
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"video 1/1 (48/56) /home/ieemoo0337/projects/datasets/FP/8999178654332/8999178654332_20241017-144634_back_addGood_5478c9a4db2c_10_18133699824.mp4: 640x512 5.5ms\n",
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"video 1/1 (49/56) /home/ieemoo0337/projects/datasets/FP/8999178654332/8999178654332_20241017-144634_back_addGood_5478c9a4db2c_10_18133699824.mp4: 640x512 5.5ms\n",
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"video 1/1 (50/56) /home/ieemoo0337/projects/datasets/FP/8999178654332/8999178654332_20241017-144634_back_addGood_5478c9a4db2c_10_18133699824.mp4: 640x512 5.6ms\n",
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"video 1/1 (51/56) /home/ieemoo0337/projects/datasets/FP/8999178654332/8999178654332_20241017-144634_back_addGood_5478c9a4db2c_10_18133699824.mp4: 640x512 5.5ms\n",
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"video 1/1 (52/56) /home/ieemoo0337/projects/datasets/FP/8999178654332/8999178654332_20241017-144634_back_addGood_5478c9a4db2c_10_18133699824.mp4: 640x512 5.5ms\n",
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"video 1/1 (53/56) /home/ieemoo0337/projects/datasets/FP/8999178654332/8999178654332_20241017-144634_back_addGood_5478c9a4db2c_10_18133699824.mp4: 640x512 5.5ms\n",
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"video 1/1 (54/56) /home/ieemoo0337/projects/datasets/FP/8999178654332/8999178654332_20241017-144634_back_addGood_5478c9a4db2c_10_18133699824.mp4: 640x512 5.5ms\n",
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"video 1/1 (55/56) /home/ieemoo0337/projects/datasets/FP/8999178654332/8999178654332_20241017-144634_back_addGood_5478c9a4db2c_10_18133699824.mp4: 640x512 5.5ms\n",
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"video 1/1 (56/56) /home/ieemoo0337/projects/datasets/FP/8999178654332/8999178654332_20241017-144634_back_addGood_5478c9a4db2c_10_18133699824.mp4: 640x512 5.5ms\n",
|
||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
|
||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"{'item1': {'Text': \"Kellogg's\", 'Color': '红色', 'Shape': '圆形', 'Material': '谷物', 'Category': '早餐谷物'}, 'item2': {'Text': 'Tortilla Chips', 'Color': '灰色', 'Shape': '三角形', 'Material': '玉米', 'Category': '零食'}, 'is_Same': False}\n",
|
||
"barcode: 8996001356326\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/8996001356326/8996001356326_20241015-170913_back_returnGood_5478c9a48b7e_240_13799009402.mp4\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/8996001356326/9415262030039.jpg\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
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||
"text": [
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n",
|
||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
"video 1/1 (1/63) /home/ieemoo0337/projects/datasets/FP/8996001356326/8996001356326_20241015-170913_back_returnGood_5478c9a48b7e_240_13799009402.mp4: 640x512 7.3ms\n",
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"video 1/1 (2/63) /home/ieemoo0337/projects/datasets/FP/8996001356326/8996001356326_20241015-170913_back_returnGood_5478c9a48b7e_240_13799009402.mp4: 640x512 5.4ms\n",
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"video 1/1 (5/63) /home/ieemoo0337/projects/datasets/FP/8996001356326/8996001356326_20241015-170913_back_returnGood_5478c9a48b7e_240_13799009402.mp4: 640x512 5.6ms\n",
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|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"load model resnet18 \n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
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"output_type": "stream",
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"video 1/1 (62/63) /home/ieemoo0337/projects/datasets/FP/8996001356326/8996001356326_20241015-170913_back_returnGood_5478c9a48b7e_240_13799009402.mp4: 640x512 5.6ms\n",
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||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
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||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"{'item1': {'Text': '实力解决肌肤问题\\n全新海盐净油系列\\n\\n净油除螨\\n滋润柔肤\\n水润亮泽\\n持久留香', 'Color': '蓝色', 'Shape': '长方形', 'Material': '塑料', 'Category': '洗护用品'}, 'item2': {'Text': '未知', 'Color': '红色', 'Shape': '圆柱形', 'Material': '金属', 'Category': '饮料'}, 'is_Same': False}\n",
|
||
"barcode: 9335390002121\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/9335390002121/9335390002121_20241014-161252_back_addGood_5478c9a49bfc_3015_18133699824.mp4\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/9335390002121/9415007301585.jpg\n"
|
||
]
|
||
},
|
||
{
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||
"name": "stderr",
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"output_type": "stream",
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"text": [
|
||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
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|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
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||
"text": [
|
||
"load model resnet18 \n"
|
||
]
|
||
},
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||
{
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"name": "stderr",
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||
"video 1/1 (170/174) /home/ieemoo0337/projects/datasets/FP/9335390002121/9335390002121_20241014-161252_back_addGood_5478c9a49bfc_3015_18133699824.mp4: 640x512 5.4ms\n",
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"video 1/1 (171/174) /home/ieemoo0337/projects/datasets/FP/9335390002121/9335390002121_20241014-161252_back_addGood_5478c9a49bfc_3015_18133699824.mp4: 640x512 5.4ms\n",
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||
"video 1/1 (172/174) /home/ieemoo0337/projects/datasets/FP/9335390002121/9335390002121_20241014-161252_back_addGood_5478c9a49bfc_3015_18133699824.mp4: 640x512 5.4ms\n",
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||
"video 1/1 (173/174) /home/ieemoo0337/projects/datasets/FP/9335390002121/9335390002121_20241014-161252_back_addGood_5478c9a49bfc_3015_18133699824.mp4: 640x512 5.4ms\n",
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||
"video 1/1 (174/174) /home/ieemoo0337/projects/datasets/FP/9335390002121/9335390002121_20241014-161252_back_addGood_5478c9a49bfc_3015_18133699824.mp4: 640x512 5.4ms\n",
|
||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
|
||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"{'item1': {'Text': '安佳黄油', 'Color': '白色', 'Shape': '长方形', 'Material': '纸', 'Category': '黄油'}, 'item2': {'Text': 'a2', 'Color': '蓝色', 'Shape': '长方形', 'Material': '纸', 'Category': '牛奶'}, 'is_Same': False}\n",
|
||
"barcode: 9345521001817\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/9345521001817/8859442800745.jpg\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/9345521001817/9345521001817_20241018-152216_back_returnGood_5478c9a48c28_300_13773168720.mp4\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
"video 1/1 (1/49) /home/ieemoo0337/projects/datasets/FP/9345521001817/9345521001817_20241018-152216_back_returnGood_5478c9a48c28_300_13773168720.mp4: 640x512 6.0ms\n",
|
||
"video 1/1 (2/49) /home/ieemoo0337/projects/datasets/FP/9345521001817/9345521001817_20241018-152216_back_returnGood_5478c9a48c28_300_13773168720.mp4: 640x512 5.5ms\n",
|
||
"video 1/1 (3/49) /home/ieemoo0337/projects/datasets/FP/9345521001817/9345521001817_20241018-152216_back_returnGood_5478c9a48c28_300_13773168720.mp4: 640x512 5.6ms\n",
|
||
"video 1/1 (4/49) /home/ieemoo0337/projects/datasets/FP/9345521001817/9345521001817_20241018-152216_back_returnGood_5478c9a48c28_300_13773168720.mp4: 640x512 5.4ms\n",
|
||
"video 1/1 (5/49) /home/ieemoo0337/projects/datasets/FP/9345521001817/9345521001817_20241018-152216_back_returnGood_5478c9a48c28_300_13773168720.mp4: 640x512 5.5ms\n",
|
||
"video 1/1 (6/49) /home/ieemoo0337/projects/datasets/FP/9345521001817/9345521001817_20241018-152216_back_returnGood_5478c9a48c28_300_13773168720.mp4: 640x512 5.5ms\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"load model resnet18 \n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
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||
"video 1/1 (8/49) /home/ieemoo0337/projects/datasets/FP/9345521001817/9345521001817_20241018-152216_back_returnGood_5478c9a48c28_300_13773168720.mp4: 640x512 5.5ms\n",
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|
||
"video 1/1 (11/49) /home/ieemoo0337/projects/datasets/FP/9345521001817/9345521001817_20241018-152216_back_returnGood_5478c9a48c28_300_13773168720.mp4: 640x512 5.4ms\n",
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"video 1/1 (17/49) /home/ieemoo0337/projects/datasets/FP/9345521001817/9345521001817_20241018-152216_back_returnGood_5478c9a48c28_300_13773168720.mp4: 640x512 5.5ms\n",
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"video 1/1 (22/49) /home/ieemoo0337/projects/datasets/FP/9345521001817/9345521001817_20241018-152216_back_returnGood_5478c9a48c28_300_13773168720.mp4: 640x512 5.5ms\n",
|
||
"video 1/1 (23/49) /home/ieemoo0337/projects/datasets/FP/9345521001817/9345521001817_20241018-152216_back_returnGood_5478c9a48c28_300_13773168720.mp4: 640x512 5.4ms\n",
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||
"video 1/1 (24/49) /home/ieemoo0337/projects/datasets/FP/9345521001817/9345521001817_20241018-152216_back_returnGood_5478c9a48c28_300_13773168720.mp4: 640x512 5.4ms\n",
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||
"video 1/1 (25/49) /home/ieemoo0337/projects/datasets/FP/9345521001817/9345521001817_20241018-152216_back_returnGood_5478c9a48c28_300_13773168720.mp4: 640x512 5.4ms\n",
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||
"video 1/1 (26/49) /home/ieemoo0337/projects/datasets/FP/9345521001817/9345521001817_20241018-152216_back_returnGood_5478c9a48c28_300_13773168720.mp4: 640x512 5.5ms\n",
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||
"video 1/1 (27/49) /home/ieemoo0337/projects/datasets/FP/9345521001817/9345521001817_20241018-152216_back_returnGood_5478c9a48c28_300_13773168720.mp4: 640x512 5.5ms\n",
|
||
"video 1/1 (28/49) /home/ieemoo0337/projects/datasets/FP/9345521001817/9345521001817_20241018-152216_back_returnGood_5478c9a48c28_300_13773168720.mp4: 640x512 5.4ms\n",
|
||
"video 1/1 (29/49) /home/ieemoo0337/projects/datasets/FP/9345521001817/9345521001817_20241018-152216_back_returnGood_5478c9a48c28_300_13773168720.mp4: 640x512 5.4ms\n",
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||
"video 1/1 (30/49) /home/ieemoo0337/projects/datasets/FP/9345521001817/9345521001817_20241018-152216_back_returnGood_5478c9a48c28_300_13773168720.mp4: 640x512 5.4ms\n",
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||
"video 1/1 (31/49) /home/ieemoo0337/projects/datasets/FP/9345521001817/9345521001817_20241018-152216_back_returnGood_5478c9a48c28_300_13773168720.mp4: 640x512 5.4ms\n",
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||
"video 1/1 (32/49) /home/ieemoo0337/projects/datasets/FP/9345521001817/9345521001817_20241018-152216_back_returnGood_5478c9a48c28_300_13773168720.mp4: 640x512 5.4ms\n",
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"video 1/1 (33/49) /home/ieemoo0337/projects/datasets/FP/9345521001817/9345521001817_20241018-152216_back_returnGood_5478c9a48c28_300_13773168720.mp4: 640x512 5.5ms\n",
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"video 1/1 (34/49) /home/ieemoo0337/projects/datasets/FP/9345521001817/9345521001817_20241018-152216_back_returnGood_5478c9a48c28_300_13773168720.mp4: 640x512 5.4ms\n",
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||
"video 1/1 (35/49) /home/ieemoo0337/projects/datasets/FP/9345521001817/9345521001817_20241018-152216_back_returnGood_5478c9a48c28_300_13773168720.mp4: 640x512 5.4ms\n",
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"video 1/1 (36/49) /home/ieemoo0337/projects/datasets/FP/9345521001817/9345521001817_20241018-152216_back_returnGood_5478c9a48c28_300_13773168720.mp4: 640x512 5.4ms\n",
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||
"video 1/1 (37/49) /home/ieemoo0337/projects/datasets/FP/9345521001817/9345521001817_20241018-152216_back_returnGood_5478c9a48c28_300_13773168720.mp4: 640x512 5.4ms\n",
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||
"video 1/1 (38/49) /home/ieemoo0337/projects/datasets/FP/9345521001817/9345521001817_20241018-152216_back_returnGood_5478c9a48c28_300_13773168720.mp4: 640x512 5.4ms\n",
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"video 1/1 (39/49) /home/ieemoo0337/projects/datasets/FP/9345521001817/9345521001817_20241018-152216_back_returnGood_5478c9a48c28_300_13773168720.mp4: 640x512 5.4ms\n",
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||
"video 1/1 (40/49) /home/ieemoo0337/projects/datasets/FP/9345521001817/9345521001817_20241018-152216_back_returnGood_5478c9a48c28_300_13773168720.mp4: 640x512 5.4ms\n",
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||
"video 1/1 (41/49) /home/ieemoo0337/projects/datasets/FP/9345521001817/9345521001817_20241018-152216_back_returnGood_5478c9a48c28_300_13773168720.mp4: 640x512 5.4ms\n",
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"video 1/1 (42/49) /home/ieemoo0337/projects/datasets/FP/9345521001817/9345521001817_20241018-152216_back_returnGood_5478c9a48c28_300_13773168720.mp4: 640x512 5.5ms\n",
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||
"video 1/1 (43/49) /home/ieemoo0337/projects/datasets/FP/9345521001817/9345521001817_20241018-152216_back_returnGood_5478c9a48c28_300_13773168720.mp4: 640x512 5.6ms\n",
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||
"video 1/1 (44/49) /home/ieemoo0337/projects/datasets/FP/9345521001817/9345521001817_20241018-152216_back_returnGood_5478c9a48c28_300_13773168720.mp4: 640x512 5.4ms\n",
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||
"video 1/1 (45/49) /home/ieemoo0337/projects/datasets/FP/9345521001817/9345521001817_20241018-152216_back_returnGood_5478c9a48c28_300_13773168720.mp4: 640x512 5.5ms\n",
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||
"video 1/1 (46/49) /home/ieemoo0337/projects/datasets/FP/9345521001817/9345521001817_20241018-152216_back_returnGood_5478c9a48c28_300_13773168720.mp4: 640x512 5.4ms\n",
|
||
"video 1/1 (47/49) /home/ieemoo0337/projects/datasets/FP/9345521001817/9345521001817_20241018-152216_back_returnGood_5478c9a48c28_300_13773168720.mp4: 640x512 5.4ms\n",
|
||
"video 1/1 (48/49) /home/ieemoo0337/projects/datasets/FP/9345521001817/9345521001817_20241018-152216_back_returnGood_5478c9a48c28_300_13773168720.mp4: 640x512 5.4ms\n",
|
||
"video 1/1 (49/49) /home/ieemoo0337/projects/datasets/FP/9345521001817/9345521001817_20241018-152216_back_returnGood_5478c9a48c28_300_13773168720.mp4: 640x512 5.5ms\n",
|
||
"/home/ieemoo0337/projects/detecttracking/tracking/traclus.py:163: RuntimeWarning: divide by zero encountered in scalar divide\n",
|
||
" tan_theta0 = (shorter_slope - longer_slope) / (1 + shorter_slope * longer_slope)\n",
|
||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
|
||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"{'item1': {'Text': 'Coconut Crispy Rolls', 'Color': '蓝色', 'Shape': '卷', 'Material': '椰子', 'Category': '零食'}, 'item2': {'Text': '未知', 'Color': '未知', 'Shape': '未知', 'Material': '未知', 'Category': '未知'}, 'is_Same': False}\n",
|
||
"barcode: 9315090201109\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/9315090201109/9315090201109_20241018-151845_back_returnGood_5478c9a49bfc_3445_13867273486.mp4\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/9315090201109/9421029085211.jpg\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
"video 1/1 (1/131) /home/ieemoo0337/projects/datasets/FP/9315090201109/9315090201109_20241018-151845_back_returnGood_5478c9a49bfc_3445_13867273486.mp4: 640x512 5.9ms\n",
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||
"video 1/1 (2/131) /home/ieemoo0337/projects/datasets/FP/9315090201109/9315090201109_20241018-151845_back_returnGood_5478c9a49bfc_3445_13867273486.mp4: 640x512 5.4ms\n",
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||
"video 1/1 (3/131) /home/ieemoo0337/projects/datasets/FP/9315090201109/9315090201109_20241018-151845_back_returnGood_5478c9a49bfc_3445_13867273486.mp4: 640x512 5.4ms\n",
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||
"video 1/1 (4/131) /home/ieemoo0337/projects/datasets/FP/9315090201109/9315090201109_20241018-151845_back_returnGood_5478c9a49bfc_3445_13867273486.mp4: 640x512 5.7ms\n",
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||
"video 1/1 (5/131) /home/ieemoo0337/projects/datasets/FP/9315090201109/9315090201109_20241018-151845_back_returnGood_5478c9a49bfc_3445_13867273486.mp4: 640x512 5.5ms\n",
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"video 1/1 (6/131) /home/ieemoo0337/projects/datasets/FP/9315090201109/9315090201109_20241018-151845_back_returnGood_5478c9a49bfc_3445_13867273486.mp4: 640x512 5.4ms\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"load model resnet18 \n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
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"video 1/1 (127/131) /home/ieemoo0337/projects/datasets/FP/9315090201109/9315090201109_20241018-151845_back_returnGood_5478c9a49bfc_3445_13867273486.mp4: 640x512 5.4ms\n",
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"video 1/1 (129/131) /home/ieemoo0337/projects/datasets/FP/9315090201109/9315090201109_20241018-151845_back_returnGood_5478c9a49bfc_3445_13867273486.mp4: 640x512 5.4ms\n",
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||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
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||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
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"output_type": "stream",
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"text": [
|
||
"{}\n",
|
||
"barcode: 8850718803347\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/8850718803347/8850718803347_20241018-112432_back_returnGood_5478c9a53be2_135_18358205530.mp4\n",
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||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/8850718803347/9315090201758.jpg\n"
|
||
]
|
||
},
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||
{
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"name": "stderr",
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"output_type": "stream",
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||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
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|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"load model resnet18 \n"
|
||
]
|
||
},
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||
{
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||
"name": "stderr",
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"video 1/1 (58/62) /home/ieemoo0337/projects/datasets/FP/8850718803347/8850718803347_20241018-112432_back_returnGood_5478c9a53be2_135_18358205530.mp4: 640x512 5.4ms\n",
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"video 1/1 (59/62) /home/ieemoo0337/projects/datasets/FP/8850718803347/8850718803347_20241018-112432_back_returnGood_5478c9a53be2_135_18358205530.mp4: 640x512 5.4ms\n",
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"video 1/1 (60/62) /home/ieemoo0337/projects/datasets/FP/8850718803347/8850718803347_20241018-112432_back_returnGood_5478c9a53be2_135_18358205530.mp4: 640x512 5.4ms\n",
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"video 1/1 (61/62) /home/ieemoo0337/projects/datasets/FP/8850718803347/8850718803347_20241018-112432_back_returnGood_5478c9a53be2_135_18358205530.mp4: 640x512 5.4ms\n",
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"video 1/1 (62/62) /home/ieemoo0337/projects/datasets/FP/8850718803347/8850718803347_20241018-112432_back_returnGood_5478c9a53be2_135_18358205530.mp4: 640x512 5.5ms\n",
|
||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
|
||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"{'item1': {'Text': \"Australia's Own Kid's Milk FOR GROWING BODIES Made in Australia\", 'Color': '白色', 'Shape': '长方形', 'Material': '纸', 'Category': '牛奶'}, 'item2': {'Text': 'STAX', 'Color': '白色', 'Shape': '圆柱形', 'Material': '塑料', 'Category': '食品'}, 'is_Same': False}\n",
|
||
"barcode: 9421902960819\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/9421902960819/9421902960819_20241018-112049_back_addGood_5478c9a4eb2c_1085_18058629568.mp4\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/9421902960819/8886001012301.jpg\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
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|
||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
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||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
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||
"text": [
|
||
"load model resnet18 \n"
|
||
]
|
||
},
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||
{
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||
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"/home/ieemoo0337/projects/detecttracking/tracking/traclus.py:163: RuntimeWarning: divide by zero encountered in scalar divide\n",
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||
" tan_theta0 = (shorter_slope - longer_slope) / (1 + shorter_slope * longer_slope)\n",
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||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
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||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n"
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||
]
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||
},
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||
{
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||
"name": "stdout",
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||
"output_type": "stream",
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||
"text": [
|
||
"{'item1': {'Text': 'Danisa TRADITIONAL BUTTER COOKIES', 'Color': '蓝色', 'Shape': '长方形', 'Material': '纸', 'Category': '饼干'}, 'item2': {'Text': 'AStick', 'Color': '紫色', 'Shape': '圆形', 'Material': '塑料', 'Category': '饮料'}, 'is_Same': False}\n",
|
||
"barcode: 9421016150199\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/9421016150199/9421016150199_20241018-162918_back_returnGood_5478c9a48c3e_265_14785332147.mp4\n",
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||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/9421016150199/8850813311020.jpg\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
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||
"text": [
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n",
|
||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
"video 1/1 (1/49) /home/ieemoo0337/projects/datasets/FP/9421016150199/9421016150199_20241018-162918_back_returnGood_5478c9a48c3e_265_14785332147.mp4: 640x512 6.4ms\n",
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||
"video 1/1 (2/49) /home/ieemoo0337/projects/datasets/FP/9421016150199/9421016150199_20241018-162918_back_returnGood_5478c9a48c3e_265_14785332147.mp4: 640x512 5.4ms\n",
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"video 1/1 (3/49) /home/ieemoo0337/projects/datasets/FP/9421016150199/9421016150199_20241018-162918_back_returnGood_5478c9a48c3e_265_14785332147.mp4: 640x512 5.3ms\n",
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||
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{
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||
"name": "stdout",
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||
"output_type": "stream",
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"load model resnet18 \n"
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|
||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
|
||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
|
||
]
|
||
},
|
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{
|
||
"name": "stdout",
|
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"text": [
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"{'item1': {'Text': 'Roasted Coconut Chips', 'Color': '橙色', 'Shape': '片状', 'Material': '椰子', 'Category': '零食'}, 'item2': {'Text': '未知', 'Color': '未知', 'Shape': '未知', 'Material': '未知', 'Category': '未知'}, 'is_Same': False}\n",
|
||
"barcode: 8855044006707\n",
|
||
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|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/8855044006707/9346506009118.jpg\n"
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||
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"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
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|
||
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|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"load model resnet18 \n"
|
||
]
|
||
},
|
||
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||
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"video 1/1 (34/51) /home/ieemoo0337/projects/datasets/FP/8855044006707/8855044006707_20241017-155821_back_returnGood_5478c9a48b7e_530_13799009402.mp4: 640x512 5.6ms\n",
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"video 1/1 (35/51) /home/ieemoo0337/projects/datasets/FP/8855044006707/8855044006707_20241017-155821_back_returnGood_5478c9a48b7e_530_13799009402.mp4: 640x512 5.6ms\n",
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"video 1/1 (37/51) /home/ieemoo0337/projects/datasets/FP/8855044006707/8855044006707_20241017-155821_back_returnGood_5478c9a48b7e_530_13799009402.mp4: 640x512 5.6ms\n",
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"video 1/1 (44/51) /home/ieemoo0337/projects/datasets/FP/8855044006707/8855044006707_20241017-155821_back_returnGood_5478c9a48b7e_530_13799009402.mp4: 640x512 5.7ms\n",
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"video 1/1 (45/51) /home/ieemoo0337/projects/datasets/FP/8855044006707/8855044006707_20241017-155821_back_returnGood_5478c9a48b7e_530_13799009402.mp4: 640x512 5.5ms\n",
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"video 1/1 (47/51) /home/ieemoo0337/projects/datasets/FP/8855044006707/8855044006707_20241017-155821_back_returnGood_5478c9a48b7e_530_13799009402.mp4: 640x512 5.5ms\n",
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"video 1/1 (48/51) /home/ieemoo0337/projects/datasets/FP/8855044006707/8855044006707_20241017-155821_back_returnGood_5478c9a48b7e_530_13799009402.mp4: 640x512 5.4ms\n",
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"video 1/1 (49/51) /home/ieemoo0337/projects/datasets/FP/8855044006707/8855044006707_20241017-155821_back_returnGood_5478c9a48b7e_530_13799009402.mp4: 640x512 5.4ms\n",
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"video 1/1 (50/51) /home/ieemoo0337/projects/datasets/FP/8855044006707/8855044006707_20241017-155821_back_returnGood_5478c9a48b7e_530_13799009402.mp4: 640x512 5.5ms\n",
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"video 1/1 (51/51) /home/ieemoo0337/projects/datasets/FP/8855044006707/8855044006707_20241017-155821_back_returnGood_5478c9a48b7e_530_13799009402.mp4: 640x512 5.4ms\n",
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||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
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||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"{'item1': {'Text': 'Brain& Bone Formula', 'Color': '紫色', 'Shape': '圆柱形', 'Material': '金属', 'Category': '营养品'}, 'item2': {'Text': '未知', 'Color': '未知', 'Shape': '未知', 'Material': '未知', 'Category': '未知'}, 'is_Same': False}\n",
|
||
"barcode: 9556041614047\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/9556041614047/9344949000136.jpg\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/9556041614047/9556041614047_20241015-172957_back_returnGood_5478c9a49bfc_210_18358205530.mp4\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
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||
"text": [
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n",
|
||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
"video 1/1 (1/124) /home/ieemoo0337/projects/datasets/FP/9556041614047/9556041614047_20241015-172957_back_returnGood_5478c9a49bfc_210_18358205530.mp4: 640x512 6.2ms\n",
|
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"video 1/1 (2/124) /home/ieemoo0337/projects/datasets/FP/9556041614047/9556041614047_20241015-172957_back_returnGood_5478c9a49bfc_210_18358205530.mp4: 640x512 5.4ms\n",
|
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|
||
"video 1/1 (4/124) /home/ieemoo0337/projects/datasets/FP/9556041614047/9556041614047_20241015-172957_back_returnGood_5478c9a49bfc_210_18358205530.mp4: 640x512 5.4ms\n",
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"video 1/1 (6/124) /home/ieemoo0337/projects/datasets/FP/9556041614047/9556041614047_20241015-172957_back_returnGood_5478c9a49bfc_210_18358205530.mp4: 640x512 5.5ms\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"load model resnet18 \n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
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"output_type": "stream",
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"/home/ieemoo0337/projects/detecttracking/tracking/traclus.py:163: RuntimeWarning: divide by zero encountered in scalar divide\n",
|
||
" tan_theta0 = (shorter_slope - longer_slope) / (1 + shorter_slope * longer_slope)\n",
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||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
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||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
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||
]
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
|
||
"{'item1': {'Text': 'Maxigenes Full Cream Instant Milk Powder', 'Color': '白色', 'Shape': '圆柱形', 'Material': '塑料', 'Category': '乳制品'}, 'item2': {'Text': 'AYAM BRAND', 'Color': '绿色', 'Shape': '圆形', 'Material': '陶瓷', 'Category': '调味品'}, 'is_Same': False}\n",
|
||
"barcode: 9350013003057\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/9350013003057/8859015703756.jpg\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/9350013003057/9350013003057_20241018-172730_back_returnGood_5478c9a53bd4_845_15027299265.mp4\n"
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||
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||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
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||
]
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||
},
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||
{
|
||
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||
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||
"text": [
|
||
"load model resnet18 \n"
|
||
]
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||
},
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||
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||
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"video 1/1 (12/92) /home/ieemoo0337/projects/datasets/FP/9350013003057/9350013003057_20241018-172730_back_returnGood_5478c9a53bd4_845_15027299265.mp4: 640x512 5.5ms\n",
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"video 1/1 (13/92) /home/ieemoo0337/projects/datasets/FP/9350013003057/9350013003057_20241018-172730_back_returnGood_5478c9a53bd4_845_15027299265.mp4: 640x512 5.6ms\n",
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"video 1/1 (59/92) /home/ieemoo0337/projects/datasets/FP/9350013003057/9350013003057_20241018-172730_back_returnGood_5478c9a53bd4_845_15027299265.mp4: 640x512 5.5ms\n",
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"video 1/1 (61/92) /home/ieemoo0337/projects/datasets/FP/9350013003057/9350013003057_20241018-172730_back_returnGood_5478c9a53bd4_845_15027299265.mp4: 640x512 5.4ms\n",
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"video 1/1 (62/92) /home/ieemoo0337/projects/datasets/FP/9350013003057/9350013003057_20241018-172730_back_returnGood_5478c9a53bd4_845_15027299265.mp4: 640x512 5.6ms\n",
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"video 1/1 (65/92) /home/ieemoo0337/projects/datasets/FP/9350013003057/9350013003057_20241018-172730_back_returnGood_5478c9a53bd4_845_15027299265.mp4: 640x512 5.4ms\n",
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"video 1/1 (67/92) /home/ieemoo0337/projects/datasets/FP/9350013003057/9350013003057_20241018-172730_back_returnGood_5478c9a53bd4_845_15027299265.mp4: 640x512 5.4ms\n",
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"video 1/1 (70/92) /home/ieemoo0337/projects/datasets/FP/9350013003057/9350013003057_20241018-172730_back_returnGood_5478c9a53bd4_845_15027299265.mp4: 640x512 5.4ms\n",
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"video 1/1 (71/92) /home/ieemoo0337/projects/datasets/FP/9350013003057/9350013003057_20241018-172730_back_returnGood_5478c9a53bd4_845_15027299265.mp4: 640x512 5.4ms\n",
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"video 1/1 (72/92) /home/ieemoo0337/projects/datasets/FP/9350013003057/9350013003057_20241018-172730_back_returnGood_5478c9a53bd4_845_15027299265.mp4: 640x512 5.5ms\n",
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"video 1/1 (73/92) /home/ieemoo0337/projects/datasets/FP/9350013003057/9350013003057_20241018-172730_back_returnGood_5478c9a53bd4_845_15027299265.mp4: 640x512 5.5ms\n",
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"video 1/1 (74/92) /home/ieemoo0337/projects/datasets/FP/9350013003057/9350013003057_20241018-172730_back_returnGood_5478c9a53bd4_845_15027299265.mp4: 640x512 5.4ms\n",
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"video 1/1 (75/92) /home/ieemoo0337/projects/datasets/FP/9350013003057/9350013003057_20241018-172730_back_returnGood_5478c9a53bd4_845_15027299265.mp4: 640x512 5.4ms\n",
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"video 1/1 (76/92) /home/ieemoo0337/projects/datasets/FP/9350013003057/9350013003057_20241018-172730_back_returnGood_5478c9a53bd4_845_15027299265.mp4: 640x512 5.5ms\n",
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"video 1/1 (77/92) /home/ieemoo0337/projects/datasets/FP/9350013003057/9350013003057_20241018-172730_back_returnGood_5478c9a53bd4_845_15027299265.mp4: 640x512 5.5ms\n",
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"video 1/1 (78/92) /home/ieemoo0337/projects/datasets/FP/9350013003057/9350013003057_20241018-172730_back_returnGood_5478c9a53bd4_845_15027299265.mp4: 640x512 5.5ms\n",
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"video 1/1 (79/92) /home/ieemoo0337/projects/datasets/FP/9350013003057/9350013003057_20241018-172730_back_returnGood_5478c9a53bd4_845_15027299265.mp4: 640x512 5.4ms\n",
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"video 1/1 (80/92) /home/ieemoo0337/projects/datasets/FP/9350013003057/9350013003057_20241018-172730_back_returnGood_5478c9a53bd4_845_15027299265.mp4: 640x512 5.4ms\n",
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"video 1/1 (81/92) /home/ieemoo0337/projects/datasets/FP/9350013003057/9350013003057_20241018-172730_back_returnGood_5478c9a53bd4_845_15027299265.mp4: 640x512 5.4ms\n",
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"video 1/1 (82/92) /home/ieemoo0337/projects/datasets/FP/9350013003057/9350013003057_20241018-172730_back_returnGood_5478c9a53bd4_845_15027299265.mp4: 640x512 5.4ms\n",
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"video 1/1 (83/92) /home/ieemoo0337/projects/datasets/FP/9350013003057/9350013003057_20241018-172730_back_returnGood_5478c9a53bd4_845_15027299265.mp4: 640x512 5.4ms\n",
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"video 1/1 (84/92) /home/ieemoo0337/projects/datasets/FP/9350013003057/9350013003057_20241018-172730_back_returnGood_5478c9a53bd4_845_15027299265.mp4: 640x512 5.4ms\n",
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"video 1/1 (85/92) /home/ieemoo0337/projects/datasets/FP/9350013003057/9350013003057_20241018-172730_back_returnGood_5478c9a53bd4_845_15027299265.mp4: 640x512 5.4ms\n",
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"video 1/1 (86/92) /home/ieemoo0337/projects/datasets/FP/9350013003057/9350013003057_20241018-172730_back_returnGood_5478c9a53bd4_845_15027299265.mp4: 640x512 5.4ms\n",
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"video 1/1 (87/92) /home/ieemoo0337/projects/datasets/FP/9350013003057/9350013003057_20241018-172730_back_returnGood_5478c9a53bd4_845_15027299265.mp4: 640x512 5.4ms\n",
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"video 1/1 (88/92) /home/ieemoo0337/projects/datasets/FP/9350013003057/9350013003057_20241018-172730_back_returnGood_5478c9a53bd4_845_15027299265.mp4: 640x512 5.4ms\n",
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"video 1/1 (89/92) /home/ieemoo0337/projects/datasets/FP/9350013003057/9350013003057_20241018-172730_back_returnGood_5478c9a53bd4_845_15027299265.mp4: 640x512 5.4ms\n",
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"video 1/1 (90/92) /home/ieemoo0337/projects/datasets/FP/9350013003057/9350013003057_20241018-172730_back_returnGood_5478c9a53bd4_845_15027299265.mp4: 640x512 5.4ms\n",
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"video 1/1 (91/92) /home/ieemoo0337/projects/datasets/FP/9350013003057/9350013003057_20241018-172730_back_returnGood_5478c9a53bd4_845_15027299265.mp4: 640x512 5.4ms\n",
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"video 1/1 (92/92) /home/ieemoo0337/projects/datasets/FP/9350013003057/9350013003057_20241018-172730_back_returnGood_5478c9a53bd4_845_15027299265.mp4: 640x512 5.4ms\n",
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||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
|
||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"{'item1': {'Text': 'if椰汁咖啡饮料', 'Color': '绿色', 'Shape': '圆形', 'Material': '塑料', 'Category': '饮料'}, 'item2': {'Text': '未知', 'Color': '白色', 'Shape': '圆柱形', 'Material': '纸', 'Category': '纸杯'}, 'is_Same': False}\n",
|
||
"barcode: 9310072013855\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/9310072013855/9310072013855_20241018-154427_back_returnGood_5478c9a53bd4_215_15027299265.mp4\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/9310072013855/9311493003982.jpg\n"
|
||
]
|
||
},
|
||
{
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||
"name": "stderr",
|
||
"output_type": "stream",
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||
"text": [
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n",
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||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
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" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
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"video 1/1 (1/134) /home/ieemoo0337/projects/datasets/FP/9310072013855/9310072013855_20241018-154427_back_returnGood_5478c9a53bd4_215_15027299265.mp4: 640x512 6.4ms\n",
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"video 1/1 (2/134) /home/ieemoo0337/projects/datasets/FP/9310072013855/9310072013855_20241018-154427_back_returnGood_5478c9a53bd4_215_15027299265.mp4: 640x512 5.5ms\n",
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"video 1/1 (3/134) /home/ieemoo0337/projects/datasets/FP/9310072013855/9310072013855_20241018-154427_back_returnGood_5478c9a53bd4_215_15027299265.mp4: 640x512 5.3ms\n",
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"video 1/1 (4/134) /home/ieemoo0337/projects/datasets/FP/9310072013855/9310072013855_20241018-154427_back_returnGood_5478c9a53bd4_215_15027299265.mp4: 640x512 5.4ms\n",
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"video 1/1 (6/134) /home/ieemoo0337/projects/datasets/FP/9310072013855/9310072013855_20241018-154427_back_returnGood_5478c9a53bd4_215_15027299265.mp4: 640x512 5.4ms\n"
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]
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"load model resnet18 \n"
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]
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},
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"/home/ieemoo0337/projects/detecttracking/tracking/traclus.py:163: RuntimeWarning: divide by zero encountered in scalar divide\n",
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||
" tan_theta0 = (shorter_slope - longer_slope) / (1 + shorter_slope * longer_slope)\n",
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||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
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||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n"
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||
]
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||
},
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||
{
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||
"name": "stdout",
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||
"output_type": "stream",
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||
"text": [
|
||
"{'item1': {'Text': 'Bundaberg Pineapple & Coconut Sparkling Drink', 'Color': '黄色', 'Shape': '圆柱形', 'Material': '玻璃', 'Category': '饮料'}, 'item2': {'Text': 'Tim Tam', 'Color': '黑色', 'Shape': '长方形', 'Material': '纸', 'Category': '零食'}, 'is_Same': False}\n",
|
||
"barcode: 9311493002572\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/9311493002572/9421029085075.jpg\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/9311493002572/9311493002572_20241019-155840_back_addGood_5478c9a49bfc_595_13773168720.mp4\n"
|
||
]
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||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
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||
"text": [
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n",
|
||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
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||
]
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||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
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||
"text": [
|
||
"load model resnet18 \n"
|
||
]
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||
},
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||
{
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||
"name": "stderr",
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"video 1/1 (31/52) /home/ieemoo0337/projects/datasets/FP/9311493002572/9311493002572_20241019-155840_back_addGood_5478c9a49bfc_595_13773168720.mp4: 640x512 5.5ms\n",
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"video 1/1 (46/52) /home/ieemoo0337/projects/datasets/FP/9311493002572/9311493002572_20241019-155840_back_addGood_5478c9a49bfc_595_13773168720.mp4: 640x512 5.8ms\n",
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"video 1/1 (48/52) /home/ieemoo0337/projects/datasets/FP/9311493002572/9311493002572_20241019-155840_back_addGood_5478c9a49bfc_595_13773168720.mp4: 640x512 5.6ms\n",
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"video 1/1 (49/52) /home/ieemoo0337/projects/datasets/FP/9311493002572/9311493002572_20241019-155840_back_addGood_5478c9a49bfc_595_13773168720.mp4: 640x512 5.7ms\n",
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"video 1/1 (50/52) /home/ieemoo0337/projects/datasets/FP/9311493002572/9311493002572_20241019-155840_back_addGood_5478c9a49bfc_595_13773168720.mp4: 640x512 5.7ms\n",
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"video 1/1 (51/52) /home/ieemoo0337/projects/datasets/FP/9311493002572/9311493002572_20241019-155840_back_addGood_5478c9a49bfc_595_13773168720.mp4: 640x512 5.6ms\n",
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"video 1/1 (52/52) /home/ieemoo0337/projects/datasets/FP/9311493002572/9311493002572_20241019-155840_back_addGood_5478c9a49bfc_595_13773168720.mp4: 640x512 5.7ms\n",
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"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
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||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
|
||
]
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||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
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||
"text": [
|
||
"{'item1': {'Text': 'Bundaberg GUAVA SPARKLING DRINK', 'Color': '红色', 'Shape': '圆柱形', 'Material': '玻璃', 'Category': '饮料'}, 'item2': {'Text': '未知', 'Color': '未知', 'Shape': '未知', 'Material': '未知', 'Category': '未知'}, 'is_Same': False}\n",
|
||
"barcode: 9346506009118\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/9346506009118/8855044006707.jpg\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/9346506009118/9346506009118_20241015-121012_back_addGood_5478c9a48b7e_1025_13799009402.mp4\n"
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||
]
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||
},
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||
{
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"name": "stderr",
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||
"output_type": "stream",
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|
||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
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},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
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||
"text": [
|
||
"load model resnet18 \n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
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"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
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||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
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||
]
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||
},
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||
{
|
||
"name": "stdout",
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||
"output_type": "stream",
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||
"text": [
|
||
"{'item1': {'Text': 'Coconut Drink with Banana Flavor', 'Color': '透明', 'Shape': '圆柱形', 'Material': '玻璃', 'Category': '饮料'}, 'item2': {'Text': '未知', 'Color': '紫色', 'Shape': '圆柱形', 'Material': '塑料', 'Category': '厨房用具'}, 'is_Same': False}\n",
|
||
"barcode: 8935024156117\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/8935024156117/8935024156117_20241015-135323_back_addGood_5478c9a48b7e_1765_13799009402.mp4\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/8935024156117/9415007042037.jpg\n"
|
||
]
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||
},
|
||
{
|
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||
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|
||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
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||
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|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
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||
"text": [
|
||
"load model resnet18 \n"
|
||
]
|
||
},
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||
{
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||
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"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
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||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
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||
]
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||
},
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||
{
|
||
"name": "stdout",
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||
"output_type": "stream",
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||
"text": [
|
||
"{'item1': {'Text': 'Anchor', 'Color': '白色', 'Shape': '长方形', 'Material': '塑料', 'Category': '食品'}, 'item2': {'Text': 'Anchor', 'Color': '白色', 'Shape': '长方形', 'Material': '塑料', 'Category': '食品'}, 'is_Same': True}\n",
|
||
"barcode: 9346506008777\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/9346506008777/9352266000616.jpg\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/9346506008777/9346506008777_20241016-163436_back_addGood_5478c9a49bfc_1200_18358205530.mp4\n"
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||
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||
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||
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||
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||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
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},
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||
{
|
||
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||
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||
"text": [
|
||
"load model resnet18 \n"
|
||
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||
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||
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||
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"/home/ieemoo0337/projects/detecttracking/tracking/traclus.py:163: RuntimeWarning: divide by zero encountered in scalar divide\n",
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" tan_theta0 = (shorter_slope - longer_slope) / (1 + shorter_slope * longer_slope)\n",
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||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
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||
"\n",
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||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
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||
"Fusing layers... \n",
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||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
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||
]
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},
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"text": [
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||
"{'item1': {'Text': 'Tim Tam Dark', 'Color': '深棕色', 'Shape': '长方形', 'Material': '巧克力', 'Category': '饼干'}, 'item2': {'Text': 'Milk', 'Color': '粉色', 'Shape': '圆形', 'Material': '塑料', 'Category': '牛奶'}, 'is_Same': False}\n",
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||
"barcode: 8859069907438\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/8859069907438/8859015700168.jpg\n",
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||
"video: /home/ieemoo0337/projects/datasets/FP/8859069907438/8859069907438_20241020-135424_back_returnGood_5478c9a49bfc_75_13799009402.mp4\n"
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||
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"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
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||
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||
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"text": [
|
||
"load model resnet18 \n"
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||
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||
},
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"video 1/1 (8/30) /home/ieemoo0337/projects/datasets/FP/8859069907438/8859069907438_20241020-135424_back_returnGood_5478c9a49bfc_75_13799009402.mp4: 640x512 5.6ms\n",
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"video 1/1 (20/30) /home/ieemoo0337/projects/datasets/FP/8859069907438/8859069907438_20241020-135424_back_returnGood_5478c9a49bfc_75_13799009402.mp4: 640x512 5.6ms\n",
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"video 1/1 (22/30) /home/ieemoo0337/projects/datasets/FP/8859069907438/8859069907438_20241020-135424_back_returnGood_5478c9a49bfc_75_13799009402.mp4: 640x512 5.6ms\n",
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"video 1/1 (24/30) /home/ieemoo0337/projects/datasets/FP/8859069907438/8859069907438_20241020-135424_back_returnGood_5478c9a49bfc_75_13799009402.mp4: 640x512 5.6ms\n",
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"video 1/1 (26/30) /home/ieemoo0337/projects/datasets/FP/8859069907438/8859069907438_20241020-135424_back_returnGood_5478c9a49bfc_75_13799009402.mp4: 640x512 5.6ms\n",
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"video 1/1 (27/30) /home/ieemoo0337/projects/datasets/FP/8859069907438/8859069907438_20241020-135424_back_returnGood_5478c9a49bfc_75_13799009402.mp4: 640x512 5.6ms\n",
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"video 1/1 (28/30) /home/ieemoo0337/projects/datasets/FP/8859069907438/8859069907438_20241020-135424_back_returnGood_5478c9a49bfc_75_13799009402.mp4: 640x512 5.7ms\n",
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"video 1/1 (29/30) /home/ieemoo0337/projects/datasets/FP/8859069907438/8859069907438_20241020-135424_back_returnGood_5478c9a49bfc_75_13799009402.mp4: 640x512 5.6ms\n",
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"video 1/1 (30/30) /home/ieemoo0337/projects/datasets/FP/8859069907438/8859069907438_20241020-135424_back_returnGood_5478c9a49bfc_75_13799009402.mp4: 640x512 6.7ms\n",
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"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
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"\n",
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||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
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||
"Fusing layers... \n",
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||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
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]
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"{'item1': {'Text': 'Coconut Water', 'Color': '绿色', 'Shape': '圆柱形', 'Material': '玻璃', 'Category': '饮料'}, 'item2': {'Text': '未知', 'Color': '未知', 'Shape': '未知', 'Material': '未知', 'Category': '未知'}, 'is_Same': False}\n",
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||
"barcode: 9421903892140\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/9421903892140/9318637391714.jpg\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/9421903892140/9421903892140_20241016-162446_back_addGood_5478c9a49bfc_1035_18358205530.mp4\n"
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]
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"name": "stderr",
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"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
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]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
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||
"text": [
|
||
"load model resnet18 \n"
|
||
]
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||
},
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{
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"name": "stderr",
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"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
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||
"\n",
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||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
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||
]
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||
},
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||
{
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||
"name": "stdout",
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||
"output_type": "stream",
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||
"text": [
|
||
"{'item1': {'Text': 'Cetaphil Moisturizing Cream', 'Color': '白色', 'Shape': '圆柱形', 'Material': '塑料', 'Category': '护肤品'}, 'item2': {'Text': '全脂奶粉', 'Color': '蓝色', 'Shape': '长方形', 'Material': '塑料', 'Category': '食品'}, 'is_Same': False}\n",
|
||
"barcode: 8859015700434\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/8859015700434/8859015700434_20241017-102526_back_returnGood_5478c9a48c3e_390_13586533739.mp4\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/8859015700434/8859594300018.jpg\n"
|
||
]
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||
},
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||
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||
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||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
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||
},
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||
{
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||
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||
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"text": [
|
||
"load model resnet18 \n"
|
||
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||
},
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||
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||
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"video 1/1 (21/48) /home/ieemoo0337/projects/datasets/FP/8859015700434/8859015700434_20241017-102526_back_returnGood_5478c9a48c3e_390_13586533739.mp4: 640x512 5.5ms\n",
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"/home/ieemoo0337/projects/detecttracking/tracking/traclus.py:163: RuntimeWarning: divide by zero encountered in scalar divide\n",
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" tan_theta0 = (shorter_slope - longer_slope) / (1 + shorter_slope * longer_slope)\n",
|
||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
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"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
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||
]
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||
},
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||
{
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"name": "stdout",
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"output_type": "stream",
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"text": [
|
||
"{'item1': {'Text': 'Chang Soda Water Lime Flavoured', 'Color': '透明', 'Shape': '圆柱形', 'Material': '玻璃', 'Category': '饮料'}, 'item2': {'Text': 'Chang Soda Water Lime Flavoured', 'Color': '透明', 'Shape': '圆柱形', 'Material': '玻璃', 'Category': '饮料'}, 'is_Same': True}\n",
|
||
"barcode: 9345521003798\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/9345521003798/9311493002503.jpg\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/9345521003798/9345521003798_20241020-153159_back_returnGood_5478c9a48b7e_805_15027299265.mp4\n"
|
||
]
|
||
},
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||
{
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||
"name": "stderr",
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||
"output_type": "stream",
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|
||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
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|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
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||
"text": [
|
||
"load model resnet18 \n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
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||
"/home/ieemoo0337/projects/detecttracking/tracking/traclus.py:163: RuntimeWarning: divide by zero encountered in scalar divide\n",
|
||
" tan_theta0 = (shorter_slope - longer_slope) / (1 + shorter_slope * longer_slope)\n",
|
||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
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||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
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||
]
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||
},
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||
{
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||
"name": "stdout",
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||
"output_type": "stream",
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||
"text": [
|
||
"{'item1': {'Text': 'Bundaberg Pink Grapefruit Sparkling Drink', 'Color': '红色', 'Shape': '圆柱形', 'Material': '玻璃', 'Category': '饮料'}, 'item2': {'Text': '洗衣液', 'Color': '蓝色', 'Shape': '长方形', 'Material': '塑料', 'Category': '清洁用品'}, 'is_Same': False}\n",
|
||
"barcode: 8858731200075\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/8858731200075/8996001353028.jpg\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/8858731200075/8858731200075_20241020-133242_back_addGood_5478c9a49bfc_535_13799009402.mp4\n"
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||
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||
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||
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|
||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
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||
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||
},
|
||
{
|
||
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|
||
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||
"text": [
|
||
"load model resnet18 \n"
|
||
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|
||
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||
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||
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"video 1/1 (55/56) /home/ieemoo0337/projects/datasets/FP/8858731200075/8858731200075_20241020-133242_back_addGood_5478c9a49bfc_535_13799009402.mp4: 640x512 5.3ms\n",
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"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
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"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n"
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||
]
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||
},
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||
{
|
||
"name": "stdout",
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"output_type": "stream",
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||
"text": [
|
||
"{'item1': {'Text': 'Cal Cheese', 'Color': '橙色', 'Shape': '方形', 'Material': '纸盒', 'Category': '零食'}, 'item2': {'Text': 'Unknown', 'Color': '未知', 'Shape': '未知', 'Material': '未知', 'Category': '未知'}, 'is_Same': False}\n",
|
||
"barcode: 8996001303764\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/8996001303764/8996001303764_20241020-105426_back_returnGood_5478c9a53bd4_340_14785332147.mp4\n",
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||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/8996001303764/9315090211498.jpg\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
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||
"text": [
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n",
|
||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
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||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
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||
"text": [
|
||
"load model resnet18 \n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
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"output_type": "stream",
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"video 1/1 (49/74) /home/ieemoo0337/projects/datasets/FP/8996001303764/8996001303764_20241020-105426_back_returnGood_5478c9a53bd4_340_14785332147.mp4: 640x512 5.5ms\n",
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"video 1/1 (50/74) /home/ieemoo0337/projects/datasets/FP/8996001303764/8996001303764_20241020-105426_back_returnGood_5478c9a53bd4_340_14785332147.mp4: 640x512 5.4ms\n",
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"video 1/1 (51/74) /home/ieemoo0337/projects/datasets/FP/8996001303764/8996001303764_20241020-105426_back_returnGood_5478c9a53bd4_340_14785332147.mp4: 640x512 5.4ms\n",
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"video 1/1 (52/74) /home/ieemoo0337/projects/datasets/FP/8996001303764/8996001303764_20241020-105426_back_returnGood_5478c9a53bd4_340_14785332147.mp4: 640x512 5.4ms\n",
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"video 1/1 (53/74) /home/ieemoo0337/projects/datasets/FP/8996001303764/8996001303764_20241020-105426_back_returnGood_5478c9a53bd4_340_14785332147.mp4: 640x512 5.4ms\n",
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"video 1/1 (65/74) /home/ieemoo0337/projects/datasets/FP/8996001303764/8996001303764_20241020-105426_back_returnGood_5478c9a53bd4_340_14785332147.mp4: 640x512 5.4ms\n",
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"video 1/1 (68/74) /home/ieemoo0337/projects/datasets/FP/8996001303764/8996001303764_20241020-105426_back_returnGood_5478c9a53bd4_340_14785332147.mp4: 640x512 5.4ms\n",
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"video 1/1 (70/74) /home/ieemoo0337/projects/datasets/FP/8996001303764/8996001303764_20241020-105426_back_returnGood_5478c9a53bd4_340_14785332147.mp4: 640x512 5.4ms\n",
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"video 1/1 (71/74) /home/ieemoo0337/projects/datasets/FP/8996001303764/8996001303764_20241020-105426_back_returnGood_5478c9a53bd4_340_14785332147.mp4: 640x512 5.4ms\n",
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"video 1/1 (72/74) /home/ieemoo0337/projects/datasets/FP/8996001303764/8996001303764_20241020-105426_back_returnGood_5478c9a53bd4_340_14785332147.mp4: 640x512 5.5ms\n",
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"video 1/1 (73/74) /home/ieemoo0337/projects/datasets/FP/8996001303764/8996001303764_20241020-105426_back_returnGood_5478c9a53bd4_340_14785332147.mp4: 640x512 5.4ms\n",
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"video 1/1 (74/74) /home/ieemoo0337/projects/datasets/FP/8996001303764/8996001303764_20241020-105426_back_returnGood_5478c9a53bd4_340_14785332147.mp4: 640x512 5.5ms\n",
|
||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
|
||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"{'item1': {'Text': 'Pure Milk', 'Color': '蓝色', 'Shape': '长方形', 'Material': '纸', 'Category': '牛奶'}, 'item2': {'Text': 'Danisa', 'Color': '白色', 'Shape': '圆形', 'Material': '金属', 'Category': '黄油'}, 'is_Same': False}\n",
|
||
"barcode: 9421029085211\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/9421029085211/9315090201109.jpg\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/9421029085211/9421029085211_20241019-184830_back_returnGood_5478c9a4db2c_1640_13867273486.mp4\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
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|
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|
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"video 1/1 (5/60) /home/ieemoo0337/projects/datasets/FP/9421029085211/9421029085211_20241019-184830_back_returnGood_5478c9a4db2c_1640_13867273486.mp4: 640x512 5.5ms\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"load model resnet18 \n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
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"output_type": "stream",
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"video 1/1 (49/60) /home/ieemoo0337/projects/datasets/FP/9421029085211/9421029085211_20241019-184830_back_returnGood_5478c9a4db2c_1640_13867273486.mp4: 640x512 5.3ms\n",
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"video 1/1 (50/60) /home/ieemoo0337/projects/datasets/FP/9421029085211/9421029085211_20241019-184830_back_returnGood_5478c9a4db2c_1640_13867273486.mp4: 640x512 5.3ms\n",
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"video 1/1 (52/60) /home/ieemoo0337/projects/datasets/FP/9421029085211/9421029085211_20241019-184830_back_returnGood_5478c9a4db2c_1640_13867273486.mp4: 640x512 5.4ms\n",
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"video 1/1 (53/60) /home/ieemoo0337/projects/datasets/FP/9421029085211/9421029085211_20241019-184830_back_returnGood_5478c9a4db2c_1640_13867273486.mp4: 640x512 5.3ms\n",
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"video 1/1 (54/60) /home/ieemoo0337/projects/datasets/FP/9421029085211/9421029085211_20241019-184830_back_returnGood_5478c9a4db2c_1640_13867273486.mp4: 640x512 5.3ms\n",
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"video 1/1 (55/60) /home/ieemoo0337/projects/datasets/FP/9421029085211/9421029085211_20241019-184830_back_returnGood_5478c9a4db2c_1640_13867273486.mp4: 640x512 5.3ms\n",
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"video 1/1 (56/60) /home/ieemoo0337/projects/datasets/FP/9421029085211/9421029085211_20241019-184830_back_returnGood_5478c9a4db2c_1640_13867273486.mp4: 640x512 5.2ms\n",
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"video 1/1 (57/60) /home/ieemoo0337/projects/datasets/FP/9421029085211/9421029085211_20241019-184830_back_returnGood_5478c9a4db2c_1640_13867273486.mp4: 640x512 5.3ms\n",
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"video 1/1 (58/60) /home/ieemoo0337/projects/datasets/FP/9421029085211/9421029085211_20241019-184830_back_returnGood_5478c9a4db2c_1640_13867273486.mp4: 640x512 5.3ms\n",
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"video 1/1 (59/60) /home/ieemoo0337/projects/datasets/FP/9421029085211/9421029085211_20241019-184830_back_returnGood_5478c9a4db2c_1640_13867273486.mp4: 640x512 5.3ms\n",
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"video 1/1 (60/60) /home/ieemoo0337/projects/datasets/FP/9421029085211/9421029085211_20241019-184830_back_returnGood_5478c9a4db2c_1640_13867273486.mp4: 640x512 5.3ms\n",
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||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
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||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"{}\n",
|
||
"barcode: 8996001353028\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/8996001353028/8996001353028_20241018-162301_back_addGood_5478c9a53bd4_170_15027299265.mp4\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/8996001353028/8858731200075.jpg\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n",
|
||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
"video 1/1 (1/87) /home/ieemoo0337/projects/datasets/FP/8996001353028/8996001353028_20241018-162301_back_addGood_5478c9a53bd4_170_15027299265.mp4: 640x512 5.8ms\n",
|
||
"video 1/1 (2/87) /home/ieemoo0337/projects/datasets/FP/8996001353028/8996001353028_20241018-162301_back_addGood_5478c9a53bd4_170_15027299265.mp4: 640x512 5.5ms\n",
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"video 1/1 (3/87) /home/ieemoo0337/projects/datasets/FP/8996001353028/8996001353028_20241018-162301_back_addGood_5478c9a53bd4_170_15027299265.mp4: 640x512 5.4ms\n",
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"video 1/1 (4/87) /home/ieemoo0337/projects/datasets/FP/8996001353028/8996001353028_20241018-162301_back_addGood_5478c9a53bd4_170_15027299265.mp4: 640x512 5.4ms\n",
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"video 1/1 (5/87) /home/ieemoo0337/projects/datasets/FP/8996001353028/8996001353028_20241018-162301_back_addGood_5478c9a53bd4_170_15027299265.mp4: 640x512 5.3ms\n",
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"video 1/1 (6/87) /home/ieemoo0337/projects/datasets/FP/8996001353028/8996001353028_20241018-162301_back_addGood_5478c9a53bd4_170_15027299265.mp4: 640x512 5.4ms\n",
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"video 1/1 (7/87) /home/ieemoo0337/projects/datasets/FP/8996001353028/8996001353028_20241018-162301_back_addGood_5478c9a53bd4_170_15027299265.mp4: 640x512 5.4ms\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"load model resnet18 \n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
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"output_type": "stream",
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"video 1/1 (85/87) /home/ieemoo0337/projects/datasets/FP/8996001353028/8996001353028_20241018-162301_back_addGood_5478c9a53bd4_170_15027299265.mp4: 640x512 5.3ms\n",
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"video 1/1 (86/87) /home/ieemoo0337/projects/datasets/FP/8996001353028/8996001353028_20241018-162301_back_addGood_5478c9a53bd4_170_15027299265.mp4: 640x512 5.3ms\n",
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||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
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||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"{'item1': {'Text': 'NANACO', 'Color': '透明', 'Shape': '圆形', 'Material': '果冻', 'Category': '甜点'}, 'item2': {'Text': 'Cal Cheese', 'Color': '橙色', 'Shape': '长方形', 'Material': '饼干', 'Category': '零食'}, 'is_Same': False}\n",
|
||
"barcode: 8859594300018\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/8859594300018/8859015700434.jpg\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/8859594300018/8859594300018_20241017-140218_back_addGood_5478c9a48c3e_560_13586533739.mp4\n"
|
||
]
|
||
},
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||
{
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||
"name": "stderr",
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||
"output_type": "stream",
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|
||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
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|
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},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"load model resnet18 \n"
|
||
]
|
||
},
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||
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||
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"/home/ieemoo0337/projects/detecttracking/tracking/traclus.py:163: RuntimeWarning: divide by zero encountered in scalar divide\n",
|
||
" tan_theta0 = (shorter_slope - longer_slope) / (1 + shorter_slope * longer_slope)\n",
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||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
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||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
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||
]
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||
},
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||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
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||
"text": [
|
||
"{'item1': {'Text': 'Mediterranean White Grape Juice', 'Color': '白色', 'Shape': '圆柱形', 'Material': '塑料', 'Category': '饮料'}, 'item2': {'Text': '未知', 'Color': '未知', 'Shape': '未知', 'Material': '未知', 'Category': '未知'}, 'is_Same': False}\n",
|
||
"barcode: 8934760211005\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/8934760211005/8994834005237.jpg\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/8934760211005/8934760211005_20241020-135449_back_addGood_5478c9a49bfc_5_13799009402.mp4\n"
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||
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||
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||
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||
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||
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||
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|
||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
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||
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||
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||
},
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||
{
|
||
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|
||
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||
"text": [
|
||
"load model resnet18 \n"
|
||
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|
||
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||
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||
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||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
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||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n"
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||
]
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||
},
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||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
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||
"text": [
|
||
"{'item1': {'Text': 'Enaak', 'Color': '黄色', 'Shape': '长方形', 'Material': '塑料', 'Category': '方便面'}, 'item2': {'Text': 'Enaak', 'Color': '黄色', 'Shape': '长方形', 'Material': '塑料', 'Category': '方便面'}, 'is_Same': True}\n",
|
||
"barcode: 9311493002503\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/9311493002503/9311493002503_20241019-155549_back_returnGood_5478c9a49bfc_595_13773168720.mp4\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/9311493002503/9345521003798.jpg\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
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||
"text": [
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n",
|
||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
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||
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||
]
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||
},
|
||
{
|
||
"name": "stdout",
|
||
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||
"text": [
|
||
"load model resnet18 \n"
|
||
]
|
||
},
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||
{
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||
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"video 1/1 (45/46) /home/ieemoo0337/projects/datasets/FP/9311493002503/9311493002503_20241019-155549_back_returnGood_5478c9a49bfc_595_13773168720.mp4: 640x512 5.7ms\n",
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"/home/ieemoo0337/projects/detecttracking/tracking/traclus.py:163: RuntimeWarning: divide by zero encountered in scalar divide\n",
|
||
" tan_theta0 = (shorter_slope - longer_slope) / (1 + shorter_slope * longer_slope)\n",
|
||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
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||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
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||
"text": [
|
||
"{'item1': {'Text': 'Anchor Whipping Cream', 'Color': '蓝色', 'Shape': '长方形', 'Material': '纸', 'Category': '乳制品'}, 'item2': {'Text': '未知', 'Color': '未知', 'Shape': '未知', 'Material': '未知', 'Category': '未知'}, 'is_Same': False}\n",
|
||
"barcode: 9318637391714\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/9318637391714/9421903892140.jpg\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/9318637391714/9318637391714_20241020-180603_back_returnGood_5478c9a53be2_615_18058629568.mp4\n"
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||
]
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||
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||
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||
"name": "stderr",
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||
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|
||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
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||
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|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"load model resnet18 \n"
|
||
]
|
||
},
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||
{
|
||
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"video 1/1 (43/72) /home/ieemoo0337/projects/datasets/FP/9318637391714/9318637391714_20241020-180603_back_returnGood_5478c9a53be2_615_18058629568.mp4: 640x512 5.6ms\n",
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"video 1/1 (44/72) /home/ieemoo0337/projects/datasets/FP/9318637391714/9318637391714_20241020-180603_back_returnGood_5478c9a53be2_615_18058629568.mp4: 640x512 5.7ms\n",
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"video 1/1 (45/72) /home/ieemoo0337/projects/datasets/FP/9318637391714/9318637391714_20241020-180603_back_returnGood_5478c9a53be2_615_18058629568.mp4: 640x512 5.7ms\n",
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"video 1/1 (46/72) /home/ieemoo0337/projects/datasets/FP/9318637391714/9318637391714_20241020-180603_back_returnGood_5478c9a53be2_615_18058629568.mp4: 640x512 5.8ms\n",
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"video 1/1 (47/72) /home/ieemoo0337/projects/datasets/FP/9318637391714/9318637391714_20241020-180603_back_returnGood_5478c9a53be2_615_18058629568.mp4: 640x512 5.6ms\n",
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"video 1/1 (48/72) /home/ieemoo0337/projects/datasets/FP/9318637391714/9318637391714_20241020-180603_back_returnGood_5478c9a53be2_615_18058629568.mp4: 640x512 5.5ms\n",
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"video 1/1 (49/72) /home/ieemoo0337/projects/datasets/FP/9318637391714/9318637391714_20241020-180603_back_returnGood_5478c9a53be2_615_18058629568.mp4: 640x512 5.5ms\n",
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"video 1/1 (52/72) /home/ieemoo0337/projects/datasets/FP/9318637391714/9318637391714_20241020-180603_back_returnGood_5478c9a53be2_615_18058629568.mp4: 640x512 5.5ms\n",
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"video 1/1 (60/72) /home/ieemoo0337/projects/datasets/FP/9318637391714/9318637391714_20241020-180603_back_returnGood_5478c9a53be2_615_18058629568.mp4: 640x512 (no detections), 5.7ms\n",
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"video 1/1 (63/72) /home/ieemoo0337/projects/datasets/FP/9318637391714/9318637391714_20241020-180603_back_returnGood_5478c9a53be2_615_18058629568.mp4: 640x512 (no detections), 5.7ms\n",
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"video 1/1 (67/72) /home/ieemoo0337/projects/datasets/FP/9318637391714/9318637391714_20241020-180603_back_returnGood_5478c9a53be2_615_18058629568.mp4: 640x512 (no detections), 5.7ms\n",
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"video 1/1 (68/72) /home/ieemoo0337/projects/datasets/FP/9318637391714/9318637391714_20241020-180603_back_returnGood_5478c9a53be2_615_18058629568.mp4: 640x512 (no detections), 5.7ms\n",
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"video 1/1 (69/72) /home/ieemoo0337/projects/datasets/FP/9318637391714/9318637391714_20241020-180603_back_returnGood_5478c9a53be2_615_18058629568.mp4: 640x512 (no detections), 5.8ms\n",
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"video 1/1 (70/72) /home/ieemoo0337/projects/datasets/FP/9318637391714/9318637391714_20241020-180603_back_returnGood_5478c9a53be2_615_18058629568.mp4: 640x512 (no detections), 5.8ms\n",
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"video 1/1 (71/72) /home/ieemoo0337/projects/datasets/FP/9318637391714/9318637391714_20241020-180603_back_returnGood_5478c9a53be2_615_18058629568.mp4: 640x512 (no detections), 5.9ms\n",
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"video 1/1 (72/72) /home/ieemoo0337/projects/datasets/FP/9318637391714/9318637391714_20241020-180603_back_returnGood_5478c9a53be2_615_18058629568.mp4: 640x512 (no detections), 5.8ms\n",
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||
"/home/ieemoo0337/projects/detecttracking/tracking/traclus.py:163: RuntimeWarning: divide by zero encountered in scalar divide\n",
|
||
" tan_theta0 = (shorter_slope - longer_slope) / (1 + shorter_slope * longer_slope)\n",
|
||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
|
||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
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||
]
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||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
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||
"text": [
|
||
"Error processing 9318637391714: unterminated string literal (detected at line 3) (<unknown>, line 3)\n",
|
||
"barcode: 9311493003982\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/9311493003982/9310072013855.jpg\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/9311493003982/9311493003982_20241019-155719_back_returnGood_5478c9a49bfc_595_13773168720.mp4\n"
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||
]
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},
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{
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"name": "stderr",
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||
"output_type": "stream",
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"text": [
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||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
"video 1/1 (1/45) /home/ieemoo0337/projects/datasets/FP/9311493003982/9311493003982_20241019-155719_back_returnGood_5478c9a49bfc_595_13773168720.mp4: 640x512 5.9ms\n",
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||
"video 1/1 (2/45) /home/ieemoo0337/projects/datasets/FP/9311493003982/9311493003982_20241019-155719_back_returnGood_5478c9a49bfc_595_13773168720.mp4: 640x512 5.4ms\n",
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"video 1/1 (4/45) /home/ieemoo0337/projects/datasets/FP/9311493003982/9311493003982_20241019-155719_back_returnGood_5478c9a49bfc_595_13773168720.mp4: 640x512 5.4ms\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"load model resnet18 \n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
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"output_type": "stream",
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"video 1/1 (45/45) /home/ieemoo0337/projects/datasets/FP/9311493003982/9311493003982_20241019-155719_back_returnGood_5478c9a49bfc_595_13773168720.mp4: 640x512 5.3ms\n",
|
||
"/home/ieemoo0337/projects/detecttracking/tracking/traclus.py:163: RuntimeWarning: divide by zero encountered in scalar divide\n",
|
||
" tan_theta0 = (shorter_slope - longer_slope) / (1 + shorter_slope * longer_slope)\n",
|
||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
|
||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
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"text": [
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"{'item1': {'Text': 'Tim Tam', 'Color': '蓝色', 'Shape': '长方形', 'Material': '纸', 'Category': '饼干'}, 'item2': {'Text': '未知', 'Color': '未知', 'Shape': '未知', 'Material': '未知', 'Category': '未知'}, 'is_Same': False}\n",
|
||
"barcode: 9346506008760\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/9346506008760/9346506008760_20241017-154228_back_addGood_5478c9a48c3e_1195_13586533739.mp4\n",
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||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/9346506008760/9345521001145.jpg\n"
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||
"name": "stderr",
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||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
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|
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|
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},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
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"text": [
|
||
"load model resnet18 \n"
|
||
]
|
||
},
|
||
{
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||
"name": "stderr",
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|
||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
|
||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"{'item1': {'Text': 'GreenKosy SILK MOISTURIZING SHAMPOO', 'Color': '白色', 'Shape': '圆柱形', 'Material': '塑料', 'Category': '洗发水'}, 'item2': {'Text': 'JerseyJoy', 'Color': '白色', 'Shape': '圆形', 'Material': '塑料', 'Category': '牛奶'}, 'is_Same': False}\n",
|
||
"barcode: 9415007301578\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/9415007301578/9345521003767.jpg\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/9415007301578/9415007301578_20241014-171027_back_addGood_5478c9a53bf4_245_13799009402.mp4\n"
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{
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"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"load model resnet18 \n"
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]
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},
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"video 1/1 (102/105) /home/ieemoo0337/projects/datasets/FP/9415007301578/9415007301578_20241014-171027_back_addGood_5478c9a53bf4_245_13799009402.mp4: 640x512 5.4ms\n",
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"/home/ieemoo0337/projects/detecttracking/tracking/traclus.py:163: RuntimeWarning: divide by zero encountered in scalar divide\n",
|
||
" tan_theta0 = (shorter_slope - longer_slope) / (1 + shorter_slope * longer_slope)\n",
|
||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
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||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
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||
]
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||
},
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||
{
|
||
"name": "stdout",
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||
"output_type": "stream",
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"text": [
|
||
"{'item1': {'Text': 'SEA SALT SHAMPOO', 'Color': '蓝色', 'Shape': '长方形', 'Material': '塑料', 'Category': '洗发水'}, 'item2': {'Text': '未知', 'Color': '未知', 'Shape': '未知', 'Material': '未知', 'Category': '未知'}, 'is_Same': False}\n",
|
||
"barcode: 9315090201758\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/9315090201758/8850718803347.jpg\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/9315090201758/9315090201758_20241014-161706_back_returnGood_5478c9a49bfc_2920_18133699824.mp4\n"
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||
]
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||
},
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||
{
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"name": "stderr",
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"output_type": "stream",
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"text": [
|
||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
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|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"load model resnet18 \n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
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"output_type": "stream",
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"/home/ieemoo0337/projects/detecttracking/tracking/traclus.py:163: RuntimeWarning: divide by zero encountered in scalar divide\n",
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||
" tan_theta0 = (shorter_slope - longer_slope) / (1 + shorter_slope * longer_slope)\n",
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||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
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||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
|
||
]
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||
},
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||
{
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||
"name": "stdout",
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||
"output_type": "stream",
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||
"text": [
|
||
"{'item1': {'Text': \"Lay's STAX Original\", 'Color': '黄色', 'Shape': '圆柱形', 'Material': '纸质', 'Category': '零食'}, 'item2': {'Text': '澳牧A2β-酪蛋白儿童成长牛奶', 'Color': '红色', 'Shape': '长方体', 'Material': '纸质', 'Category': '乳制品'}, 'is_Same': False}\n",
|
||
"barcode: 8993379257644\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/8993379257644/9556041613866.jpg\n",
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||
"video: /home/ieemoo0337/projects/datasets/FP/8993379257644/8993379257644_20241018-152954_back_addGood_5478c9a48c02_245_13586533739.mp4\n"
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]
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||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
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||
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{
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"load model resnet18 \n"
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"video 1/1 (56/58) /home/ieemoo0337/projects/datasets/FP/8993379257644/8993379257644_20241018-152954_back_addGood_5478c9a48c02_245_13586533739.mp4: 640x512 5.5ms\n",
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||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
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||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
|
||
]
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||
},
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||
{
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||
"name": "stdout",
|
||
"output_type": "stream",
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||
"text": [
|
||
"{'item1': {'Text': '雄鸡标 沙拉酱金枪鱼', 'Color': '红色', 'Shape': '圆形', 'Material': '金属', 'Category': '食品'}, 'item2': {'Text': 'Pop', 'Color': '白色', 'Shape': '长方形', 'Material': '纸', 'Category': '食品'}, 'is_Same': False}\n",
|
||
"barcode: 8996001303078\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/8996001303078/9345521000926.jpg\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/8996001303078/8996001303078_20241017-111853_back_addGood_5478c9a51ba6_5_18358205530.mp4\n"
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||
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||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
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||
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||
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||
{
|
||
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|
||
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|
||
"load model resnet18 \n"
|
||
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||
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"video 1/1 (105/111) /home/ieemoo0337/projects/datasets/FP/8996001303078/8996001303078_20241017-111853_back_addGood_5478c9a51ba6_5_18358205530.mp4: 640x512 5.6ms\n",
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"video 1/1 (106/111) /home/ieemoo0337/projects/datasets/FP/8996001303078/8996001303078_20241017-111853_back_addGood_5478c9a51ba6_5_18358205530.mp4: 640x512 5.5ms\n",
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"video 1/1 (107/111) /home/ieemoo0337/projects/datasets/FP/8996001303078/8996001303078_20241017-111853_back_addGood_5478c9a51ba6_5_18358205530.mp4: 640x512 5.5ms\n",
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"video 1/1 (109/111) /home/ieemoo0337/projects/datasets/FP/8996001303078/8996001303078_20241017-111853_back_addGood_5478c9a51ba6_5_18358205530.mp4: 640x512 5.5ms\n",
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"video 1/1 (110/111) /home/ieemoo0337/projects/datasets/FP/8996001303078/8996001303078_20241017-111853_back_addGood_5478c9a51ba6_5_18358205530.mp4: 640x512 5.5ms\n",
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"video 1/1 (111/111) /home/ieemoo0337/projects/datasets/FP/8996001303078/8996001303078_20241017-111853_back_addGood_5478c9a51ba6_5_18358205530.mp4: 640x512 5.4ms\n",
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"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
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"\n",
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||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
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||
"Fusing layers... \n"
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||
]
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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||
"{'item1': {'Text': 'GreenKosy NATURAL Goat Milk Bath Milk', 'Color': '白色', 'Shape': '长方形', 'Material': '塑料', 'Category': '沐浴乳'}, 'item2': {'Text': 'Biscuit', 'Color': '白色', 'Shape': '圆形', 'Material': '纸', 'Category': '饼干'}, 'is_Same': False}\n",
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||
"barcode: 9345521003781\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/9345521003781/9551010541867.jpg\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/9345521003781/9345521003781_20241016-152122_back_addGood_5478c9a48b7e_805_13586533739.mp4\n"
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||
]
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},
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||
{
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||
"name": "stderr",
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"output_type": "stream",
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"text": [
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"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n",
|
||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
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]
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},
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{
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||
"name": "stdout",
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||
"output_type": "stream",
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"text": [
|
||
"load model resnet18 \n"
|
||
]
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||
},
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{
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"name": "stderr",
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"video 1/1 (89/93) /home/ieemoo0337/projects/datasets/FP/9345521003781/9345521003781_20241016-152122_back_addGood_5478c9a48b7e_805_13586533739.mp4: 640x512 5.5ms\n",
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"video 1/1 (91/93) /home/ieemoo0337/projects/datasets/FP/9345521003781/9345521003781_20241016-152122_back_addGood_5478c9a48b7e_805_13586533739.mp4: 640x512 5.5ms\n",
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"video 1/1 (93/93) /home/ieemoo0337/projects/datasets/FP/9345521003781/9345521003781_20241016-152122_back_addGood_5478c9a48b7e_805_13586533739.mp4: 640x512 5.5ms\n",
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"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
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||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
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||
]
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||
},
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||
{
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||
"name": "stdout",
|
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"output_type": "stream",
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||
"text": [
|
||
"{'item1': {'Text': 'MICO', 'Color': '蓝色', 'Shape': '圆形', 'Material': '纸', 'Category': '饼干'}, 'item2': {'Text': 'MICO', 'Color': '蓝色', 'Shape': '圆形', 'Material': '塑料', 'Category': '清洁用品'}, 'is_Same': False}\n",
|
||
"barcode: 9345521000933\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/9345521000933/9345521000933_20241018-142812_back_addGood_5478c9a48b8c_795_13799009402.mp4\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/9345521000933/8888077102023.jpg\n"
|
||
]
|
||
},
|
||
{
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"name": "stderr",
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||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
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},
|
||
{
|
||
"name": "stdout",
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||
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"text": [
|
||
"load model resnet18 \n"
|
||
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||
},
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||
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||
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"video 1/1 (52/55) /home/ieemoo0337/projects/datasets/FP/9345521000933/9345521000933_20241018-142812_back_addGood_5478c9a48b8c_795_13799009402.mp4: 640x512 5.5ms\n",
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"video 1/1 (53/55) /home/ieemoo0337/projects/datasets/FP/9345521000933/9345521000933_20241018-142812_back_addGood_5478c9a48b8c_795_13799009402.mp4: 640x512 5.6ms\n",
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"video 1/1 (54/55) /home/ieemoo0337/projects/datasets/FP/9345521000933/9345521000933_20241018-142812_back_addGood_5478c9a48b8c_795_13799009402.mp4: 640x512 5.5ms\n",
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"video 1/1 (55/55) /home/ieemoo0337/projects/datasets/FP/9345521000933/9345521000933_20241018-142812_back_addGood_5478c9a48b8c_795_13799009402.mp4: 640x512 5.5ms\n",
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||
"/home/ieemoo0337/projects/detecttracking/tracking/traclus.py:163: RuntimeWarning: divide by zero encountered in scalar divide\n",
|
||
" tan_theta0 = (shorter_slope - longer_slope) / (1 + shorter_slope * longer_slope)\n",
|
||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
|
||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
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||
"text": [
|
||
"{'item1': {'Text': 'HELLO PANDA', 'Color': '红色', 'Shape': '长方形', 'Material': '纸盒', 'Category': '零食'}, 'item2': {'Text': '未知', 'Color': '未知', 'Shape': '未知', 'Material': '未知', 'Category': '未知'}, 'is_Same': False}\n",
|
||
"barcode: 8809916330421\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/8809916330421/9311493002480.jpg\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/8809916330421/8809916330421_20241015-111046_back_addGood_5478c9a4db2c_280_13586533739.mp4\n"
|
||
]
|
||
},
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||
{
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||
"name": "stderr",
|
||
"output_type": "stream",
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||
"text": [
|
||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
"video 1/1 (1/84) /home/ieemoo0337/projects/datasets/FP/8809916330421/8809916330421_20241015-111046_back_addGood_5478c9a4db2c_280_13586533739.mp4: 640x512 6.4ms\n",
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"video 1/1 (2/84) /home/ieemoo0337/projects/datasets/FP/8809916330421/8809916330421_20241015-111046_back_addGood_5478c9a4db2c_280_13586533739.mp4: 640x512 5.4ms\n",
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"video 1/1 (3/84) /home/ieemoo0337/projects/datasets/FP/8809916330421/8809916330421_20241015-111046_back_addGood_5478c9a4db2c_280_13586533739.mp4: 640x512 5.4ms\n",
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"video 1/1 (4/84) /home/ieemoo0337/projects/datasets/FP/8809916330421/8809916330421_20241015-111046_back_addGood_5478c9a4db2c_280_13586533739.mp4: 640x512 5.4ms\n",
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"video 1/1 (5/84) /home/ieemoo0337/projects/datasets/FP/8809916330421/8809916330421_20241015-111046_back_addGood_5478c9a4db2c_280_13586533739.mp4: 640x512 5.4ms\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"load model resnet18 \n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
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"video 1/1 (72/84) /home/ieemoo0337/projects/datasets/FP/8809916330421/8809916330421_20241015-111046_back_addGood_5478c9a4db2c_280_13586533739.mp4: 640x512 5.4ms\n",
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"video 1/1 (73/84) /home/ieemoo0337/projects/datasets/FP/8809916330421/8809916330421_20241015-111046_back_addGood_5478c9a4db2c_280_13586533739.mp4: 640x512 5.3ms\n",
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"video 1/1 (74/84) /home/ieemoo0337/projects/datasets/FP/8809916330421/8809916330421_20241015-111046_back_addGood_5478c9a4db2c_280_13586533739.mp4: 640x512 5.4ms\n",
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"video 1/1 (75/84) /home/ieemoo0337/projects/datasets/FP/8809916330421/8809916330421_20241015-111046_back_addGood_5478c9a4db2c_280_13586533739.mp4: 640x512 5.4ms\n",
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"video 1/1 (76/84) /home/ieemoo0337/projects/datasets/FP/8809916330421/8809916330421_20241015-111046_back_addGood_5478c9a4db2c_280_13586533739.mp4: 640x512 5.4ms\n",
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"video 1/1 (77/84) /home/ieemoo0337/projects/datasets/FP/8809916330421/8809916330421_20241015-111046_back_addGood_5478c9a4db2c_280_13586533739.mp4: 640x512 5.4ms\n",
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"video 1/1 (78/84) /home/ieemoo0337/projects/datasets/FP/8809916330421/8809916330421_20241015-111046_back_addGood_5478c9a4db2c_280_13586533739.mp4: 640x512 5.4ms\n",
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"video 1/1 (79/84) /home/ieemoo0337/projects/datasets/FP/8809916330421/8809916330421_20241015-111046_back_addGood_5478c9a4db2c_280_13586533739.mp4: 640x512 5.4ms\n",
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"video 1/1 (80/84) /home/ieemoo0337/projects/datasets/FP/8809916330421/8809916330421_20241015-111046_back_addGood_5478c9a4db2c_280_13586533739.mp4: 640x512 5.5ms\n",
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"video 1/1 (81/84) /home/ieemoo0337/projects/datasets/FP/8809916330421/8809916330421_20241015-111046_back_addGood_5478c9a4db2c_280_13586533739.mp4: 640x512 5.6ms\n",
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"video 1/1 (82/84) /home/ieemoo0337/projects/datasets/FP/8809916330421/8809916330421_20241015-111046_back_addGood_5478c9a4db2c_280_13586533739.mp4: 640x512 5.4ms\n",
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"video 1/1 (83/84) /home/ieemoo0337/projects/datasets/FP/8809916330421/8809916330421_20241015-111046_back_addGood_5478c9a4db2c_280_13586533739.mp4: 640x512 5.5ms\n",
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"video 1/1 (84/84) /home/ieemoo0337/projects/datasets/FP/8809916330421/8809916330421_20241015-111046_back_addGood_5478c9a4db2c_280_13586533739.mp4: 640x512 5.5ms\n",
|
||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
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||
"\n"
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||
]
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},
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||
{
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||
"name": "stdout",
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||
"output_type": "stream",
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||
"text": [
|
||
"{'item1': {'Text': 'GreenKosy', 'Color': '绿色', 'Shape': '长方形', 'Material': '塑料', 'Category': '洗发水'}, 'item2': {'Text': 'FINUTE CRAB SHRIMP chips', 'Color': '红色', 'Shape': '长方形', 'Material': '塑料', 'Category': '零食'}, 'is_Same': False}\n",
|
||
"barcode: 8886001012301\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/8886001012301/8886001012301_20241020-104946_back_returnGood_5478c9a53bd4_1955_14785332147.mp4\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/8886001012301/9421902960819.jpg\n"
|
||
]
|
||
},
|
||
{
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||
"name": "stderr",
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||
"output_type": "stream",
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"text": [
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n",
|
||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
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"video 1/1 (3/80) /home/ieemoo0337/projects/datasets/FP/8886001012301/8886001012301_20241020-104946_back_returnGood_5478c9a53bd4_1955_14785332147.mp4: 640x512 5.5ms\n",
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"video 1/1 (4/80) /home/ieemoo0337/projects/datasets/FP/8886001012301/8886001012301_20241020-104946_back_returnGood_5478c9a53bd4_1955_14785332147.mp4: 640x512 5.4ms\n",
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"video 1/1 (5/80) /home/ieemoo0337/projects/datasets/FP/8886001012301/8886001012301_20241020-104946_back_returnGood_5478c9a53bd4_1955_14785332147.mp4: 640x512 5.4ms\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"load model resnet18 \n"
|
||
]
|
||
},
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||
{
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||
"name": "stderr",
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"video 1/1 (78/80) /home/ieemoo0337/projects/datasets/FP/8886001012301/8886001012301_20241020-104946_back_returnGood_5478c9a53bd4_1955_14785332147.mp4: 640x512 5.4ms\n",
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"video 1/1 (79/80) /home/ieemoo0337/projects/datasets/FP/8886001012301/8886001012301_20241020-104946_back_returnGood_5478c9a53bd4_1955_14785332147.mp4: 640x512 5.4ms\n",
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"video 1/1 (80/80) /home/ieemoo0337/projects/datasets/FP/8886001012301/8886001012301_20241020-104946_back_returnGood_5478c9a53bd4_1955_14785332147.mp4: 640x512 5.3ms\n",
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"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
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||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n"
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||
]
|
||
},
|
||
{
|
||
"name": "stdout",
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||
"output_type": "stream",
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||
"text": [
|
||
"{'item1': {'Text': '至初 婴儿配方奶粉 (0-6月龄,1段)', 'Color': '紫色', 'Shape': '圆柱形', 'Material': '金属', 'Category': '婴儿配方奶粉'}, 'item2': {'Text': 'Danisa 丹麦皇冠', 'Color': '白色', 'Shape': '长方形', 'Material': '纸盒', 'Category': '饼干'}, 'is_Same': False}\n",
|
||
"barcode: 9315090211498\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/9315090211498/8996001303764.jpg\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/9315090211498/9315090211498_20241017-172454_back_addGood_5478c9a49bfc_1080_13773168720.mp4\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
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||
"output_type": "stream",
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||
"text": [
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n",
|
||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
"video 1/1 (1/81) /home/ieemoo0337/projects/datasets/FP/9315090211498/9315090211498_20241017-172454_back_addGood_5478c9a49bfc_1080_13773168720.mp4: 640x512 6.5ms\n",
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"video 1/1 (6/81) /home/ieemoo0337/projects/datasets/FP/9315090211498/9315090211498_20241017-172454_back_addGood_5478c9a49bfc_1080_13773168720.mp4: 640x512 5.6ms\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
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||
"text": [
|
||
"load model resnet18 \n"
|
||
]
|
||
},
|
||
{
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||
"name": "stderr",
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"output_type": "stream",
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"video 1/1 (77/81) /home/ieemoo0337/projects/datasets/FP/9315090211498/9315090211498_20241017-172454_back_addGood_5478c9a49bfc_1080_13773168720.mp4: 640x512 5.6ms\n",
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"video 1/1 (79/81) /home/ieemoo0337/projects/datasets/FP/9315090211498/9315090211498_20241017-172454_back_addGood_5478c9a49bfc_1080_13773168720.mp4: 640x512 5.6ms\n",
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"video 1/1 (80/81) /home/ieemoo0337/projects/datasets/FP/9315090211498/9315090211498_20241017-172454_back_addGood_5478c9a49bfc_1080_13773168720.mp4: 640x512 5.8ms\n",
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"video 1/1 (81/81) /home/ieemoo0337/projects/datasets/FP/9315090211498/9315090211498_20241017-172454_back_addGood_5478c9a49bfc_1080_13773168720.mp4: 640x512 5.6ms\n",
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"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
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"\n",
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||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
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||
]
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},
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{
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||
"name": "stdout",
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"output_type": "stream",
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"text": [
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||
"{'item1': {'Text': 'Danisa Traditional Butter Cookies', 'Color': '蓝色', 'Shape': '圆形', 'Material': '金属', 'Category': '饼干'}, 'item2': {'Text': 'Pure Milk', 'Color': '白色', 'Shape': '长方形', 'Material': '纸', 'Category': '牛奶'}, 'is_Same': False}\n",
|
||
"barcode: 8852756303353\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/8852756303353/8999178654332.jpg\n",
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||
"video: /home/ieemoo0337/projects/datasets/FP/8852756303353/8852756303353_20241016-154520_back_returnGood_5478c9a49bfc_220_18358205530.mp4\n"
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"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
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},
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{
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||
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"text": [
|
||
"load model resnet18 \n"
|
||
]
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||
},
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"/home/ieemoo0337/projects/detecttracking/tracking/traclus.py:163: RuntimeWarning: divide by zero encountered in scalar divide\n",
|
||
" tan_theta0 = (shorter_slope - longer_slope) / (1 + shorter_slope * longer_slope)\n",
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||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
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"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
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||
]
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
|
||
"{'item1': {'Text': 'MaiTos Tortilla Chips Snack', 'Color': '白色', 'Shape': '长方形', 'Material': '塑料', 'Category': '零食'}, 'item2': {'Text': \"Kellogg's\", 'Color': '白色', 'Shape': '长方形', 'Material': '纸', 'Category': '早餐谷物'}, 'is_Same': False}\n",
|
||
"barcode: 8888077102023\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/8888077102023/8888077102023_20241020-141328_back_addGood_5478c9a49bfc_100_13799009402.mp4\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/8888077102023/9345521000933.jpg\n"
|
||
]
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||
},
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||
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||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
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},
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||
{
|
||
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||
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||
"text": [
|
||
"load model resnet18 \n"
|
||
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||
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||
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||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
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||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n"
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||
]
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||
},
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||
{
|
||
"name": "stdout",
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||
"output_type": "stream",
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||
"text": [
|
||
"{'item1': {'Text': 'Bundaberg PEACH SPARKLING DRINK', 'Color': '橙色', 'Shape': '长方形', 'Material': '玻璃', 'Category': '饮料'}, 'item2': {'Text': 'HELLO PANDA', 'Color': '红色', 'Shape': '长方形', 'Material': '纸', 'Category': '零食'}, 'is_Same': False}\n",
|
||
"barcode: 8993083932950\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/8993083932950/9556041610032.jpg\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/8993083932950/8993083932950_20241019-151253_back_returnGood_5478c9a49bfc_135_13773168720.mp4\n"
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||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
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||
"text": [
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n",
|
||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
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||
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||
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|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
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||
"text": [
|
||
"load model resnet18 \n"
|
||
]
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||
},
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||
{
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||
"name": "stderr",
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||
"output_type": "stream",
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"video 1/1 (30/50) /home/ieemoo0337/projects/datasets/FP/8993083932950/8993083932950_20241019-151253_back_returnGood_5478c9a49bfc_135_13773168720.mp4: 640x512 5.2ms\n",
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"video 1/1 (45/50) /home/ieemoo0337/projects/datasets/FP/8993083932950/8993083932950_20241019-151253_back_returnGood_5478c9a49bfc_135_13773168720.mp4: 640x512 5.2ms\n",
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"video 1/1 (46/50) /home/ieemoo0337/projects/datasets/FP/8993083932950/8993083932950_20241019-151253_back_returnGood_5478c9a49bfc_135_13773168720.mp4: 640x512 5.2ms\n",
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"video 1/1 (47/50) /home/ieemoo0337/projects/datasets/FP/8993083932950/8993083932950_20241019-151253_back_returnGood_5478c9a49bfc_135_13773168720.mp4: 640x512 5.2ms\n",
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"video 1/1 (48/50) /home/ieemoo0337/projects/datasets/FP/8993083932950/8993083932950_20241019-151253_back_returnGood_5478c9a49bfc_135_13773168720.mp4: 640x512 5.2ms\n",
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"video 1/1 (49/50) /home/ieemoo0337/projects/datasets/FP/8993083932950/8993083932950_20241019-151253_back_returnGood_5478c9a49bfc_135_13773168720.mp4: 640x512 5.2ms\n",
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"video 1/1 (50/50) /home/ieemoo0337/projects/datasets/FP/8993083932950/8993083932950_20241019-151253_back_returnGood_5478c9a49bfc_135_13773168720.mp4: 640x512 5.2ms\n",
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"/home/ieemoo0337/projects/detecttracking/tracking/traclus.py:163: RuntimeWarning: divide by zero encountered in scalar divide\n",
|
||
" tan_theta0 = (shorter_slope - longer_slope) / (1 + shorter_slope * longer_slope)\n",
|
||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
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||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
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||
]
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||
},
|
||
{
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||
"name": "stdout",
|
||
"output_type": "stream",
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||
"text": [
|
||
"{'item1': {'Text': '雄鸡标', 'Color': '蓝色', 'Shape': '圆形', 'Material': '金属', 'Category': '食品'}, 'item2': {'Text': 'Chocolate Strawberry Mix', 'Color': '绿色', 'Shape': '长方形', 'Material': '纸', 'Category': '食品'}, 'is_Same': False}\n",
|
||
"barcode: 9345521000926\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/9345521000926/9345521000926_20241020-152414_back_addGood_5478c9a53be2_795_18058629568.mp4\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/9345521000926/8996001303078.jpg\n"
|
||
]
|
||
},
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||
{
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"name": "stderr",
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||
"output_type": "stream",
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|
||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
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]
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},
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||
{
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||
"name": "stdout",
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||
"output_type": "stream",
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||
"text": [
|
||
"load model resnet18 \n"
|
||
]
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||
},
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"/home/ieemoo0337/projects/detecttracking/tracking/traclus.py:163: RuntimeWarning: divide by zero encountered in scalar divide\n",
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||
" tan_theta0 = (shorter_slope - longer_slope) / (1 + shorter_slope * longer_slope)\n",
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||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
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||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
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||
]
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||
},
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||
{
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||
"name": "stdout",
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||
"output_type": "stream",
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||
"text": [
|
||
"{'item1': {'Text': 'Danisa Traditional Butter Cookies', 'Color': '蓝色', 'Shape': '圆形', 'Material': '纸盒', 'Category': '饼干'}, 'item2': {'Text': '未知', 'Color': '未知', 'Shape': '未知', 'Material': '未知', 'Category': '未知'}, 'is_Same': False}\n",
|
||
"barcode: 8996001303474\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/8996001303474/9421903892119.jpg\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/8996001303474/8996001303474_20241020-175014_back_returnGood_5478c9a53bd4_2030_14785332147.mp4\n"
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||
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||
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||
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||
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||
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||
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|
||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
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||
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||
},
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||
{
|
||
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||
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||
"text": [
|
||
"load model resnet18 \n"
|
||
]
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||
},
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||
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||
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||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
|
||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
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||
"text": [
|
||
"{}\n",
|
||
"barcode: 9421029081985\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/9421029081985/9421029081985_20241018-113315_back_returnGood_5478c9a48b7e_1055_15027299265.mp4\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/9421029081985/9421029080278.jpg\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
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||
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||
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|
||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
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]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
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||
"text": [
|
||
"load model resnet18 \n"
|
||
]
|
||
},
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||
{
|
||
"name": "stderr",
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"/home/ieemoo0337/projects/detecttracking/tracking/traclus.py:163: RuntimeWarning: divide by zero encountered in scalar divide\n",
|
||
" tan_theta0 = (shorter_slope - longer_slope) / (1 + shorter_slope * longer_slope)\n",
|
||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
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||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
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||
]
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||
},
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||
{
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"name": "stdout",
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"output_type": "stream",
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||
"text": [
|
||
"{'item1': {'Text': 'Theland New Zealand Farm Milk Powder Skim Milk Powder', 'Color': '蓝色', 'Shape': '长方形', 'Material': '塑料', 'Category': '乳制品'}, 'item2': {'Text': 'New Zealand Farm Milk Powder Skim Milk Powder', 'Color': '白色', 'Shape': '长方形', 'Material': '塑料', 'Category': '乳制品'}, 'is_Same': True}\n",
|
||
"barcode: 9311493002480\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/9311493002480/8809916330421.jpg\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/9311493002480/9311493002480_20241018-112402_back_returnGood_5478c9a49bfc_595_18969520488.mp4\n"
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||
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||
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||
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||
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||
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||
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||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
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|
||
]
|
||
},
|
||
{
|
||
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|
||
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||
"text": [
|
||
"load model resnet18 \n"
|
||
]
|
||
},
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||
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||
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"video 1/1 (81/87) /home/ieemoo0337/projects/datasets/FP/9311493002480/9311493002480_20241018-112402_back_returnGood_5478c9a49bfc_595_18969520488.mp4: 640x512 5.5ms\n",
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"video 1/1 (82/87) /home/ieemoo0337/projects/datasets/FP/9311493002480/9311493002480_20241018-112402_back_returnGood_5478c9a49bfc_595_18969520488.mp4: 640x512 5.4ms\n",
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"video 1/1 (83/87) /home/ieemoo0337/projects/datasets/FP/9311493002480/9311493002480_20241018-112402_back_returnGood_5478c9a49bfc_595_18969520488.mp4: 640x512 5.4ms\n",
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"video 1/1 (84/87) /home/ieemoo0337/projects/datasets/FP/9311493002480/9311493002480_20241018-112402_back_returnGood_5478c9a49bfc_595_18969520488.mp4: 640x512 5.4ms\n",
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"video 1/1 (85/87) /home/ieemoo0337/projects/datasets/FP/9311493002480/9311493002480_20241018-112402_back_returnGood_5478c9a49bfc_595_18969520488.mp4: 640x512 5.4ms\n",
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"video 1/1 (86/87) /home/ieemoo0337/projects/datasets/FP/9311493002480/9311493002480_20241018-112402_back_returnGood_5478c9a49bfc_595_18969520488.mp4: 640x512 5.4ms\n",
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"video 1/1 (87/87) /home/ieemoo0337/projects/datasets/FP/9311493002480/9311493002480_20241018-112402_back_returnGood_5478c9a49bfc_595_18969520488.mp4: 640x512 5.5ms\n",
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||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
|
||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n"
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||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"{'item1': {'Text': 'GOOD LIFE FINUTE CRAB chips 게 맛 칩', 'Color': '红色', 'Shape': '长方形', 'Material': '塑料', 'Category': '零食'}, 'item2': {'Text': 'LADABERG PEACH', 'Color': '橙色', 'Shape': '圆形', 'Material': '玻璃', 'Category': '饮料'}, 'is_Same': False}\n",
|
||
"barcode: 9415007042037\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/9415007042037/8935024156117.jpg\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/9415007042037/9415007042037_20241020-113231_back_addGood_5478c9a4db2c_90_13773168720.mp4\n"
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||
]
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||
},
|
||
{
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||
"name": "stderr",
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||
"output_type": "stream",
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||
"text": [
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n",
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||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
"video 1/1 (1/53) /home/ieemoo0337/projects/datasets/FP/9415007042037/9415007042037_20241020-113231_back_addGood_5478c9a4db2c_90_13773168720.mp4: 640x512 6.5ms\n",
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]
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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||
"load model resnet18 \n"
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]
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},
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"video 1/1 (49/53) /home/ieemoo0337/projects/datasets/FP/9415007042037/9415007042037_20241020-113231_back_addGood_5478c9a4db2c_90_13773168720.mp4: 640x512 5.9ms\n",
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"video 1/1 (51/53) /home/ieemoo0337/projects/datasets/FP/9415007042037/9415007042037_20241020-113231_back_addGood_5478c9a4db2c_90_13773168720.mp4: 640x512 5.8ms\n",
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"video 1/1 (52/53) /home/ieemoo0337/projects/datasets/FP/9415007042037/9415007042037_20241020-113231_back_addGood_5478c9a4db2c_90_13773168720.mp4: 640x512 5.9ms\n",
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"video 1/1 (53/53) /home/ieemoo0337/projects/datasets/FP/9415007042037/9415007042037_20241020-113231_back_addGood_5478c9a4db2c_90_13773168720.mp4: 640x512 5.9ms\n",
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||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
|
||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"{'item1': {'Text': 'G7 COFFEE INSTANT COFFEE', 'Color': '红色', 'Shape': '长方形', 'Material': '塑料', 'Category': '咖啡'}, 'item2': {'Text': '水果果冻', 'Color': '紫色', 'Shape': '长方形', 'Material': '塑料', 'Category': '糖果'}, 'is_Same': False}\n",
|
||
"barcode: 9556041610032\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/9556041610032/8993083932950.jpg\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/9556041610032/9556041610032_20241018-152331_back_addGood_5478c9a48c3e_355_14785332147.mp4\n"
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||
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||
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||
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||
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|
||
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||
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|
||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
"video 1/1 (1/68) /home/ieemoo0337/projects/datasets/FP/9556041610032/9556041610032_20241018-152331_back_addGood_5478c9a48c3e_355_14785332147.mp4: 640x512 7.0ms\n",
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||
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|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"load model resnet18 \n"
|
||
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|
||
},
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||
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||
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||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
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||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"{'item1': {'Text': 'Assorted BEAR COOKIES', 'Color': '蓝色', 'Shape': '熊的形状', 'Material': '饼干', 'Category': '零食'}, 'item2': {'Text': '未知', 'Color': '未知', 'Shape': '未知', 'Material': '未知', 'Category': '未知'}, 'is_Same': False}\n",
|
||
"barcode: 8859015700168\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/8859015700168/8859015700168_20241017-175130_back_returnGood_5478c9a48b7e_380_13799009402.mp4\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/8859015700168/8859069907438.jpg\n"
|
||
]
|
||
},
|
||
{
|
||
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||
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||
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|
||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
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||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
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||
"text": [
|
||
"load model resnet18 \n"
|
||
]
|
||
},
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||
{
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||
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"video 1/1 (28/34) /home/ieemoo0337/projects/datasets/FP/8859015700168/8859015700168_20241017-175130_back_returnGood_5478c9a48b7e_380_13799009402.mp4: 640x512 5.4ms\n",
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"video 1/1 (29/34) /home/ieemoo0337/projects/datasets/FP/8859015700168/8859015700168_20241017-175130_back_returnGood_5478c9a48b7e_380_13799009402.mp4: 640x512 5.3ms\n",
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"video 1/1 (30/34) /home/ieemoo0337/projects/datasets/FP/8859015700168/8859015700168_20241017-175130_back_returnGood_5478c9a48b7e_380_13799009402.mp4: 640x512 5.3ms\n",
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"video 1/1 (31/34) /home/ieemoo0337/projects/datasets/FP/8859015700168/8859015700168_20241017-175130_back_returnGood_5478c9a48b7e_380_13799009402.mp4: 640x512 5.4ms\n",
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"video 1/1 (32/34) /home/ieemoo0337/projects/datasets/FP/8859015700168/8859015700168_20241017-175130_back_returnGood_5478c9a48b7e_380_13799009402.mp4: 640x512 5.5ms\n",
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"video 1/1 (33/34) /home/ieemoo0337/projects/datasets/FP/8859015700168/8859015700168_20241017-175130_back_returnGood_5478c9a48b7e_380_13799009402.mp4: 640x512 5.5ms\n",
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"video 1/1 (34/34) /home/ieemoo0337/projects/datasets/FP/8859015700168/8859015700168_20241017-175130_back_returnGood_5478c9a48b7e_380_13799009402.mp4: 640x512 5.6ms\n",
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"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
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"\n",
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||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
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||
"Fusing layers... \n",
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||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
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||
]
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
|
||
"{'item1': {'Text': '巧克力脆皮布朗尼', 'Color': '棕色', 'Shape': '长方形', 'Material': '椰子', 'Category': '零食'}, 'item2': {'Text': '未知', 'Color': '绿色', 'Shape': '未知', 'Material': '未知', 'Category': '未知'}, 'is_Same': False}\n",
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||
"barcode: 9335390000547\n",
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||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/9335390000547/8852116806524.jpg\n",
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"video: /home/ieemoo0337/projects/datasets/FP/9335390000547/9335390000547_20241014-182017_back_addGood_5478c9a53bf4_1080_13799009402.mp4\n"
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]
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},
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"name": "stderr",
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"output_type": "stream",
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"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
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"video 1/1 (3/83) /home/ieemoo0337/projects/datasets/FP/9335390000547/9335390000547_20241014-182017_back_addGood_5478c9a53bf4_1080_13799009402.mp4: 640x512 5.5ms\n",
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"video 1/1 (4/83) /home/ieemoo0337/projects/datasets/FP/9335390000547/9335390000547_20241014-182017_back_addGood_5478c9a53bf4_1080_13799009402.mp4: 640x512 5.4ms\n",
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},
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{
|
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"name": "stdout",
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"output_type": "stream",
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"text": [
|
||
"load model resnet18 \n"
|
||
]
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},
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"video 1/1 (73/83) /home/ieemoo0337/projects/datasets/FP/9335390000547/9335390000547_20241014-182017_back_addGood_5478c9a53bf4_1080_13799009402.mp4: 640x512 5.5ms\n",
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"video 1/1 (74/83) /home/ieemoo0337/projects/datasets/FP/9335390000547/9335390000547_20241014-182017_back_addGood_5478c9a53bf4_1080_13799009402.mp4: 640x512 5.5ms\n",
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"video 1/1 (75/83) /home/ieemoo0337/projects/datasets/FP/9335390000547/9335390000547_20241014-182017_back_addGood_5478c9a53bf4_1080_13799009402.mp4: 640x512 5.5ms\n",
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"video 1/1 (76/83) /home/ieemoo0337/projects/datasets/FP/9335390000547/9335390000547_20241014-182017_back_addGood_5478c9a53bf4_1080_13799009402.mp4: 640x512 5.5ms\n",
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"video 1/1 (77/83) /home/ieemoo0337/projects/datasets/FP/9335390000547/9335390000547_20241014-182017_back_addGood_5478c9a53bf4_1080_13799009402.mp4: 640x512 5.6ms\n",
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"video 1/1 (78/83) /home/ieemoo0337/projects/datasets/FP/9335390000547/9335390000547_20241014-182017_back_addGood_5478c9a53bf4_1080_13799009402.mp4: 640x512 5.6ms\n",
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"video 1/1 (79/83) /home/ieemoo0337/projects/datasets/FP/9335390000547/9335390000547_20241014-182017_back_addGood_5478c9a53bf4_1080_13799009402.mp4: 640x512 5.5ms\n",
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"video 1/1 (80/83) /home/ieemoo0337/projects/datasets/FP/9335390000547/9335390000547_20241014-182017_back_addGood_5478c9a53bf4_1080_13799009402.mp4: 640x512 5.5ms\n",
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"video 1/1 (81/83) /home/ieemoo0337/projects/datasets/FP/9335390000547/9335390000547_20241014-182017_back_addGood_5478c9a53bf4_1080_13799009402.mp4: 640x512 5.5ms\n",
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"video 1/1 (82/83) /home/ieemoo0337/projects/datasets/FP/9335390000547/9335390000547_20241014-182017_back_addGood_5478c9a53bf4_1080_13799009402.mp4: 640x512 5.6ms\n",
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"video 1/1 (83/83) /home/ieemoo0337/projects/datasets/FP/9335390000547/9335390000547_20241014-182017_back_addGood_5478c9a53bf4_1080_13799009402.mp4: 640x512 5.5ms\n",
|
||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
|
||
"\n"
|
||
]
|
||
},
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||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"{'item1': {'Text': 'Original Flavour', 'Color': '绿色', 'Shape': '长方形', 'Material': '海苔', 'Category': '零食'}, 'item2': {'Text': '牛奶', 'Color': '白色', 'Shape': '圆柱形', 'Material': '塑料', 'Category': '乳制品'}, 'is_Same': False}\n",
|
||
"barcode: 9344949000143\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/9344949000143/9344949000143_20241019-112725_back_addGood_5478c9a49bfc_520_13773168720.mp4\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/9344949000143/8809713911410.jpg\n"
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||
]
|
||
},
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{
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||
"name": "stderr",
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||
"output_type": "stream",
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"text": [
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n",
|
||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
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||
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|
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},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
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||
"text": [
|
||
"load model resnet18 \n"
|
||
]
|
||
},
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||
"name": "stderr",
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||
"video 1/1 (56/57) /home/ieemoo0337/projects/datasets/FP/9344949000143/9344949000143_20241019-112725_back_addGood_5478c9a49bfc_520_13773168720.mp4: 640x512 5.3ms\n",
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"video 1/1 (57/57) /home/ieemoo0337/projects/datasets/FP/9344949000143/9344949000143_20241019-112725_back_addGood_5478c9a49bfc_520_13773168720.mp4: 640x512 5.3ms\n",
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||
"/home/ieemoo0337/projects/detecttracking/tracking/traclus.py:163: RuntimeWarning: divide by zero encountered in scalar divide\n",
|
||
" tan_theta0 = (shorter_slope - longer_slope) / (1 + shorter_slope * longer_slope)\n",
|
||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
|
||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"{'item1': {'Text': 'CAFFE LATTE', 'Color': '未知', 'Shape': '未知', 'Material': '未知', 'Category': '咖啡'}, 'item2': {'Text': 'Goat Milk Powder', 'Color': '未知', 'Shape': '未知', 'Material': '未知', 'Category': '乳制品'}, 'is_Same': False}\n",
|
||
"barcode: 9415007004585\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/9415007004585/9310072012599.jpg\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/9415007004585/9415007004585_20241020-113222_back_returnGood_5478c9a4db2c_260_13773168720.mp4\n"
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||
]
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{
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"name": "stderr",
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"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
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"video 1/1 (1/56) /home/ieemoo0337/projects/datasets/FP/9415007004585/9415007004585_20241020-113222_back_returnGood_5478c9a4db2c_260_13773168720.mp4: 640x512 6.3ms\n",
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{
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"name": "stdout",
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"load model resnet18 \n"
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"video 1/1 (55/56) /home/ieemoo0337/projects/datasets/FP/9415007004585/9415007004585_20241020-113222_back_returnGood_5478c9a4db2c_260_13773168720.mp4: 640x512 5.3ms\n",
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||
"/home/ieemoo0337/projects/detecttracking/tracking/traclus.py:163: RuntimeWarning: divide by zero encountered in scalar divide\n",
|
||
" tan_theta0 = (shorter_slope - longer_slope) / (1 + shorter_slope * longer_slope)\n",
|
||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
|
||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
|
||
]
|
||
},
|
||
{
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||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"{'item1': {'Text': 'OCSHP CAPSULE DETERGENT', 'Color': '白色', 'Shape': '长方体', 'Material': '塑料', 'Category': '洗衣胶囊'}, 'item2': {'Text': '洗衣粉', 'Color': '白色', 'Shape': '长方体', 'Material': '塑料', 'Category': '洗衣粉'}, 'is_Same': False}\n",
|
||
"barcode: 9311493002534\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/9311493002534/8886001012295.jpg\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/9311493002534/9311493002534_20241018-112147_back_addGood_5478c9a49bfc_595_18969520488.mp4\n"
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||
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|
||
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|
||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
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|
||
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|
||
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|
||
{
|
||
"name": "stdout",
|
||
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|
||
"text": [
|
||
"load model resnet18 \n"
|
||
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|
||
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"video 1/1 (97/99) /home/ieemoo0337/projects/datasets/FP/9311493002534/9311493002534_20241018-112147_back_addGood_5478c9a49bfc_595_18969520488.mp4: 640x512 6.1ms\n",
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"video 1/1 (98/99) /home/ieemoo0337/projects/datasets/FP/9311493002534/9311493002534_20241018-112147_back_addGood_5478c9a49bfc_595_18969520488.mp4: 640x512 6.1ms\n",
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"video 1/1 (99/99) /home/ieemoo0337/projects/datasets/FP/9311493002534/9311493002534_20241018-112147_back_addGood_5478c9a49bfc_595_18969520488.mp4: 640x512 6.1ms\n",
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"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
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"\n",
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||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
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||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
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||
"Fusing layers... \n",
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||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
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||
]
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"{'item1': {'Text': 'Danisa TRADITIONAL BUTTER COOKIES', 'Color': '蓝色', 'Shape': '圆形', 'Material': '纸盒', 'Category': '饼干'}, 'item2': {'Text': 'Bundaberg', 'Color': '粉色', 'Shape': '圆柱形', 'Material': '玻璃', 'Category': '饮料'}, 'is_Same': False}\n",
|
||
"barcode: 8994834005237\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/8994834005237/8934760211005.jpg\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/8994834005237/8994834005237_20241015-145820_back_addGood_5478c9a48b7e_100_13799009402.mp4\n"
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||
]
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||
},
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||
{
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"name": "stderr",
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||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
"video 1/1 (1/62) /home/ieemoo0337/projects/datasets/FP/8994834005237/8994834005237_20241015-145820_back_addGood_5478c9a48b7e_100_13799009402.mp4: 640x512 11.8ms\n",
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||
]
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},
|
||
{
|
||
"name": "stdout",
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||
"output_type": "stream",
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"text": [
|
||
"load model resnet18 \n"
|
||
]
|
||
},
|
||
{
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||
"name": "stderr",
|
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"video 1/1 (42/62) /home/ieemoo0337/projects/datasets/FP/8994834005237/8994834005237_20241015-145820_back_addGood_5478c9a48b7e_100_13799009402.mp4: 640x512 5.6ms\n",
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"video 1/1 (58/62) /home/ieemoo0337/projects/datasets/FP/8994834005237/8994834005237_20241015-145820_back_addGood_5478c9a48b7e_100_13799009402.mp4: 640x512 5.6ms\n",
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"video 1/1 (59/62) /home/ieemoo0337/projects/datasets/FP/8994834005237/8994834005237_20241015-145820_back_addGood_5478c9a48b7e_100_13799009402.mp4: 640x512 5.6ms\n",
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"video 1/1 (60/62) /home/ieemoo0337/projects/datasets/FP/8994834005237/8994834005237_20241015-145820_back_addGood_5478c9a48b7e_100_13799009402.mp4: 640x512 5.6ms\n",
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"video 1/1 (61/62) /home/ieemoo0337/projects/datasets/FP/8994834005237/8994834005237_20241015-145820_back_addGood_5478c9a48b7e_100_13799009402.mp4: 640x512 5.6ms\n",
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"video 1/1 (62/62) /home/ieemoo0337/projects/datasets/FP/8994834005237/8994834005237_20241015-145820_back_addGood_5478c9a48b7e_100_13799009402.mp4: 640x512 5.6ms\n",
|
||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
|
||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"{'item1': {'Text': 'Tipo Dream Egg Cookies', 'Color': '黄色', 'Shape': '长方形', 'Material': '饼干', 'Category': '零食'}, 'item2': {'Text': '未知', 'Color': '未知', 'Shape': '未知', 'Material': '未知', 'Category': '未知'}, 'is_Same': False}\n",
|
||
"barcode: 8888077108032\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/8888077108032/8888077108032_20241018-175036_back_returnGood_5478c9a4eb2c_115_18969520488.mp4\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/8888077108032/8859339800032.jpg\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n",
|
||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
"video 1/1 (1/76) /home/ieemoo0337/projects/datasets/FP/8888077108032/8888077108032_20241018-175036_back_returnGood_5478c9a4eb2c_115_18969520488.mp4: 640x512 7.3ms\n",
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"video 1/1 (2/76) /home/ieemoo0337/projects/datasets/FP/8888077108032/8888077108032_20241018-175036_back_returnGood_5478c9a4eb2c_115_18969520488.mp4: 640x512 5.4ms\n",
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||
"video 1/1 (3/76) /home/ieemoo0337/projects/datasets/FP/8888077108032/8888077108032_20241018-175036_back_returnGood_5478c9a4eb2c_115_18969520488.mp4: 640x512 5.4ms\n",
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||
"video 1/1 (4/76) /home/ieemoo0337/projects/datasets/FP/8888077108032/8888077108032_20241018-175036_back_returnGood_5478c9a4eb2c_115_18969520488.mp4: 640x512 5.4ms\n",
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||
"video 1/1 (5/76) /home/ieemoo0337/projects/datasets/FP/8888077108032/8888077108032_20241018-175036_back_returnGood_5478c9a4eb2c_115_18969520488.mp4: 640x512 5.5ms\n",
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"video 1/1 (6/76) /home/ieemoo0337/projects/datasets/FP/8888077108032/8888077108032_20241018-175036_back_returnGood_5478c9a4eb2c_115_18969520488.mp4: 640x512 5.5ms\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"load model resnet18 \n"
|
||
]
|
||
},
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||
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||
"/home/ieemoo0337/projects/detecttracking/tracking/traclus.py:163: RuntimeWarning: divide by zero encountered in scalar divide\n",
|
||
" tan_theta0 = (shorter_slope - longer_slope) / (1 + shorter_slope * longer_slope)\n",
|
||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
|
||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"{'item1': {'Text': '泰国经典茉莉香米', 'Color': '白色', 'Shape': '长方形', 'Material': '塑料', 'Category': '食品'}, 'item2': {'Text': '牛奶', 'Color': '白色', 'Shape': '长方形', 'Material': '纸', 'Category': '食品'}, 'is_Same': False}\n",
|
||
"barcode: 9421029082005\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/9421029082005/9421029082005_20241020-164235_back_returnGood_5478c9a48b8c_1035_18358205530.mp4\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/9421029082005/9351699000613.jpg\n"
|
||
]
|
||
},
|
||
{
|
||
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|
||
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||
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|
||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
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||
},
|
||
{
|
||
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|
||
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||
"text": [
|
||
"load model resnet18 \n"
|
||
]
|
||
},
|
||
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"video 1/1 (94/106) /home/ieemoo0337/projects/datasets/FP/9421029082005/9421029082005_20241020-164235_back_returnGood_5478c9a48b8c_1035_18358205530.mp4: 640x512 5.3ms\n",
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"video 1/1 (95/106) /home/ieemoo0337/projects/datasets/FP/9421029082005/9421029082005_20241020-164235_back_returnGood_5478c9a48b8c_1035_18358205530.mp4: 640x512 5.3ms\n",
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"video 1/1 (96/106) /home/ieemoo0337/projects/datasets/FP/9421029082005/9421029082005_20241020-164235_back_returnGood_5478c9a48b8c_1035_18358205530.mp4: 640x512 5.3ms\n",
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"video 1/1 (97/106) /home/ieemoo0337/projects/datasets/FP/9421029082005/9421029082005_20241020-164235_back_returnGood_5478c9a48b8c_1035_18358205530.mp4: 640x512 5.3ms\n",
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"video 1/1 (98/106) /home/ieemoo0337/projects/datasets/FP/9421029082005/9421029082005_20241020-164235_back_returnGood_5478c9a48b8c_1035_18358205530.mp4: 640x512 5.3ms\n",
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"video 1/1 (99/106) /home/ieemoo0337/projects/datasets/FP/9421029082005/9421029082005_20241020-164235_back_returnGood_5478c9a48b8c_1035_18358205530.mp4: 640x512 5.2ms\n",
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"video 1/1 (100/106) /home/ieemoo0337/projects/datasets/FP/9421029082005/9421029082005_20241020-164235_back_returnGood_5478c9a48b8c_1035_18358205530.mp4: 640x512 5.3ms\n",
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"video 1/1 (101/106) /home/ieemoo0337/projects/datasets/FP/9421029082005/9421029082005_20241020-164235_back_returnGood_5478c9a48b8c_1035_18358205530.mp4: 640x512 5.3ms\n",
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"video 1/1 (102/106) /home/ieemoo0337/projects/datasets/FP/9421029082005/9421029082005_20241020-164235_back_returnGood_5478c9a48b8c_1035_18358205530.mp4: 640x512 5.3ms\n",
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"video 1/1 (103/106) /home/ieemoo0337/projects/datasets/FP/9421029082005/9421029082005_20241020-164235_back_returnGood_5478c9a48b8c_1035_18358205530.mp4: 640x512 5.3ms\n",
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"video 1/1 (104/106) /home/ieemoo0337/projects/datasets/FP/9421029082005/9421029082005_20241020-164235_back_returnGood_5478c9a48b8c_1035_18358205530.mp4: 640x512 5.3ms\n",
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"video 1/1 (105/106) /home/ieemoo0337/projects/datasets/FP/9421029082005/9421029082005_20241020-164235_back_returnGood_5478c9a48b8c_1035_18358205530.mp4: 640x512 5.3ms\n",
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"video 1/1 (106/106) /home/ieemoo0337/projects/datasets/FP/9421029082005/9421029082005_20241020-164235_back_returnGood_5478c9a48b8c_1035_18358205530.mp4: 640x512 5.3ms\n",
|
||
"/home/ieemoo0337/projects/detecttracking/tracking/traclus.py:163: RuntimeWarning: divide by zero encountered in scalar divide\n",
|
||
" tan_theta0 = (shorter_slope - longer_slope) / (1 + shorter_slope * longer_slope)\n",
|
||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
|
||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"{'item1': {'Text': 'A2', 'Color': '蓝色', 'Shape': '长方形', 'Material': '纸箱', 'Category': '牛奶'}, 'item2': {'Text': '薄脆', 'Color': '蓝色', 'Shape': '长方形', 'Material': '纸箱', 'Category': '零食'}, 'is_Same': False}\n",
|
||
"barcode: 8993083932943\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/8993083932943/9346506003406.jpg\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/8993083932943/8993083932943_20241020-141339_back_addGood_5478c9a49bfc_5_13799009402.mp4\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
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||
"text": [
|
||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
"video 1/1 (1/56) /home/ieemoo0337/projects/datasets/FP/8993083932943/8993083932943_20241020-141339_back_addGood_5478c9a49bfc_5_13799009402.mp4: 640x512 6.7ms\n",
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||
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|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"load model resnet18 \n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
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||
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"video 1/1 (52/56) /home/ieemoo0337/projects/datasets/FP/8993083932943/8993083932943_20241020-141339_back_addGood_5478c9a49bfc_5_13799009402.mp4: 640x512 5.3ms\n",
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||
"video 1/1 (54/56) /home/ieemoo0337/projects/datasets/FP/8993083932943/8993083932943_20241020-141339_back_addGood_5478c9a49bfc_5_13799009402.mp4: 640x512 5.3ms\n",
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"video 1/1 (55/56) /home/ieemoo0337/projects/datasets/FP/8993083932943/8993083932943_20241020-141339_back_addGood_5478c9a49bfc_5_13799009402.mp4: 640x512 5.3ms\n",
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|
||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
|
||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
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||
"text": [
|
||
"{'item1': {'Text': 'Jersey Platinum Formulated Milk Powder for Active Middle-Aged People With Skim Milk Milk Protein Dietary Fibre Rich in Vitamins A, C, D & E', 'Color': '绿色', 'Shape': '圆柱形', 'Material': '金属', 'Category': '乳制品'}, 'item2': {'Text': '未知', 'Color': '未知', 'Shape': '未知', 'Material': '未知', 'Category': '未知'}, 'is_Same': False}\n",
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||
"barcode: 8934803028799\n",
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||
"video: /home/ieemoo0337/projects/datasets/FP/8934803028799/8934803028799_20241016-134224_back_addGood_5478c9a53bf4_140_13773168720.mp4\n",
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"goodsPic: /home/ieemoo0337/projects/datasets/FP/8934803028799/8850006304952.jpg\n"
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"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
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" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
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"load model resnet18 \n"
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"video 1/1 (71/75) /home/ieemoo0337/projects/datasets/FP/8934803028799/8934803028799_20241016-134224_back_addGood_5478c9a53bf4_140_13773168720.mp4: 640x512 5.3ms\n",
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"video 1/1 (72/75) /home/ieemoo0337/projects/datasets/FP/8934803028799/8934803028799_20241016-134224_back_addGood_5478c9a53bf4_140_13773168720.mp4: 640x512 5.3ms\n",
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"video 1/1 (73/75) /home/ieemoo0337/projects/datasets/FP/8934803028799/8934803028799_20241016-134224_back_addGood_5478c9a53bf4_140_13773168720.mp4: 640x512 5.4ms\n",
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"video 1/1 (74/75) /home/ieemoo0337/projects/datasets/FP/8934803028799/8934803028799_20241016-134224_back_addGood_5478c9a53bf4_140_13773168720.mp4: 640x512 5.3ms\n",
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"video 1/1 (75/75) /home/ieemoo0337/projects/datasets/FP/8934803028799/8934803028799_20241016-134224_back_addGood_5478c9a53bf4_140_13773168720.mp4: 640x512 5.3ms\n",
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||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
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||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
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||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
|
||
]
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||
},
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{
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"output_type": "stream",
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"text": [
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||
"{'item1': {'Text': 'Colgate', 'Color': '绿色', 'Shape': '长方形', 'Material': '塑料', 'Category': '漱口水'}, 'item2': {'Text': '辣条', 'Color': '蓝色', 'Shape': '长方形', 'Material': '塑料', 'Category': '零食'}, 'is_Same': False}\n",
|
||
"barcode: 9352266000616\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/9352266000616/9352266000616_20241017-142123_back_addGood_5478c9a4db2c_340_18133699824.mp4\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/9352266000616/9346506008777.jpg\n"
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||
]
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},
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{
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"name": "stderr",
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||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
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},
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||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
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"text": [
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||
"load model resnet18 \n"
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||
]
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||
},
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{
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"video 1/1 (81/86) /home/ieemoo0337/projects/datasets/FP/9352266000616/9352266000616_20241017-142123_back_addGood_5478c9a4db2c_340_18133699824.mp4: 640x512 5.5ms\n",
|
||
"video 1/1 (82/86) /home/ieemoo0337/projects/datasets/FP/9352266000616/9352266000616_20241017-142123_back_addGood_5478c9a4db2c_340_18133699824.mp4: 640x512 5.5ms\n",
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"video 1/1 (83/86) /home/ieemoo0337/projects/datasets/FP/9352266000616/9352266000616_20241017-142123_back_addGood_5478c9a4db2c_340_18133699824.mp4: 640x512 5.5ms\n",
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||
"video 1/1 (84/86) /home/ieemoo0337/projects/datasets/FP/9352266000616/9352266000616_20241017-142123_back_addGood_5478c9a4db2c_340_18133699824.mp4: 640x512 5.5ms\n",
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||
"video 1/1 (85/86) /home/ieemoo0337/projects/datasets/FP/9352266000616/9352266000616_20241017-142123_back_addGood_5478c9a4db2c_340_18133699824.mp4: 640x512 5.5ms\n",
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"video 1/1 (86/86) /home/ieemoo0337/projects/datasets/FP/9352266000616/9352266000616_20241017-142123_back_addGood_5478c9a4db2c_340_18133699824.mp4: 640x512 5.5ms\n",
|
||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
|
||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
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"output_type": "stream",
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"text": [
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"{'item1': {'Text': 'Jerseyjoy Acejoy SKIM Milk', 'Color': '白色', 'Shape': '圆柱形', 'Material': '塑料', 'Category': '乳制品'}, 'item2': {'Text': 'OCHP', 'Color': '蓝色', 'Shape': '长方形', 'Material': '塑料', 'Category': '容器'}, 'is_Same': False}\n",
|
||
"barcode: 9310072000282\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/9310072000282/9310072000282_20241019-142114_back_addGood_5478c9a49bfc_210_13773168720.mp4\n",
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||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/9310072000282/8850511311100.jpg\n"
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{
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||
"name": "stderr",
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||
"output_type": "stream",
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"text": [
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||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
"video 1/1 (1/55) /home/ieemoo0337/projects/datasets/FP/9310072000282/9310072000282_20241019-142114_back_addGood_5478c9a49bfc_210_13773168720.mp4: 640x512 6.4ms\n",
|
||
"video 1/1 (2/55) /home/ieemoo0337/projects/datasets/FP/9310072000282/9310072000282_20241019-142114_back_addGood_5478c9a49bfc_210_13773168720.mp4: 640x512 5.6ms\n",
|
||
"video 1/1 (3/55) /home/ieemoo0337/projects/datasets/FP/9310072000282/9310072000282_20241019-142114_back_addGood_5478c9a49bfc_210_13773168720.mp4: 640x512 5.4ms\n",
|
||
"video 1/1 (4/55) /home/ieemoo0337/projects/datasets/FP/9310072000282/9310072000282_20241019-142114_back_addGood_5478c9a49bfc_210_13773168720.mp4: 640x512 5.5ms\n",
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||
"video 1/1 (5/55) /home/ieemoo0337/projects/datasets/FP/9310072000282/9310072000282_20241019-142114_back_addGood_5478c9a49bfc_210_13773168720.mp4: 640x512 5.4ms\n",
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"video 1/1 (6/55) /home/ieemoo0337/projects/datasets/FP/9310072000282/9310072000282_20241019-142114_back_addGood_5478c9a49bfc_210_13773168720.mp4: 640x512 5.4ms\n"
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||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
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||
"load model resnet18 \n"
|
||
]
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||
},
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{
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"name": "stderr",
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"video 1/1 (32/55) /home/ieemoo0337/projects/datasets/FP/9310072000282/9310072000282_20241019-142114_back_addGood_5478c9a49bfc_210_13773168720.mp4: 640x512 5.5ms\n",
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"video 1/1 (33/55) /home/ieemoo0337/projects/datasets/FP/9310072000282/9310072000282_20241019-142114_back_addGood_5478c9a49bfc_210_13773168720.mp4: 640x512 5.5ms\n",
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"video 1/1 (41/55) /home/ieemoo0337/projects/datasets/FP/9310072000282/9310072000282_20241019-142114_back_addGood_5478c9a49bfc_210_13773168720.mp4: 640x512 5.5ms\n",
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"video 1/1 (45/55) /home/ieemoo0337/projects/datasets/FP/9310072000282/9310072000282_20241019-142114_back_addGood_5478c9a49bfc_210_13773168720.mp4: 640x512 5.4ms\n",
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"video 1/1 (46/55) /home/ieemoo0337/projects/datasets/FP/9310072000282/9310072000282_20241019-142114_back_addGood_5478c9a49bfc_210_13773168720.mp4: 640x512 5.4ms\n",
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"video 1/1 (49/55) /home/ieemoo0337/projects/datasets/FP/9310072000282/9310072000282_20241019-142114_back_addGood_5478c9a49bfc_210_13773168720.mp4: 640x512 5.4ms\n",
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"video 1/1 (51/55) /home/ieemoo0337/projects/datasets/FP/9310072000282/9310072000282_20241019-142114_back_addGood_5478c9a49bfc_210_13773168720.mp4: 640x512 5.4ms\n",
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||
"video 1/1 (52/55) /home/ieemoo0337/projects/datasets/FP/9310072000282/9310072000282_20241019-142114_back_addGood_5478c9a49bfc_210_13773168720.mp4: 640x512 5.4ms\n",
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||
"video 1/1 (53/55) /home/ieemoo0337/projects/datasets/FP/9310072000282/9310072000282_20241019-142114_back_addGood_5478c9a49bfc_210_13773168720.mp4: 640x512 5.4ms\n",
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||
"video 1/1 (54/55) /home/ieemoo0337/projects/datasets/FP/9310072000282/9310072000282_20241019-142114_back_addGood_5478c9a49bfc_210_13773168720.mp4: 640x512 5.5ms\n",
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||
"video 1/1 (55/55) /home/ieemoo0337/projects/datasets/FP/9310072000282/9310072000282_20241019-142114_back_addGood_5478c9a49bfc_210_13773168720.mp4: 640x512 5.4ms\n",
|
||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
|
||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"{'item1': {'Text': '露莎士 泰式甜辣酱', 'Color': '红色', 'Shape': '长方形', 'Material': '玻璃', 'Category': '调料'}, 'item2': {'Text': '露莎士 泰式甜辣酱', 'Color': '红色', 'Shape': '长方形', 'Material': '玻璃', 'Category': '调料'}, 'is_Same': True}\n",
|
||
"barcode: 9421903892119\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/9421903892119/8996001303474.jpg\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/9421903892119/9421903892119_20241015-120226_back_addGood_5478c9a48b7e_1060_13799009402.mp4\n"
|
||
]
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||
},
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||
{
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||
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||
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||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
"video 1/1 (1/57) /home/ieemoo0337/projects/datasets/FP/9421903892119/9421903892119_20241015-120226_back_addGood_5478c9a48b7e_1060_13799009402.mp4: 640x512 6.7ms\n",
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"video 1/1 (4/57) /home/ieemoo0337/projects/datasets/FP/9421903892119/9421903892119_20241015-120226_back_addGood_5478c9a48b7e_1060_13799009402.mp4: 640x512 5.2ms\n",
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{
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"name": "stdout",
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"load model resnet18 \n"
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]
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},
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||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
|
||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
|
||
]
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||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
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||
"text": [
|
||
"{'item1': {'Text': 'Danisa Traditional Butter Cookies', 'Color': '蓝色', 'Shape': '长方形', 'Material': '纸盒', 'Category': '饼干'}, 'item2': {'Text': '未知', 'Color': '绿色', 'Shape': '未知', 'Material': '塑料袋', 'Category': '蔬菜'}, 'is_Same': False}\n",
|
||
"barcode: 8859442800745\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/8859442800745/8859442800745_20241020-135303_back_returnGood_5478c9a49bfc_80_13799009402.mp4\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/8859442800745/9345521001817.jpg\n"
|
||
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||
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||
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||
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||
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||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
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|
||
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|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"load model resnet18 \n"
|
||
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|
||
},
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||
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||
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"video 1/1 (58/60) /home/ieemoo0337/projects/datasets/FP/8859442800745/8859442800745_20241020-135303_back_returnGood_5478c9a49bfc_80_13799009402.mp4: 640x512 5.3ms\n",
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"video 1/1 (59/60) /home/ieemoo0337/projects/datasets/FP/8859442800745/8859442800745_20241020-135303_back_returnGood_5478c9a49bfc_80_13799009402.mp4: 640x512 5.4ms\n",
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"video 1/1 (60/60) /home/ieemoo0337/projects/datasets/FP/8859442800745/8859442800745_20241020-135303_back_returnGood_5478c9a49bfc_80_13799009402.mp4: 640x512 5.3ms\n",
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"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
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"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
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||
]
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},
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||
{
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||
"name": "stdout",
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"output_type": "stream",
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||
"text": [
|
||
"{'item1': {'Text': 'GreenKosy', 'Color': '金色', 'Shape': '圆柱形', 'Material': '塑料', 'Category': '护发产品'}, 'item2': {'Text': '无', 'Color': '蓝色', 'Shape': '方形', 'Material': '塑料', 'Category': '购物车'}, 'is_Same': False}\n",
|
||
"barcode: 8851016000513\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/8851016000513/8850511321499.jpg\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/8851016000513/8851016000513_20241020-171543_back_addGood_5478c9a48b8c_75_18358205530.mp4\n"
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"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
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},
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||
{
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||
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||
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|
||
"load model resnet18 \n"
|
||
]
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||
},
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||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
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||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
|
||
]
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||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"{'item1': {'Text': 'ROZA', 'Color': '黑色', 'Shape': '长方形', 'Material': '塑料', 'Category': '调味品'}, 'item2': {'Text': '泰国风味豆芽', 'Color': '绿色', 'Shape': '长条形', 'Material': '塑料', 'Category': '蔬菜'}, 'is_Same': False}\n",
|
||
"barcode: 9417574001097\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/9417574001097/9417574001097_20241018-165605_back_addGood_5478c9a4eb2c_520_18969520488.mp4\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/9417574001097/9322316001108.jpg\n"
|
||
]
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||
},
|
||
{
|
||
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||
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|
||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
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||
},
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||
{
|
||
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||
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||
"text": [
|
||
"load model resnet18 \n"
|
||
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||
},
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||
{
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||
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||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
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||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
|
||
]
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||
},
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||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
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||
"text": [
|
||
"{'item1': {'Text': 'Lanolin Oil', 'Color': '白色', 'Shape': '圆柱形', 'Material': '塑料', 'Category': '护肤品'}, 'item2': {'Text': '未知', 'Color': '未知', 'Shape': '未知', 'Material': '未知', 'Category': '未知'}, 'is_Same': False}\n",
|
||
"barcode: 9311493002527\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/9311493002527/9345521003774.jpg\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/9311493002527/9311493002527_20241019-155854_back_addGood_5478c9a49bfc_595_13773168720.mp4\n"
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||
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||
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||
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||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
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||
},
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||
{
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||
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||
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||
"text": [
|
||
"load model resnet18 \n"
|
||
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||
},
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||
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||
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"video 1/1 (55/57) /home/ieemoo0337/projects/datasets/FP/9311493002527/9311493002527_20241019-155854_back_addGood_5478c9a49bfc_595_13773168720.mp4: 640x512 5.2ms\n",
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"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
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"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
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||
]
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||
},
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||
{
|
||
"name": "stdout",
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||
"output_type": "stream",
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"text": [
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||
"{'item1': {'Text': '实力解决头发问题\\n全新海盐净油系列\\n\\n净油除螨\\n水油平衡\\n顺滑发丝\\n深层洁净', 'Color': '蓝色', 'Shape': '长方形', 'Material': '塑料', 'Category': '洗发水'}, 'item2': {'Text': '未知', 'Color': '未知', 'Shape': '未知', 'Material': '未知', 'Category': '未知'}, 'is_Same': False}\n",
|
||
"barcode: 8809803536486\n",
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||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/8809803536486/9551010540006.jpg\n",
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||
"video: /home/ieemoo0337/projects/datasets/FP/8809803536486/8809803536486_20241016-114236_back_returnGood_5478c9a53bf4_235_13773168720.mp4\n"
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||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
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},
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{
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||
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||
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"text": [
|
||
"load model resnet18 \n"
|
||
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||
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||
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"/home/ieemoo0337/projects/detecttracking/tracking/traclus.py:163: RuntimeWarning: divide by zero encountered in scalar divide\n",
|
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" tan_theta0 = (shorter_slope - longer_slope) / (1 + shorter_slope * longer_slope)\n",
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"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
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"\n",
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||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
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||
]
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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||
"{'item1': {'Text': 'Tiny MICO', 'Color': '多色', 'Shape': '长方形', 'Material': '纸', 'Category': '饼干'}, 'item2': {'Text': '马卡龙综合口味夹心饼干', 'Color': '白色', 'Shape': '长方形', 'Material': '纸', 'Category': '饼干'}, 'is_Same': True}\n",
|
||
"barcode: 8850006304952\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/8850006304952/8850006304952_20241018-132002_back_returnGood_5478c9a48b8c_0_13799009402.mp4\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/8850006304952/8934803028799.jpg\n"
|
||
]
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||
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||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
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|
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||
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|
||
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||
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||
"text": [
|
||
"load model resnet18 \n"
|
||
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|
||
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||
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"video 1/1 (47/51) /home/ieemoo0337/projects/datasets/FP/8850006304952/8850006304952_20241018-132002_back_returnGood_5478c9a48b8c_0_13799009402.mp4: 640x512 5.2ms\n",
|
||
"video 1/1 (48/51) /home/ieemoo0337/projects/datasets/FP/8850006304952/8850006304952_20241018-132002_back_returnGood_5478c9a48b8c_0_13799009402.mp4: 640x512 5.3ms\n",
|
||
"video 1/1 (49/51) /home/ieemoo0337/projects/datasets/FP/8850006304952/8850006304952_20241018-132002_back_returnGood_5478c9a48b8c_0_13799009402.mp4: 640x512 5.3ms\n",
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||
"video 1/1 (50/51) /home/ieemoo0337/projects/datasets/FP/8850006304952/8850006304952_20241018-132002_back_returnGood_5478c9a48b8c_0_13799009402.mp4: 640x512 5.2ms\n",
|
||
"video 1/1 (51/51) /home/ieemoo0337/projects/datasets/FP/8850006304952/8850006304952_20241018-132002_back_returnGood_5478c9a48b8c_0_13799009402.mp4: 640x512 5.2ms\n",
|
||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
|
||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"{'item1': {'Text': 'Vchips', 'Color': '蓝色', 'Shape': '长方形', 'Material': '塑料', 'Category': '零食'}, 'item2': {'Text': '未知', 'Color': '绿色', 'Shape': '圆柱形', 'Material': '塑料', 'Category': '饮料'}, 'is_Same': False}\n",
|
||
"barcode: 8852116806524\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/8852116806524/9335390000547.jpg\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/8852116806524/8852116806524_20241015-144553_back_addGood_5478c9a48b7e_55_13799009402.mp4\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
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||
"text": [
|
||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
"video 1/1 (1/46) /home/ieemoo0337/projects/datasets/FP/8852116806524/8852116806524_20241015-144553_back_addGood_5478c9a48b7e_55_13799009402.mp4: 640x512 7.5ms\n",
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||
"video 1/1 (2/46) /home/ieemoo0337/projects/datasets/FP/8852116806524/8852116806524_20241015-144553_back_addGood_5478c9a48b7e_55_13799009402.mp4: 640x512 5.2ms\n",
|
||
"video 1/1 (3/46) /home/ieemoo0337/projects/datasets/FP/8852116806524/8852116806524_20241015-144553_back_addGood_5478c9a48b7e_55_13799009402.mp4: 640x512 5.2ms\n",
|
||
"video 1/1 (4/46) /home/ieemoo0337/projects/datasets/FP/8852116806524/8852116806524_20241015-144553_back_addGood_5478c9a48b7e_55_13799009402.mp4: 640x512 5.2ms\n",
|
||
"video 1/1 (5/46) /home/ieemoo0337/projects/datasets/FP/8852116806524/8852116806524_20241015-144553_back_addGood_5478c9a48b7e_55_13799009402.mp4: 640x512 5.2ms\n",
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||
"video 1/1 (6/46) /home/ieemoo0337/projects/datasets/FP/8852116806524/8852116806524_20241015-144553_back_addGood_5478c9a48b7e_55_13799009402.mp4: 640x512 5.2ms\n",
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||
"video 1/1 (7/46) /home/ieemoo0337/projects/datasets/FP/8852116806524/8852116806524_20241015-144553_back_addGood_5478c9a48b7e_55_13799009402.mp4: 640x512 5.2ms\n",
|
||
"video 1/1 (8/46) /home/ieemoo0337/projects/datasets/FP/8852116806524/8852116806524_20241015-144553_back_addGood_5478c9a48b7e_55_13799009402.mp4: 640x512 5.2ms\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"load model resnet18 \n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
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"video 1/1 (10/46) /home/ieemoo0337/projects/datasets/FP/8852116806524/8852116806524_20241015-144553_back_addGood_5478c9a48b7e_55_13799009402.mp4: 640x512 5.2ms\n",
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"video 1/1 (11/46) /home/ieemoo0337/projects/datasets/FP/8852116806524/8852116806524_20241015-144553_back_addGood_5478c9a48b7e_55_13799009402.mp4: 640x512 5.3ms\n",
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"video 1/1 (19/46) /home/ieemoo0337/projects/datasets/FP/8852116806524/8852116806524_20241015-144553_back_addGood_5478c9a48b7e_55_13799009402.mp4: 640x512 5.1ms\n",
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"video 1/1 (20/46) /home/ieemoo0337/projects/datasets/FP/8852116806524/8852116806524_20241015-144553_back_addGood_5478c9a48b7e_55_13799009402.mp4: 640x512 5.2ms\n",
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"video 1/1 (21/46) /home/ieemoo0337/projects/datasets/FP/8852116806524/8852116806524_20241015-144553_back_addGood_5478c9a48b7e_55_13799009402.mp4: 640x512 5.2ms\n",
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"video 1/1 (22/46) /home/ieemoo0337/projects/datasets/FP/8852116806524/8852116806524_20241015-144553_back_addGood_5478c9a48b7e_55_13799009402.mp4: 640x512 5.2ms\n",
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"video 1/1 (23/46) /home/ieemoo0337/projects/datasets/FP/8852116806524/8852116806524_20241015-144553_back_addGood_5478c9a48b7e_55_13799009402.mp4: 640x512 5.2ms\n",
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"video 1/1 (24/46) /home/ieemoo0337/projects/datasets/FP/8852116806524/8852116806524_20241015-144553_back_addGood_5478c9a48b7e_55_13799009402.mp4: 640x512 5.2ms\n",
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||
"video 1/1 (25/46) /home/ieemoo0337/projects/datasets/FP/8852116806524/8852116806524_20241015-144553_back_addGood_5478c9a48b7e_55_13799009402.mp4: 640x512 5.2ms\n",
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"video 1/1 (26/46) /home/ieemoo0337/projects/datasets/FP/8852116806524/8852116806524_20241015-144553_back_addGood_5478c9a48b7e_55_13799009402.mp4: 640x512 5.1ms\n",
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"video 1/1 (27/46) /home/ieemoo0337/projects/datasets/FP/8852116806524/8852116806524_20241015-144553_back_addGood_5478c9a48b7e_55_13799009402.mp4: 640x512 5.2ms\n",
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"video 1/1 (28/46) /home/ieemoo0337/projects/datasets/FP/8852116806524/8852116806524_20241015-144553_back_addGood_5478c9a48b7e_55_13799009402.mp4: 640x512 5.2ms\n",
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"video 1/1 (29/46) /home/ieemoo0337/projects/datasets/FP/8852116806524/8852116806524_20241015-144553_back_addGood_5478c9a48b7e_55_13799009402.mp4: 640x512 5.1ms\n",
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"video 1/1 (30/46) /home/ieemoo0337/projects/datasets/FP/8852116806524/8852116806524_20241015-144553_back_addGood_5478c9a48b7e_55_13799009402.mp4: 640x512 5.2ms\n",
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"video 1/1 (31/46) /home/ieemoo0337/projects/datasets/FP/8852116806524/8852116806524_20241015-144553_back_addGood_5478c9a48b7e_55_13799009402.mp4: 640x512 5.2ms\n",
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"video 1/1 (32/46) /home/ieemoo0337/projects/datasets/FP/8852116806524/8852116806524_20241015-144553_back_addGood_5478c9a48b7e_55_13799009402.mp4: 640x512 5.2ms\n",
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"video 1/1 (33/46) /home/ieemoo0337/projects/datasets/FP/8852116806524/8852116806524_20241015-144553_back_addGood_5478c9a48b7e_55_13799009402.mp4: 640x512 5.2ms\n",
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"video 1/1 (34/46) /home/ieemoo0337/projects/datasets/FP/8852116806524/8852116806524_20241015-144553_back_addGood_5478c9a48b7e_55_13799009402.mp4: 640x512 5.2ms\n",
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"video 1/1 (36/46) /home/ieemoo0337/projects/datasets/FP/8852116806524/8852116806524_20241015-144553_back_addGood_5478c9a48b7e_55_13799009402.mp4: 640x512 5.2ms\n",
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||
"video 1/1 (37/46) /home/ieemoo0337/projects/datasets/FP/8852116806524/8852116806524_20241015-144553_back_addGood_5478c9a48b7e_55_13799009402.mp4: 640x512 5.2ms\n",
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"video 1/1 (38/46) /home/ieemoo0337/projects/datasets/FP/8852116806524/8852116806524_20241015-144553_back_addGood_5478c9a48b7e_55_13799009402.mp4: 640x512 5.2ms\n",
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"video 1/1 (39/46) /home/ieemoo0337/projects/datasets/FP/8852116806524/8852116806524_20241015-144553_back_addGood_5478c9a48b7e_55_13799009402.mp4: 640x512 5.2ms\n",
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"video 1/1 (40/46) /home/ieemoo0337/projects/datasets/FP/8852116806524/8852116806524_20241015-144553_back_addGood_5478c9a48b7e_55_13799009402.mp4: 640x512 5.2ms\n",
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||
"video 1/1 (41/46) /home/ieemoo0337/projects/datasets/FP/8852116806524/8852116806524_20241015-144553_back_addGood_5478c9a48b7e_55_13799009402.mp4: 640x512 5.2ms\n",
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||
"video 1/1 (42/46) /home/ieemoo0337/projects/datasets/FP/8852116806524/8852116806524_20241015-144553_back_addGood_5478c9a48b7e_55_13799009402.mp4: 640x512 5.2ms\n",
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||
"video 1/1 (43/46) /home/ieemoo0337/projects/datasets/FP/8852116806524/8852116806524_20241015-144553_back_addGood_5478c9a48b7e_55_13799009402.mp4: 640x512 5.2ms\n",
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||
"video 1/1 (44/46) /home/ieemoo0337/projects/datasets/FP/8852116806524/8852116806524_20241015-144553_back_addGood_5478c9a48b7e_55_13799009402.mp4: 640x512 5.2ms\n",
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||
"video 1/1 (45/46) /home/ieemoo0337/projects/datasets/FP/8852116806524/8852116806524_20241015-144553_back_addGood_5478c9a48b7e_55_13799009402.mp4: 640x512 5.2ms\n",
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||
"video 1/1 (46/46) /home/ieemoo0337/projects/datasets/FP/8852116806524/8852116806524_20241015-144553_back_addGood_5478c9a48b7e_55_13799009402.mp4: 640x512 5.2ms\n",
|
||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
|
||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"{'item1': {'Text': 'a2 Milk full cream fresh milk', 'Color': '白色', 'Shape': '圆柱形', 'Material': '塑料', 'Category': '乳制品'}, 'item2': {'Text': 'Nori', 'Color': '绿色', 'Shape': '不规则形状', 'Material': '海苔', 'Category': '零食'}, 'is_Same': False}\n",
|
||
"barcode: 8859339800032\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/8859339800032/8888077108032.jpg\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4\n"
|
||
]
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||
},
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||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
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||
"text": [
|
||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
"video 1/1 (1/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 6.4ms\n",
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"video 1/1 (2/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.3ms\n",
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||
"video 1/1 (3/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.3ms\n",
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||
"video 1/1 (4/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.3ms\n",
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"video 1/1 (5/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.3ms\n"
|
||
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|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"load model resnet18 \n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
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"video 1/1 (9/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.4ms\n",
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"video 1/1 (11/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.4ms\n",
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"video 1/1 (13/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.4ms\n",
|
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"video 1/1 (14/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.3ms\n",
|
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"video 1/1 (15/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.3ms\n",
|
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"video 1/1 (16/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.5ms\n",
|
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"video 1/1 (17/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.3ms\n",
|
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"video 1/1 (18/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.3ms\n",
|
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"video 1/1 (19/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.3ms\n",
|
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"video 1/1 (20/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.3ms\n",
|
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"video 1/1 (21/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.3ms\n",
|
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"video 1/1 (22/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.2ms\n",
|
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"video 1/1 (23/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.3ms\n",
|
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"video 1/1 (24/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.3ms\n",
|
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"video 1/1 (25/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.3ms\n",
|
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"video 1/1 (26/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.3ms\n",
|
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"video 1/1 (27/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.2ms\n",
|
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"video 1/1 (28/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.2ms\n",
|
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"video 1/1 (29/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.3ms\n",
|
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"video 1/1 (30/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.3ms\n",
|
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"video 1/1 (31/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.2ms\n",
|
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"video 1/1 (32/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.3ms\n",
|
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"video 1/1 (33/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.3ms\n",
|
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"video 1/1 (34/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.3ms\n",
|
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"video 1/1 (35/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.3ms\n",
|
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"video 1/1 (36/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.3ms\n",
|
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"video 1/1 (37/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.3ms\n",
|
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"video 1/1 (38/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.5ms\n",
|
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"video 1/1 (39/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.3ms\n",
|
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"video 1/1 (40/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.2ms\n",
|
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"video 1/1 (41/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.2ms\n",
|
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"video 1/1 (42/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.2ms\n",
|
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"video 1/1 (43/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.4ms\n",
|
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"video 1/1 (44/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.4ms\n",
|
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"video 1/1 (45/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.3ms\n",
|
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"video 1/1 (46/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.2ms\n",
|
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"video 1/1 (47/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.3ms\n",
|
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"video 1/1 (48/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.2ms\n",
|
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"video 1/1 (49/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.2ms\n",
|
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"video 1/1 (50/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.2ms\n",
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"video 1/1 (51/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.3ms\n",
|
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"video 1/1 (52/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.2ms\n",
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"video 1/1 (53/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.2ms\n",
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"video 1/1 (54/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.3ms\n",
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"video 1/1 (55/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.2ms\n",
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"video 1/1 (56/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.3ms\n",
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"video 1/1 (57/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.3ms\n",
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"video 1/1 (58/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.4ms\n",
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"video 1/1 (59/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.2ms\n",
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"video 1/1 (60/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.2ms\n",
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"video 1/1 (61/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.4ms\n",
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"video 1/1 (62/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.2ms\n",
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"video 1/1 (63/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.4ms\n",
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"video 1/1 (64/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.3ms\n",
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"video 1/1 (65/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.3ms\n",
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"video 1/1 (66/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.3ms\n",
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"video 1/1 (67/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.3ms\n",
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"video 1/1 (68/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.2ms\n",
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"video 1/1 (69/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.3ms\n",
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"video 1/1 (70/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.6ms\n",
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"video 1/1 (71/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.3ms\n",
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"video 1/1 (72/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.3ms\n",
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"video 1/1 (73/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.6ms\n",
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"video 1/1 (74/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.4ms\n",
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"video 1/1 (75/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.4ms\n",
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"video 1/1 (76/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.6ms\n",
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"video 1/1 (77/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.4ms\n",
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"video 1/1 (78/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.4ms\n",
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"video 1/1 (79/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.4ms\n",
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"video 1/1 (80/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.4ms\n",
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"video 1/1 (81/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.4ms\n",
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"video 1/1 (82/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.4ms\n",
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"video 1/1 (83/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.4ms\n",
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"video 1/1 (84/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.4ms\n",
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"video 1/1 (85/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.4ms\n",
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"video 1/1 (86/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.4ms\n",
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"video 1/1 (87/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.4ms\n",
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"video 1/1 (88/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.4ms\n",
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"video 1/1 (89/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.4ms\n",
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"video 1/1 (90/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.5ms\n",
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"video 1/1 (91/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.4ms\n",
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"video 1/1 (92/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.6ms\n",
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"video 1/1 (93/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.6ms\n",
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"video 1/1 (94/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.4ms\n",
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"video 1/1 (95/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.4ms\n",
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"video 1/1 (96/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.5ms\n",
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"video 1/1 (97/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.4ms\n",
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"video 1/1 (98/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.4ms\n",
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"video 1/1 (99/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.6ms\n",
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"video 1/1 (100/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.4ms\n",
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"video 1/1 (101/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.5ms\n",
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"video 1/1 (102/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.5ms\n",
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"video 1/1 (103/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.4ms\n",
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"video 1/1 (172/174) /home/ieemoo0337/projects/datasets/FP/8859339800032/8859339800032_20241019-153648_back_returnGood_5478c9a53be2_5075_14785332147.mp4: 640x512 5.4ms\n",
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||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
|
||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
|
||
]
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||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"{'item1': {'Text': 'HELLO PANDA', 'Color': '蓝色', 'Shape': '长方形', 'Material': '纸', 'Category': '零食'}, 'item2': {'Text': '熊', 'Color': '红色', 'Shape': '长方形', 'Material': '塑料', 'Category': '食品'}, 'is_Same': False}\n",
|
||
"barcode: 9351699000613\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/9351699000613/9421029082005.jpg\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/9351699000613/9351699000613_20241019-161549_back_returnGood_5478c9a53be2_5_14785332147.mp4\n"
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||
]
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||
},
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||
{
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||
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||
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||
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|
||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
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||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
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||
"text": [
|
||
"load model resnet18 \n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
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"text": [
|
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"video 1/1 (115/117) /home/ieemoo0337/projects/datasets/FP/9351699000613/9351699000613_20241019-161549_back_returnGood_5478c9a53be2_5_14785332147.mp4: 640x512 5.4ms\n",
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"video 1/1 (116/117) /home/ieemoo0337/projects/datasets/FP/9351699000613/9351699000613_20241019-161549_back_returnGood_5478c9a53be2_5_14785332147.mp4: 640x512 5.4ms\n",
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"video 1/1 (117/117) /home/ieemoo0337/projects/datasets/FP/9351699000613/9351699000613_20241019-161549_back_returnGood_5478c9a53be2_5_14785332147.mp4: 640x512 5.4ms\n",
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"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
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"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
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||
]
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
|
||
"{'item1': {'Text': 'New Zealand Farm Fresh Milk Powder', 'Color': '灰色', 'Shape': '长方形', 'Material': '塑料', 'Category': '乳制品'}, 'item2': {'Text': 'Theland A2 New Zealand Pure Milk', 'Color': '蓝色', 'Shape': '长方形', 'Material': '纸箱', 'Category': '乳制品'}, 'is_Same': False}\n",
|
||
"barcode: 9555030108659\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/9555030108659/8996001356319.jpg\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/9555030108659/9555030108659_20241019-135122_back_returnGood_5478c9a49bfc_10_13773168720.mp4\n"
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||
]
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},
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{
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"name": "stderr",
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"output_type": "stream",
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|
||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
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|
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]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
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||
"text": [
|
||
"load model resnet18 \n"
|
||
]
|
||
},
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{
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||
"name": "stderr",
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"/home/ieemoo0337/projects/detecttracking/tracking/traclus.py:163: RuntimeWarning: divide by zero encountered in scalar divide\n",
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||
" tan_theta0 = (shorter_slope - longer_slope) / (1 + shorter_slope * longer_slope)\n",
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||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
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"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
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||
]
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||
},
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{
|
||
"name": "stdout",
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"output_type": "stream",
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"text": [
|
||
"{'item1': {'Text': '爱时乐 AStick 香草牛奶味威化卷心酥', 'Color': '蓝色', 'Shape': '圆柱形', 'Material': '纸盒', 'Category': '零食'}, 'item2': {'Text': '大马哈鱼肠肉肠片蜜味', 'Color': '绿色', 'Shape': '长方形', 'Material': '塑料袋', 'Category': '肉制品'}, 'is_Same': False}\n",
|
||
"barcode: 6975573940135\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/6975573940135/6975573940135_20241014-111702_back_returnGood_5478c9a4db2c_1120_13586533739.mp4\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/6975573940135/9344949000143.jpg\n"
|
||
]
|
||
},
|
||
{
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||
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|
||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
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},
|
||
{
|
||
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|
||
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||
"text": [
|
||
"load model resnet18 \n"
|
||
]
|
||
},
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||
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||
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"/home/ieemoo0337/projects/detecttracking/tracking/traclus.py:163: RuntimeWarning: divide by zero encountered in scalar divide\n",
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||
" tan_theta0 = (shorter_slope - longer_slope) / (1 + shorter_slope * longer_slope)\n",
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||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
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||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
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||
"Fusing layers... \n",
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||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
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||
]
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||
},
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||
{
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||
"name": "stdout",
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||
"output_type": "stream",
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||
"text": [
|
||
"{'item1': {'Text': 'Maxigenes Goat Milk Powder', 'Color': '白色', 'Shape': '圆柱形', 'Material': '塑料', 'Category': '乳制品'}, 'item2': {'Text': '食品用', 'Color': '绿色', 'Shape': '长方形', 'Material': '塑料', 'Category': '清洁用品'}, 'is_Same': False}\n",
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||
"barcode: 8859015703756\n",
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||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/8859015703756/9350013003057.jpg\n",
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||
"video: /home/ieemoo0337/projects/datasets/FP/8859015703756/8859015703756_20241017-112636_back_returnGood_5478c9a48c3e_305_13586533739.mp4\n"
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]
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},
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"name": "stderr",
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"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
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"video 1/1 (1/58) /home/ieemoo0337/projects/datasets/FP/8859015703756/8859015703756_20241017-112636_back_returnGood_5478c9a48c3e_305_13586533739.mp4: 640x512 6.6ms\n",
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"load model resnet18 \n"
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]
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},
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"video 1/1 (56/58) /home/ieemoo0337/projects/datasets/FP/8859015703756/8859015703756_20241017-112636_back_returnGood_5478c9a48c3e_305_13586533739.mp4: 640x512 5.3ms\n",
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"video 1/1 (57/58) /home/ieemoo0337/projects/datasets/FP/8859015703756/8859015703756_20241017-112636_back_returnGood_5478c9a48c3e_305_13586533739.mp4: 640x512 5.2ms\n",
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"video 1/1 (58/58) /home/ieemoo0337/projects/datasets/FP/8859015703756/8859015703756_20241017-112636_back_returnGood_5478c9a48c3e_305_13586533739.mp4: 640x512 5.2ms\n",
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||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
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||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
|
||
]
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||
},
|
||
{
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||
"name": "stdout",
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"output_type": "stream",
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"text": [
|
||
"Error processing 8859015703756: unterminated string literal (detected at line 1) (<unknown>, line 1)\n",
|
||
"barcode: 9322316001108\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/9322316001108/9417574001097.jpg\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/9322316001108/9322316001108_20241016-151528_back_addGood_5478c9a48c3e_5_13799009402.mp4\n"
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||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
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"video 1/1 (1/45) /home/ieemoo0337/projects/datasets/FP/9322316001108/9322316001108_20241016-151528_back_addGood_5478c9a48c3e_5_13799009402.mp4: 640x512 6.4ms\n",
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||
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},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
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||
"text": [
|
||
"load model resnet18 \n"
|
||
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||
},
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"video 1/1 (16/45) /home/ieemoo0337/projects/datasets/FP/9322316001108/9322316001108_20241016-151528_back_addGood_5478c9a48c3e_5_13799009402.mp4: 640x512 5.4ms\n",
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"video 1/1 (17/45) /home/ieemoo0337/projects/datasets/FP/9322316001108/9322316001108_20241016-151528_back_addGood_5478c9a48c3e_5_13799009402.mp4: 640x512 5.4ms\n",
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"video 1/1 (18/45) /home/ieemoo0337/projects/datasets/FP/9322316001108/9322316001108_20241016-151528_back_addGood_5478c9a48c3e_5_13799009402.mp4: 640x512 5.4ms\n",
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"video 1/1 (19/45) /home/ieemoo0337/projects/datasets/FP/9322316001108/9322316001108_20241016-151528_back_addGood_5478c9a48c3e_5_13799009402.mp4: 640x512 5.4ms\n",
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"video 1/1 (20/45) /home/ieemoo0337/projects/datasets/FP/9322316001108/9322316001108_20241016-151528_back_addGood_5478c9a48c3e_5_13799009402.mp4: 640x512 5.4ms\n",
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"video 1/1 (22/45) /home/ieemoo0337/projects/datasets/FP/9322316001108/9322316001108_20241016-151528_back_addGood_5478c9a48c3e_5_13799009402.mp4: 640x512 5.4ms\n",
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"video 1/1 (23/45) /home/ieemoo0337/projects/datasets/FP/9322316001108/9322316001108_20241016-151528_back_addGood_5478c9a48c3e_5_13799009402.mp4: 640x512 5.4ms\n",
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"video 1/1 (24/45) /home/ieemoo0337/projects/datasets/FP/9322316001108/9322316001108_20241016-151528_back_addGood_5478c9a48c3e_5_13799009402.mp4: 640x512 5.4ms\n",
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"video 1/1 (25/45) /home/ieemoo0337/projects/datasets/FP/9322316001108/9322316001108_20241016-151528_back_addGood_5478c9a48c3e_5_13799009402.mp4: 640x512 5.4ms\n",
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"video 1/1 (30/45) /home/ieemoo0337/projects/datasets/FP/9322316001108/9322316001108_20241016-151528_back_addGood_5478c9a48c3e_5_13799009402.mp4: 640x512 5.3ms\n",
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"video 1/1 (35/45) /home/ieemoo0337/projects/datasets/FP/9322316001108/9322316001108_20241016-151528_back_addGood_5478c9a48c3e_5_13799009402.mp4: 640x512 5.4ms\n",
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"video 1/1 (36/45) /home/ieemoo0337/projects/datasets/FP/9322316001108/9322316001108_20241016-151528_back_addGood_5478c9a48c3e_5_13799009402.mp4: 640x512 5.4ms\n",
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"video 1/1 (37/45) /home/ieemoo0337/projects/datasets/FP/9322316001108/9322316001108_20241016-151528_back_addGood_5478c9a48c3e_5_13799009402.mp4: 640x512 5.3ms\n",
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"video 1/1 (41/45) /home/ieemoo0337/projects/datasets/FP/9322316001108/9322316001108_20241016-151528_back_addGood_5478c9a48c3e_5_13799009402.mp4: 640x512 5.4ms\n",
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"video 1/1 (42/45) /home/ieemoo0337/projects/datasets/FP/9322316001108/9322316001108_20241016-151528_back_addGood_5478c9a48c3e_5_13799009402.mp4: 640x512 5.3ms\n",
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"video 1/1 (43/45) /home/ieemoo0337/projects/datasets/FP/9322316001108/9322316001108_20241016-151528_back_addGood_5478c9a48c3e_5_13799009402.mp4: 640x512 5.3ms\n",
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"video 1/1 (44/45) /home/ieemoo0337/projects/datasets/FP/9322316001108/9322316001108_20241016-151528_back_addGood_5478c9a48c3e_5_13799009402.mp4: 640x512 5.5ms\n",
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"video 1/1 (45/45) /home/ieemoo0337/projects/datasets/FP/9322316001108/9322316001108_20241016-151528_back_addGood_5478c9a48c3e_5_13799009402.mp4: 640x512 5.4ms\n",
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"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
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"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
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||
]
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},
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||
{
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"name": "stdout",
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"output_type": "stream",
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||
"text": [
|
||
"Error processing 9322316001108: invalid character '，' (U+FF0C) (<unknown>, line 1)\n",
|
||
"barcode: 8996001356319\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/8996001356319/9555030108659.jpg\n",
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||
"video: /home/ieemoo0337/projects/datasets/FP/8996001356319/8996001356319_20241019-143413_back_returnGood_5478c9a49bfc_235_13773168720.mp4\n"
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]
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},
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"name": "stderr",
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"output_type": "stream",
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||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
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||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
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||
"text": [
|
||
"load model resnet18 \n"
|
||
]
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||
},
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||
{
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||
"name": "stderr",
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"output_type": "stream",
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"video 1/1 (46/52) /home/ieemoo0337/projects/datasets/FP/8996001356319/8996001356319_20241019-143413_back_returnGood_5478c9a49bfc_235_13773168720.mp4: 640x512 5.3ms\n",
|
||
"video 1/1 (47/52) /home/ieemoo0337/projects/datasets/FP/8996001356319/8996001356319_20241019-143413_back_returnGood_5478c9a49bfc_235_13773168720.mp4: 640x512 5.4ms\n",
|
||
"video 1/1 (48/52) /home/ieemoo0337/projects/datasets/FP/8996001356319/8996001356319_20241019-143413_back_returnGood_5478c9a49bfc_235_13773168720.mp4: 640x512 5.3ms\n",
|
||
"video 1/1 (49/52) /home/ieemoo0337/projects/datasets/FP/8996001356319/8996001356319_20241019-143413_back_returnGood_5478c9a49bfc_235_13773168720.mp4: 640x512 5.3ms\n",
|
||
"video 1/1 (50/52) /home/ieemoo0337/projects/datasets/FP/8996001356319/8996001356319_20241019-143413_back_returnGood_5478c9a49bfc_235_13773168720.mp4: 640x512 5.3ms\n",
|
||
"video 1/1 (51/52) /home/ieemoo0337/projects/datasets/FP/8996001356319/8996001356319_20241019-143413_back_returnGood_5478c9a49bfc_235_13773168720.mp4: 640x512 5.4ms\n",
|
||
"video 1/1 (52/52) /home/ieemoo0337/projects/datasets/FP/8996001356319/8996001356319_20241019-143413_back_returnGood_5478c9a49bfc_235_13773168720.mp4: 640x512 5.4ms\n",
|
||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
|
||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"{'item1': {'Text': 'HIMALAYA VAJOMBA HONEY LIME MINTS ENRICHED WITH VITAMIN C', 'Color': '绿色', 'Shape': '长方形', 'Material': '塑料', 'Category': '口香糖'}, 'item2': {'Text': 'Asi', 'Color': '蓝色', 'Shape': '圆柱形', 'Material': '金属', 'Category': '罐头'}, 'is_Same': False}\n",
|
||
"barcode: 9345521001145\n",
|
||
"goodsPic: /home/ieemoo0337/projects/datasets/FP/9345521001145/9346506008760.jpg\n",
|
||
"video: /home/ieemoo0337/projects/datasets/FP/9345521001145/9345521001145_20241017-112028_back_addGood_5478c9a4db2c_815_18133699824.mp4\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
"video 1/1 (1/39) /home/ieemoo0337/projects/datasets/FP/9345521001145/9345521001145_20241017-112028_back_addGood_5478c9a4db2c_815_18133699824.mp4: 640x512 6.2ms\n",
|
||
"video 1/1 (2/39) /home/ieemoo0337/projects/datasets/FP/9345521001145/9345521001145_20241017-112028_back_addGood_5478c9a4db2c_815_18133699824.mp4: 640x512 5.3ms\n",
|
||
"video 1/1 (3/39) /home/ieemoo0337/projects/datasets/FP/9345521001145/9345521001145_20241017-112028_back_addGood_5478c9a4db2c_815_18133699824.mp4: 640x512 5.2ms\n",
|
||
"video 1/1 (4/39) /home/ieemoo0337/projects/datasets/FP/9345521001145/9345521001145_20241017-112028_back_addGood_5478c9a4db2c_815_18133699824.mp4: 640x512 5.3ms\n",
|
||
"video 1/1 (5/39) /home/ieemoo0337/projects/datasets/FP/9345521001145/9345521001145_20241017-112028_back_addGood_5478c9a4db2c_815_18133699824.mp4: 640x512 5.3ms\n",
|
||
"video 1/1 (6/39) /home/ieemoo0337/projects/datasets/FP/9345521001145/9345521001145_20241017-112028_back_addGood_5478c9a4db2c_815_18133699824.mp4: 640x512 5.3ms\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"load model resnet18 \n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
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||
"text": [
|
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"video 1/1 (7/39) /home/ieemoo0337/projects/datasets/FP/9345521001145/9345521001145_20241017-112028_back_addGood_5478c9a4db2c_815_18133699824.mp4: 640x512 5.3ms\n",
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"video 1/1 (8/39) /home/ieemoo0337/projects/datasets/FP/9345521001145/9345521001145_20241017-112028_back_addGood_5478c9a4db2c_815_18133699824.mp4: 640x512 5.3ms\n",
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"video 1/1 (9/39) /home/ieemoo0337/projects/datasets/FP/9345521001145/9345521001145_20241017-112028_back_addGood_5478c9a4db2c_815_18133699824.mp4: 640x512 5.3ms\n",
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"video 1/1 (10/39) /home/ieemoo0337/projects/datasets/FP/9345521001145/9345521001145_20241017-112028_back_addGood_5478c9a4db2c_815_18133699824.mp4: 640x512 5.4ms\n",
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"video 1/1 (21/39) /home/ieemoo0337/projects/datasets/FP/9345521001145/9345521001145_20241017-112028_back_addGood_5478c9a4db2c_815_18133699824.mp4: 640x512 5.3ms\n",
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"video 1/1 (24/39) /home/ieemoo0337/projects/datasets/FP/9345521001145/9345521001145_20241017-112028_back_addGood_5478c9a4db2c_815_18133699824.mp4: 640x512 5.3ms\n",
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"video 1/1 (25/39) /home/ieemoo0337/projects/datasets/FP/9345521001145/9345521001145_20241017-112028_back_addGood_5478c9a4db2c_815_18133699824.mp4: 640x512 5.3ms\n",
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"video 1/1 (26/39) /home/ieemoo0337/projects/datasets/FP/9345521001145/9345521001145_20241017-112028_back_addGood_5478c9a4db2c_815_18133699824.mp4: 640x512 5.3ms\n",
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"video 1/1 (27/39) /home/ieemoo0337/projects/datasets/FP/9345521001145/9345521001145_20241017-112028_back_addGood_5478c9a4db2c_815_18133699824.mp4: 640x512 5.4ms\n",
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||
"video 1/1 (29/39) /home/ieemoo0337/projects/datasets/FP/9345521001145/9345521001145_20241017-112028_back_addGood_5478c9a4db2c_815_18133699824.mp4: 640x512 5.3ms\n",
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||
"video 1/1 (30/39) /home/ieemoo0337/projects/datasets/FP/9345521001145/9345521001145_20241017-112028_back_addGood_5478c9a4db2c_815_18133699824.mp4: 640x512 5.2ms\n",
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||
"video 1/1 (31/39) /home/ieemoo0337/projects/datasets/FP/9345521001145/9345521001145_20241017-112028_back_addGood_5478c9a4db2c_815_18133699824.mp4: 640x512 5.4ms\n",
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||
"video 1/1 (32/39) /home/ieemoo0337/projects/datasets/FP/9345521001145/9345521001145_20241017-112028_back_addGood_5478c9a4db2c_815_18133699824.mp4: 640x512 5.4ms\n",
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||
"video 1/1 (33/39) /home/ieemoo0337/projects/datasets/FP/9345521001145/9345521001145_20241017-112028_back_addGood_5478c9a4db2c_815_18133699824.mp4: 640x512 5.3ms\n",
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"video 1/1 (34/39) /home/ieemoo0337/projects/datasets/FP/9345521001145/9345521001145_20241017-112028_back_addGood_5478c9a4db2c_815_18133699824.mp4: 640x512 5.3ms\n",
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"video 1/1 (35/39) /home/ieemoo0337/projects/datasets/FP/9345521001145/9345521001145_20241017-112028_back_addGood_5478c9a4db2c_815_18133699824.mp4: 640x512 5.3ms\n",
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||
"video 1/1 (36/39) /home/ieemoo0337/projects/datasets/FP/9345521001145/9345521001145_20241017-112028_back_addGood_5478c9a4db2c_815_18133699824.mp4: 640x512 5.3ms\n",
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||
"video 1/1 (37/39) /home/ieemoo0337/projects/datasets/FP/9345521001145/9345521001145_20241017-112028_back_addGood_5478c9a4db2c_815_18133699824.mp4: 640x512 5.3ms\n",
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||
"video 1/1 (38/39) /home/ieemoo0337/projects/datasets/FP/9345521001145/9345521001145_20241017-112028_back_addGood_5478c9a4db2c_815_18133699824.mp4: 640x512 5.3ms\n",
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||
"video 1/1 (39/39) /home/ieemoo0337/projects/datasets/FP/9345521001145/9345521001145_20241017-112028_back_addGood_5478c9a4db2c_815_18133699824.mp4: 640x512 5.3ms\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"{'item1': {'Text': 'Jerseyjoy Acejoy Full Cream Milk', 'Color': '白色', 'Shape': '圆柱形', 'Material': '塑料', 'Category': '乳制品'}, 'item2': {'Text': '未知', 'Color': '未知', 'Shape': '未知', 'Material': '未知', 'Category': '未知'}, 'is_Same': False}\n",
|
||
"Precision: 0.14\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"import os\n",
|
||
"import torch\n",
|
||
"from Qwen_agent import item_analysis\n",
|
||
"import json\n",
|
||
"\n",
|
||
"dir_path = \"/home/ieemoo0337/projects/datasets/FP\"\n",
|
||
"dir_names = os.listdir(dir_path)\n",
|
||
"error_list = []\n",
|
||
"false_list = []\n",
|
||
"empty_list = []\n",
|
||
"pass_list = []\n",
|
||
"count = 0\n",
|
||
"for dir in dir_names:\n",
|
||
" if count >= 100:\n",
|
||
" break\n",
|
||
" torch.cuda.empty_cache()\n",
|
||
" stream_dict = {}\n",
|
||
" sub_dir = os.path.join(dir_path, dir)\n",
|
||
" print(\"barcode: \", dir)\n",
|
||
" for file in os.listdir(sub_dir):\n",
|
||
" stream_dict[\"barcode\"] = dir\n",
|
||
" if file.endswith(\".mp4\"):\n",
|
||
" stream_dict[\"video\"] = os.path.join(sub_dir, file)\n",
|
||
" print(\"video: \", stream_dict[\"video\"])\n",
|
||
" elif file.endswith(\".jpg\"):\n",
|
||
" stream_dict[\"goodsPic\"] = os.path.join(sub_dir, file)\n",
|
||
" print(\"goodsPic: \", stream_dict[\"goodsPic\"])\n",
|
||
" try:\n",
|
||
" result = item_analysis(stream_dict)\n",
|
||
" print(result)\n",
|
||
" if not result:\n",
|
||
" empty_list.append(stream_dict[\"barcode\"])\n",
|
||
" continue\n",
|
||
" except Exception as e:\n",
|
||
" print(f\"Error processing {stream_dict['barcode']}: {e}\")\n",
|
||
" error_list.append(stream_dict[\"barcode\"])\n",
|
||
" continue\n",
|
||
" if result[\"is_Same\"] == False:\n",
|
||
" false_list.append([stream_dict[\"barcode\"], result, stream_dict[\"video\"], stream_dict[\"goodsPic\"]])\n",
|
||
" else:\n",
|
||
" pass_list.append([stream_dict[\"barcode\"], result, stream_dict[\"video\"], stream_dict[\"goodsPic\"]])\n",
|
||
" del result\n",
|
||
" # data_list.append(stream_dict)\n",
|
||
" count += 1\n",
|
||
"print(\"Precision: \", 1 - len(false_list) / len(dir_names))\n",
|
||
"with open('pass_list.json', 'w') as f:\n",
|
||
" json.dump(pass_list, f)\n",
|
||
"with open('false_list.json', 'w') as f:\n",
|
||
" json.dump(false_list, f)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 4,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"(7, 86)"
|
||
]
|
||
},
|
||
"execution_count": 4,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"len(pass_list), len(false_list)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 4,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"[['9421029085075',\n",
|
||
" {'item1': {'Text': 'Bundaberg PASSIONFRUIT SPARKLING DRINK',\n",
|
||
" 'Color': '橙色',\n",
|
||
" 'Shape': '圆柱形',\n",
|
||
" 'Material': '玻璃',\n",
|
||
" 'Category': '饮料'},\n",
|
||
" 'item2': {'Text': 'Bundaberg PASSIONFRUIT SPARKLING DRINK',\n",
|
||
" 'Color': '橙色',\n",
|
||
" 'Shape': '圆柱形',\n",
|
||
" 'Material': '玻璃',\n",
|
||
" 'Category': '饮料'},\n",
|
||
" 'is_Same': True},\n",
|
||
" '/home/ieemoo0337/projects/datasets/FP/9421029085075/9421029085075_20241016-163745_back_returnGood_5478c9a49bfc_995_18358205530.mp4',\n",
|
||
" '/home/ieemoo0337/projects/datasets/FP/9421029085075/9311493002572.jpg'],\n",
|
||
" ['9421902960826',\n",
|
||
" {'item1': {'Text': 'Plant voice',\n",
|
||
" 'Color': '白色',\n",
|
||
" 'Shape': '圆柱形',\n",
|
||
" 'Material': '塑料',\n",
|
||
" 'Category': '洗发水'},\n",
|
||
" 'item2': {'Text': 'Plant voice',\n",
|
||
" 'Color': '白色',\n",
|
||
" 'Shape': '圆柱形',\n",
|
||
" 'Material': '塑料',\n",
|
||
" 'Category': '洗发水'},\n",
|
||
" 'is_Same': True},\n",
|
||
" '/home/ieemoo0337/projects/datasets/FP/9421902960826/9421902960826_20241018-112509_back_returnGood_5478c9a4eb2c_1065_18058629568.mp4',\n",
|
||
" '/home/ieemoo0337/projects/datasets/FP/9421902960826/9350013003071.jpg'],\n",
|
||
" ['9311493002572',\n",
|
||
" {'item1': {'Text': 'Bundaberg GUAVA SPARKLING DRINK',\n",
|
||
" 'Color': '红色',\n",
|
||
" 'Shape': '圆柱形',\n",
|
||
" 'Material': '玻璃',\n",
|
||
" 'Category': '饮料'},\n",
|
||
" 'item2': {'Text': 'Bundaberg GUAVA SPARKLING DRINK',\n",
|
||
" 'Color': '黄色',\n",
|
||
" 'Shape': '圆柱形',\n",
|
||
" 'Material': '玻璃',\n",
|
||
" 'Category': '饮料'},\n",
|
||
" 'is_Same': True},\n",
|
||
" '/home/ieemoo0337/projects/datasets/FP/9311493002572/9311493002572_20241019-155840_back_addGood_5478c9a49bfc_595_13773168720.mp4',\n",
|
||
" '/home/ieemoo0337/projects/datasets/FP/9311493002572/9421029085075.jpg'],\n",
|
||
" ['8859015700434',\n",
|
||
" {'item1': {'Text': 'Chang Soda Water Lime Flavoured',\n",
|
||
" 'Color': '透明',\n",
|
||
" 'Shape': '圆柱形',\n",
|
||
" 'Material': '玻璃',\n",
|
||
" 'Category': '饮料'},\n",
|
||
" 'item2': {'Text': 'Chang Soda Water Lime Flavoured',\n",
|
||
" 'Color': '透明',\n",
|
||
" 'Shape': '圆柱形',\n",
|
||
" 'Material': '玻璃',\n",
|
||
" 'Category': '饮料'},\n",
|
||
" 'is_Same': True},\n",
|
||
" '/home/ieemoo0337/projects/datasets/FP/8859015700434/8859015700434_20241017-102526_back_returnGood_5478c9a48c3e_390_13586533739.mp4',\n",
|
||
" '/home/ieemoo0337/projects/datasets/FP/8859015700434/8859594300018.jpg'],\n",
|
||
" ['8934760211005',\n",
|
||
" {'item1': {'Text': 'Enaak',\n",
|
||
" 'Color': '黄色',\n",
|
||
" 'Shape': '长方形',\n",
|
||
" 'Material': '塑料',\n",
|
||
" 'Category': '方便面'},\n",
|
||
" 'item2': {'Text': 'Enaak',\n",
|
||
" 'Color': '黄色',\n",
|
||
" 'Shape': '长方形',\n",
|
||
" 'Material': '塑料',\n",
|
||
" 'Category': '方便面'},\n",
|
||
" 'is_Same': True},\n",
|
||
" '/home/ieemoo0337/projects/datasets/FP/8934760211005/8934760211005_20241020-135449_back_addGood_5478c9a49bfc_5_13799009402.mp4',\n",
|
||
" '/home/ieemoo0337/projects/datasets/FP/8934760211005/8994834005237.jpg'],\n",
|
||
" ['9345521003781',\n",
|
||
" {'item1': {'Text': 'MICO',\n",
|
||
" 'Color': '蓝色',\n",
|
||
" 'Shape': '圆形',\n",
|
||
" 'Material': '纸',\n",
|
||
" 'Category': '饼干'},\n",
|
||
" 'item2': {'Text': 'MICO',\n",
|
||
" 'Color': '蓝色',\n",
|
||
" 'Shape': '圆形',\n",
|
||
" 'Material': '纸',\n",
|
||
" 'Category': '饼干'},\n",
|
||
" 'is_Same': True},\n",
|
||
" '/home/ieemoo0337/projects/datasets/FP/9345521003781/9345521003781_20241016-152122_back_addGood_5478c9a48b7e_805_13586533739.mp4',\n",
|
||
" '/home/ieemoo0337/projects/datasets/FP/9345521003781/9551010541867.jpg'],\n",
|
||
" ['9415007042037',\n",
|
||
" {'item1': {'Text': 'G7 COFFEE INSTANT COFFEE',\n",
|
||
" 'Color': '红色',\n",
|
||
" 'Shape': '长方形',\n",
|
||
" 'Material': '塑料',\n",
|
||
" 'Category': '咖啡'},\n",
|
||
" 'item2': {'Text': 'G7 COFFEE INSTANT COFFEE',\n",
|
||
" 'Color': '红色',\n",
|
||
" 'Shape': '长方形',\n",
|
||
" 'Material': '塑料',\n",
|
||
" 'Category': '咖啡'},\n",
|
||
" 'is_Same': True},\n",
|
||
" '/home/ieemoo0337/projects/datasets/FP/9415007042037/9415007042037_20241020-113231_back_addGood_5478c9a4db2c_90_13773168720.mp4',\n",
|
||
" '/home/ieemoo0337/projects/datasets/FP/9415007042037/8935024156117.jpg'],\n",
|
||
" ['9310072000282',\n",
|
||
" {'item1': {'Text': '露莎士 泰式甜辣酱',\n",
|
||
" 'Color': '红色',\n",
|
||
" 'Shape': '长方形',\n",
|
||
" 'Material': '玻璃',\n",
|
||
" 'Category': '调料'},\n",
|
||
" 'item2': {'Text': '露莎士 泰式甜辣酱',\n",
|
||
" 'Color': '红色',\n",
|
||
" 'Shape': '长方形',\n",
|
||
" 'Material': '玻璃',\n",
|
||
" 'Category': '调料'},\n",
|
||
" 'is_Same': True},\n",
|
||
" '/home/ieemoo0337/projects/datasets/FP/9310072000282/9310072000282_20241019-142114_back_addGood_5478c9a49bfc_210_13773168720.mp4',\n",
|
||
" '/home/ieemoo0337/projects/datasets/FP/9310072000282/8850511311100.jpg']]"
|
||
]
|
||
},
|
||
"execution_count": 4,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"pass_list"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 26,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"with open('pass_list.json', 'w') as f:\n",
|
||
" json.dump(pass_list, f)\n",
|
||
"with open('false_list.json', 'w') as f:\n",
|
||
" json.dump(false_list, f)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 27,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"[['8935024140147',\n",
|
||
" {'item1': {'Text': 'Farm Milk Powder',\n",
|
||
" 'Color': '红色',\n",
|
||
" 'Shape': '长方体',\n",
|
||
" 'Material': '纸箱',\n",
|
||
" 'Category': '乳制品'},\n",
|
||
" 'item2': {'Text': '农夫牛奶',\n",
|
||
" 'Color': '红色',\n",
|
||
" 'Shape': '长方体',\n",
|
||
" 'Material': '纸箱',\n",
|
||
" 'Category': '乳制品'},\n",
|
||
" 'is_Same': True},\n",
|
||
" '/home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4',\n",
|
||
" '/home/ieemoo0337/projects/datasets/FP/8935024140147/9421029085228.jpg'],\n",
|
||
" ['9421029085075',\n",
|
||
" {'item1': {'Text': 'Bundaberg PASSIONFRUIT SPARKLING DRINK',\n",
|
||
" 'Color': '橙色',\n",
|
||
" 'Shape': '圆柱形',\n",
|
||
" 'Material': '玻璃',\n",
|
||
" 'Category': '饮料'},\n",
|
||
" 'item2': {'Text': 'Bundaberg PASSIONFRUIT SPARKLING DRINK',\n",
|
||
" 'Color': '橙色',\n",
|
||
" 'Shape': '圆柱形',\n",
|
||
" 'Material': '玻璃',\n",
|
||
" 'Category': '饮料'},\n",
|
||
" 'is_Same': True},\n",
|
||
" '/home/ieemoo0337/projects/datasets/FP/9421029085075/9421029085075_20241016-163745_back_returnGood_5478c9a49bfc_995_18358205530.mp4',\n",
|
||
" '/home/ieemoo0337/projects/datasets/FP/9421029085075/9311493002572.jpg'],\n",
|
||
" ['8935024156117',\n",
|
||
" {'item1': {'Text': 'Anchor',\n",
|
||
" 'Color': '白色',\n",
|
||
" 'Shape': '长方形',\n",
|
||
" 'Material': '塑料',\n",
|
||
" 'Category': '食品'},\n",
|
||
" 'item2': {'Text': 'Anchor',\n",
|
||
" 'Color': '白色',\n",
|
||
" 'Shape': '长方形',\n",
|
||
" 'Material': '塑料',\n",
|
||
" 'Category': '食品'},\n",
|
||
" 'is_Same': True},\n",
|
||
" '/home/ieemoo0337/projects/datasets/FP/8935024156117/8935024156117_20241015-135323_back_addGood_5478c9a48b7e_1765_13799009402.mp4',\n",
|
||
" '/home/ieemoo0337/projects/datasets/FP/8935024156117/9415007042037.jpg'],\n",
|
||
" ['8859015700434',\n",
|
||
" {'item1': {'Text': 'Chang Soda Water Lime Flavoured',\n",
|
||
" 'Color': '透明',\n",
|
||
" 'Shape': '圆柱形',\n",
|
||
" 'Material': '玻璃',\n",
|
||
" 'Category': '饮料'},\n",
|
||
" 'item2': {'Text': 'Chang Soda Water Lime Flavoured',\n",
|
||
" 'Color': '透明',\n",
|
||
" 'Shape': '圆柱形',\n",
|
||
" 'Material': '玻璃',\n",
|
||
" 'Category': '饮料'},\n",
|
||
" 'is_Same': True},\n",
|
||
" '/home/ieemoo0337/projects/datasets/FP/8859015700434/8859015700434_20241017-102526_back_returnGood_5478c9a48c3e_390_13586533739.mp4',\n",
|
||
" '/home/ieemoo0337/projects/datasets/FP/8859015700434/8859594300018.jpg'],\n",
|
||
" ['8934760211005',\n",
|
||
" {'item1': {'Text': 'Enaak',\n",
|
||
" 'Color': '黄色',\n",
|
||
" 'Shape': '长方形',\n",
|
||
" 'Material': '塑料',\n",
|
||
" 'Category': '方便面'},\n",
|
||
" 'item2': {'Text': 'Enaak',\n",
|
||
" 'Color': '黄色',\n",
|
||
" 'Shape': '长方形',\n",
|
||
" 'Material': '塑料',\n",
|
||
" 'Category': '方便面'},\n",
|
||
" 'is_Same': True},\n",
|
||
" '/home/ieemoo0337/projects/datasets/FP/8934760211005/8934760211005_20241020-135449_back_addGood_5478c9a49bfc_5_13799009402.mp4',\n",
|
||
" '/home/ieemoo0337/projects/datasets/FP/8934760211005/8994834005237.jpg'],\n",
|
||
" ['9421029081985',\n",
|
||
" {'item1': {'Text': 'Theland New Zealand Farm Milk Powder Skim Milk Powder',\n",
|
||
" 'Color': '蓝色',\n",
|
||
" 'Shape': '长方形',\n",
|
||
" 'Material': '塑料',\n",
|
||
" 'Category': '乳制品'},\n",
|
||
" 'item2': {'Text': 'Theland 新西兰农场鲜奶粉',\n",
|
||
" 'Color': '白色',\n",
|
||
" 'Shape': '长方形',\n",
|
||
" 'Material': '塑料',\n",
|
||
" 'Category': '乳制品'},\n",
|
||
" 'is_Same': True},\n",
|
||
" '/home/ieemoo0337/projects/datasets/FP/9421029081985/9421029081985_20241018-113315_back_returnGood_5478c9a48b7e_1055_15027299265.mp4',\n",
|
||
" '/home/ieemoo0337/projects/datasets/FP/9421029081985/9421029080278.jpg'],\n",
|
||
" ['9415007042037',\n",
|
||
" {'item1': {'Text': 'G7 COFFEE INSTANT COFFEE',\n",
|
||
" 'Color': '红色',\n",
|
||
" 'Shape': '长方形',\n",
|
||
" 'Material': '塑料',\n",
|
||
" 'Category': '咖啡'},\n",
|
||
" 'item2': {'Text': 'G7 COFFEE INSTANT COFFEE',\n",
|
||
" 'Color': '红色',\n",
|
||
" 'Shape': '长方形',\n",
|
||
" 'Material': '塑料',\n",
|
||
" 'Category': '咖啡'},\n",
|
||
" 'is_Same': True},\n",
|
||
" '/home/ieemoo0337/projects/datasets/FP/9415007042037/9415007042037_20241020-113231_back_addGood_5478c9a4db2c_90_13773168720.mp4',\n",
|
||
" '/home/ieemoo0337/projects/datasets/FP/9415007042037/8935024156117.jpg'],\n",
|
||
" ['9415007004585',\n",
|
||
" {'item1': {'Text': 'OCSHP CAPSULE DETERGENT',\n",
|
||
" 'Color': '白色',\n",
|
||
" 'Shape': '长方体',\n",
|
||
" 'Material': '塑料',\n",
|
||
" 'Category': '洗衣液'},\n",
|
||
" 'item2': {'Text': 'OCSHP CAPSULE DETERGENT',\n",
|
||
" 'Color': '蓝色',\n",
|
||
" 'Shape': '长方体',\n",
|
||
" 'Material': '塑料',\n",
|
||
" 'Category': '洗衣液'},\n",
|
||
" 'is_Same': True},\n",
|
||
" '/home/ieemoo0337/projects/datasets/FP/9415007004585/9415007004585_20241020-113222_back_returnGood_5478c9a4db2c_260_13773168720.mp4',\n",
|
||
" '/home/ieemoo0337/projects/datasets/FP/9415007004585/9310072012599.jpg'],\n",
|
||
" ['8994834005237',\n",
|
||
" {'item1': {'Text': 'Tipo',\n",
|
||
" 'Color': '黄色',\n",
|
||
" 'Shape': '长方形',\n",
|
||
" 'Material': '饼干',\n",
|
||
" 'Category': '零食'},\n",
|
||
" 'item2': {'Text': 'Enak',\n",
|
||
" 'Color': '黄色',\n",
|
||
" 'Shape': '长方形',\n",
|
||
" 'Material': '饼干',\n",
|
||
" 'Category': '零食'},\n",
|
||
" 'is_Same': True},\n",
|
||
" '/home/ieemoo0337/projects/datasets/FP/8994834005237/8994834005237_20241015-145820_back_addGood_5478c9a48b7e_100_13799009402.mp4',\n",
|
||
" '/home/ieemoo0337/projects/datasets/FP/8994834005237/8934760211005.jpg'],\n",
|
||
" ['9310072000282',\n",
|
||
" {'item1': {'Text': '露莎士 泰式甜辣酱',\n",
|
||
" 'Color': '红色',\n",
|
||
" 'Shape': '长方形',\n",
|
||
" 'Material': '玻璃',\n",
|
||
" 'Category': '调料'},\n",
|
||
" 'item2': {'Text': '露莎士 泰式甜辣酱',\n",
|
||
" 'Color': '红色',\n",
|
||
" 'Shape': '长方形',\n",
|
||
" 'Material': '玻璃',\n",
|
||
" 'Category': '调料'},\n",
|
||
" 'is_Same': True},\n",
|
||
" '/home/ieemoo0337/projects/datasets/FP/9310072000282/9310072000282_20241019-142114_back_addGood_5478c9a49bfc_210_13773168720.mp4',\n",
|
||
" '/home/ieemoo0337/projects/datasets/FP/9310072000282/8850511311100.jpg'],\n",
|
||
" ['9417574001097',\n",
|
||
" {'item1': {'Text': 'Lanolin Oil Moisturising Cream',\n",
|
||
" 'Color': '白色',\n",
|
||
" 'Shape': '圆柱形',\n",
|
||
" 'Material': '塑料',\n",
|
||
" 'Category': '护肤品'},\n",
|
||
" 'item2': {'Text': 'Lanolin Oil Moisturising Cream',\n",
|
||
" 'Color': '白色',\n",
|
||
" 'Shape': '圆柱形',\n",
|
||
" 'Material': '塑料',\n",
|
||
" 'Category': '护肤品'},\n",
|
||
" 'is_Same': True},\n",
|
||
" '/home/ieemoo0337/projects/datasets/FP/9417574001097/9417574001097_20241018-165605_back_addGood_5478c9a4eb2c_520_18969520488.mp4',\n",
|
||
" '/home/ieemoo0337/projects/datasets/FP/9417574001097/9322316001108.jpg']]"
|
||
]
|
||
},
|
||
"execution_count": 27,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"pass_list"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 7,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"import json\n",
|
||
"with open('pass_list.json', 'w') as f:\n",
|
||
" json.dump(pass_list, f)\n",
|
||
"with open('false_list.json', 'w') as f:\n",
|
||
" json.dump(false_list, f)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 1,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"ename": "NameError",
|
||
"evalue": "name 'pass_list' is not defined",
|
||
"output_type": "error",
|
||
"traceback": [
|
||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||
"\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
|
||
"Cell \u001b[0;32mIn[1], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mpass_list\u001b[49m\n",
|
||
"\u001b[0;31mNameError\u001b[0m: name 'pass_list' is not defined"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"pass_list"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 1,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"/home/ieemoo0337/.local/lib/python3.10/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
|
||
" from .autonotebook import tqdm as notebook_tqdm\n",
|
||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"load model resnet18 \n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"`Qwen2VLRotaryEmbedding` can now be fully parameterized by passing the model config through the `config` argument. All other arguments will be removed in v4.46\n",
|
||
"Loading checkpoint shards: 100%|██████████| 5/5 [00:05<00:00, 1.04s/it]\n",
|
||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
|
||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n",
|
||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"load model resnet18 \n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
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||
"text": [
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"video 1/1 (1/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 42.9ms\n",
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"video 1/1 (2/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.4ms\n",
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"video 1/1 (3/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.1ms\n",
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"video 1/1 (4/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.2ms\n",
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"video 1/1 (5/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.4ms\n",
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"video 1/1 (6/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 7.7ms\n",
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"video 1/1 (29/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.5ms\n",
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"video 1/1 (30/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.6ms\n",
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"video 1/1 (31/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.5ms\n",
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"video 1/1 (33/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.9ms\n",
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"video 1/1 (34/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.4ms\n",
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"video 1/1 (35/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.3ms\n",
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"video 1/1 (37/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.8ms\n",
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"video 1/1 (39/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.2ms\n",
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"video 1/1 (41/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 10.0ms\n",
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"video 1/1 (43/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.2ms\n",
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"video 1/1 (56/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.3ms\n",
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"video 1/1 (59/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.2ms\n",
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"video 1/1 (60/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.2ms\n",
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"video 1/1 (62/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.2ms\n",
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"video 1/1 (63/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.2ms\n",
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"video 1/1 (64/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.3ms\n",
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"video 1/1 (65/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.2ms\n",
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"video 1/1 (66/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.3ms\n",
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"video 1/1 (67/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.1ms\n",
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"video 1/1 (68/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.2ms\n",
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"video 1/1 (69/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.1ms\n",
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"video 1/1 (70/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.1ms\n",
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"video 1/1 (71/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.5ms\n",
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"video 1/1 (72/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.4ms\n",
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"video 1/1 (73/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.3ms\n",
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"video 1/1 (74/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.2ms\n",
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"video 1/1 (75/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.4ms\n",
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"video 1/1 (77/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.3ms\n",
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"video 1/1 (80/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 6.0ms\n",
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"video 1/1 (81/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 6.9ms\n",
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"video 1/1 (82/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.7ms\n",
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"video 1/1 (83/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.8ms\n",
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"video 1/1 (84/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.8ms\n",
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"video 1/1 (85/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.8ms\n",
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"video 1/1 (86/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.7ms\n",
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"video 1/1 (87/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 6.1ms\n",
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"video 1/1 (88/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.7ms\n",
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"video 1/1 (89/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.7ms\n",
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"video 1/1 (90/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.7ms\n",
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"video 1/1 (91/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.7ms\n",
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"video 1/1 (92/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.7ms\n",
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"video 1/1 (93/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.7ms\n",
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"video 1/1 (94/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.6ms\n",
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"video 1/1 (95/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.7ms\n",
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"video 1/1 (96/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.5ms\n",
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"video 1/1 (97/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.5ms\n",
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"video 1/1 (98/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.4ms\n",
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"video 1/1 (99/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.5ms\n",
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"video 1/1 (100/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.4ms\n",
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"video 1/1 (101/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.4ms\n",
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"video 1/1 (102/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.4ms\n",
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"video 1/1 (103/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.4ms\n",
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"video 1/1 (104/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.3ms\n",
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"video 1/1 (105/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.3ms\n",
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"video 1/1 (106/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.4ms\n",
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"video 1/1 (107/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.3ms\n",
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"video 1/1 (108/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.6ms\n",
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"video 1/1 (109/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.4ms\n",
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"video 1/1 (110/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.3ms\n",
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"video 1/1 (111/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.2ms\n",
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"video 1/1 (112/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.3ms\n",
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"video 1/1 (113/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.3ms\n",
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"video 1/1 (114/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.3ms\n",
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"video 1/1 (115/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.3ms\n",
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"video 1/1 (116/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.3ms\n",
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"video 1/1 (117/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.3ms\n",
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"video 1/1 (118/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.3ms\n",
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"video 1/1 (119/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.5ms\n",
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"video 1/1 (120/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.3ms\n",
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"video 1/1 (121/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.3ms\n",
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"video 1/1 (122/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.2ms\n",
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"video 1/1 (123/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.8ms\n",
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"video 1/1 (124/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.4ms\n",
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"video 1/1 (125/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.3ms\n",
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"video 1/1 (126/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.3ms\n",
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"video 1/1 (127/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.2ms\n",
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"video 1/1 (128/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.3ms\n",
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"video 1/1 (129/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.3ms\n",
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"video 1/1 (130/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.3ms\n",
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"video 1/1 (131/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.3ms\n",
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"video 1/1 (132/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.8ms\n",
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"video 1/1 (133/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.3ms\n",
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"video 1/1 (134/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.4ms\n",
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"video 1/1 (135/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.3ms\n",
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"video 1/1 (136/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.3ms\n",
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"video 1/1 (137/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.3ms\n",
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"video 1/1 (138/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.3ms\n"
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||
]
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},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
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||
"text": [
|
||
"Number of input images: 4\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"import os\n",
|
||
"import torch\n",
|
||
"from Qwen_agent import item_analysis\n",
|
||
"\n",
|
||
"std_img = '/home/ieemoo0337/projects/datasets/FP/8935024140147/9421029085228.jpg'\n",
|
||
"video_path = '/home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4'\n",
|
||
"\n",
|
||
"stream_dict = {\n",
|
||
" \"goodsName\" : \"优诺优丝黄桃果粒风味发酵乳\",\n",
|
||
" \"measureProperty\" : 0,\n",
|
||
" \"qty\" : 1,\n",
|
||
" \"price\" : 25.9,\n",
|
||
" \"weight\": 560, # 单位克\n",
|
||
" \"barcode\": \"6922646102433\",\n",
|
||
" \"video\" : video_path,\n",
|
||
" \"goodsPic\" : std_img,\n",
|
||
" \"measureUnit\" : \"组\",\n",
|
||
" \"goodsSpec\" : \"405g\"\n",
|
||
"}\n",
|
||
"torch.cuda.empty_cache()\n",
|
||
"result = item_analysis(stream_dict)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 2,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"{'item1': {'Text': 'Farm Milk Powder',\n",
|
||
" 'Color': '红色',\n",
|
||
" 'Shape': '长方体',\n",
|
||
" 'Material': '纸箱',\n",
|
||
" 'Category': '乳制品'},\n",
|
||
" 'item2': {'Text': '农夫牛奶',\n",
|
||
" 'Color': '红色',\n",
|
||
" 'Shape': '长方体',\n",
|
||
" 'Material': '纸箱',\n",
|
||
" 'Category': '乳制品'},\n",
|
||
" 'is_Same': True}"
|
||
]
|
||
},
|
||
"execution_count": 2,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"result"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 8,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
|
||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n",
|
||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
"video 1/1 (1/52) /home/ieemoo0337/projects/datasets/FP/9311493002572/9311493002572_20241019-155840_back_addGood_5478c9a49bfc_595_13773168720.mp4: 640x512 6.3ms\n",
|
||
"video 1/1 (2/52) /home/ieemoo0337/projects/datasets/FP/9311493002572/9311493002572_20241019-155840_back_addGood_5478c9a49bfc_595_13773168720.mp4: 640x512 5.1ms\n",
|
||
"video 1/1 (3/52) /home/ieemoo0337/projects/datasets/FP/9311493002572/9311493002572_20241019-155840_back_addGood_5478c9a49bfc_595_13773168720.mp4: 640x512 5.2ms\n",
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||
"video 1/1 (4/52) /home/ieemoo0337/projects/datasets/FP/9311493002572/9311493002572_20241019-155840_back_addGood_5478c9a49bfc_595_13773168720.mp4: 640x512 5.2ms\n",
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||
"video 1/1 (5/52) /home/ieemoo0337/projects/datasets/FP/9311493002572/9311493002572_20241019-155840_back_addGood_5478c9a49bfc_595_13773168720.mp4: 640x512 5.2ms\n",
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||
"video 1/1 (6/52) /home/ieemoo0337/projects/datasets/FP/9311493002572/9311493002572_20241019-155840_back_addGood_5478c9a49bfc_595_13773168720.mp4: 640x512 5.2ms\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"load model resnet18 \n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"video 1/1 (7/52) /home/ieemoo0337/projects/datasets/FP/9311493002572/9311493002572_20241019-155840_back_addGood_5478c9a49bfc_595_13773168720.mp4: 640x512 5.3ms\n",
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"video 1/1 (8/52) /home/ieemoo0337/projects/datasets/FP/9311493002572/9311493002572_20241019-155840_back_addGood_5478c9a49bfc_595_13773168720.mp4: 640x512 5.2ms\n",
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"video 1/1 (9/52) /home/ieemoo0337/projects/datasets/FP/9311493002572/9311493002572_20241019-155840_back_addGood_5478c9a49bfc_595_13773168720.mp4: 640x512 5.2ms\n",
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"video 1/1 (10/52) /home/ieemoo0337/projects/datasets/FP/9311493002572/9311493002572_20241019-155840_back_addGood_5478c9a49bfc_595_13773168720.mp4: 640x512 5.5ms\n",
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"video 1/1 (11/52) /home/ieemoo0337/projects/datasets/FP/9311493002572/9311493002572_20241019-155840_back_addGood_5478c9a49bfc_595_13773168720.mp4: 640x512 5.1ms\n",
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"video 1/1 (12/52) /home/ieemoo0337/projects/datasets/FP/9311493002572/9311493002572_20241019-155840_back_addGood_5478c9a49bfc_595_13773168720.mp4: 640x512 5.2ms\n",
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"video 1/1 (13/52) /home/ieemoo0337/projects/datasets/FP/9311493002572/9311493002572_20241019-155840_back_addGood_5478c9a49bfc_595_13773168720.mp4: 640x512 5.3ms\n",
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"video 1/1 (14/52) /home/ieemoo0337/projects/datasets/FP/9311493002572/9311493002572_20241019-155840_back_addGood_5478c9a49bfc_595_13773168720.mp4: 640x512 5.2ms\n",
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"video 1/1 (15/52) /home/ieemoo0337/projects/datasets/FP/9311493002572/9311493002572_20241019-155840_back_addGood_5478c9a49bfc_595_13773168720.mp4: 640x512 5.2ms\n",
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"video 1/1 (16/52) /home/ieemoo0337/projects/datasets/FP/9311493002572/9311493002572_20241019-155840_back_addGood_5478c9a49bfc_595_13773168720.mp4: 640x512 5.2ms\n",
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"video 1/1 (17/52) /home/ieemoo0337/projects/datasets/FP/9311493002572/9311493002572_20241019-155840_back_addGood_5478c9a49bfc_595_13773168720.mp4: 640x512 5.2ms\n",
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"video 1/1 (18/52) /home/ieemoo0337/projects/datasets/FP/9311493002572/9311493002572_20241019-155840_back_addGood_5478c9a49bfc_595_13773168720.mp4: 640x512 5.2ms\n",
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"video 1/1 (19/52) /home/ieemoo0337/projects/datasets/FP/9311493002572/9311493002572_20241019-155840_back_addGood_5478c9a49bfc_595_13773168720.mp4: 640x512 5.2ms\n",
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"video 1/1 (20/52) /home/ieemoo0337/projects/datasets/FP/9311493002572/9311493002572_20241019-155840_back_addGood_5478c9a49bfc_595_13773168720.mp4: 640x512 5.2ms\n",
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"video 1/1 (21/52) /home/ieemoo0337/projects/datasets/FP/9311493002572/9311493002572_20241019-155840_back_addGood_5478c9a49bfc_595_13773168720.mp4: 640x512 5.3ms\n",
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"video 1/1 (22/52) /home/ieemoo0337/projects/datasets/FP/9311493002572/9311493002572_20241019-155840_back_addGood_5478c9a49bfc_595_13773168720.mp4: 640x512 5.2ms\n",
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"video 1/1 (23/52) /home/ieemoo0337/projects/datasets/FP/9311493002572/9311493002572_20241019-155840_back_addGood_5478c9a49bfc_595_13773168720.mp4: 640x512 5.2ms\n",
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"video 1/1 (24/52) /home/ieemoo0337/projects/datasets/FP/9311493002572/9311493002572_20241019-155840_back_addGood_5478c9a49bfc_595_13773168720.mp4: 640x512 5.2ms\n",
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"video 1/1 (25/52) /home/ieemoo0337/projects/datasets/FP/9311493002572/9311493002572_20241019-155840_back_addGood_5478c9a49bfc_595_13773168720.mp4: 640x512 5.2ms\n",
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"video 1/1 (26/52) /home/ieemoo0337/projects/datasets/FP/9311493002572/9311493002572_20241019-155840_back_addGood_5478c9a49bfc_595_13773168720.mp4: 640x512 5.3ms\n",
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"video 1/1 (27/52) /home/ieemoo0337/projects/datasets/FP/9311493002572/9311493002572_20241019-155840_back_addGood_5478c9a49bfc_595_13773168720.mp4: 640x512 5.2ms\n",
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"video 1/1 (28/52) /home/ieemoo0337/projects/datasets/FP/9311493002572/9311493002572_20241019-155840_back_addGood_5478c9a49bfc_595_13773168720.mp4: 640x512 5.2ms\n",
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"video 1/1 (29/52) /home/ieemoo0337/projects/datasets/FP/9311493002572/9311493002572_20241019-155840_back_addGood_5478c9a49bfc_595_13773168720.mp4: 640x512 5.2ms\n",
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"video 1/1 (30/52) /home/ieemoo0337/projects/datasets/FP/9311493002572/9311493002572_20241019-155840_back_addGood_5478c9a49bfc_595_13773168720.mp4: 640x512 5.2ms\n",
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"video 1/1 (31/52) /home/ieemoo0337/projects/datasets/FP/9311493002572/9311493002572_20241019-155840_back_addGood_5478c9a49bfc_595_13773168720.mp4: 640x512 5.2ms\n",
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"video 1/1 (32/52) /home/ieemoo0337/projects/datasets/FP/9311493002572/9311493002572_20241019-155840_back_addGood_5478c9a49bfc_595_13773168720.mp4: 640x512 5.3ms\n",
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"video 1/1 (33/52) /home/ieemoo0337/projects/datasets/FP/9311493002572/9311493002572_20241019-155840_back_addGood_5478c9a49bfc_595_13773168720.mp4: 640x512 5.3ms\n",
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"video 1/1 (34/52) /home/ieemoo0337/projects/datasets/FP/9311493002572/9311493002572_20241019-155840_back_addGood_5478c9a49bfc_595_13773168720.mp4: 640x512 5.2ms\n",
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"video 1/1 (35/52) /home/ieemoo0337/projects/datasets/FP/9311493002572/9311493002572_20241019-155840_back_addGood_5478c9a49bfc_595_13773168720.mp4: 640x512 5.2ms\n",
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"video 1/1 (36/52) /home/ieemoo0337/projects/datasets/FP/9311493002572/9311493002572_20241019-155840_back_addGood_5478c9a49bfc_595_13773168720.mp4: 640x512 5.3ms\n",
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"video 1/1 (37/52) /home/ieemoo0337/projects/datasets/FP/9311493002572/9311493002572_20241019-155840_back_addGood_5478c9a49bfc_595_13773168720.mp4: 640x512 5.2ms\n",
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"video 1/1 (38/52) /home/ieemoo0337/projects/datasets/FP/9311493002572/9311493002572_20241019-155840_back_addGood_5478c9a49bfc_595_13773168720.mp4: 640x512 5.3ms\n",
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"video 1/1 (39/52) /home/ieemoo0337/projects/datasets/FP/9311493002572/9311493002572_20241019-155840_back_addGood_5478c9a49bfc_595_13773168720.mp4: 640x512 5.3ms\n",
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"video 1/1 (40/52) /home/ieemoo0337/projects/datasets/FP/9311493002572/9311493002572_20241019-155840_back_addGood_5478c9a49bfc_595_13773168720.mp4: 640x512 5.2ms\n",
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"video 1/1 (41/52) /home/ieemoo0337/projects/datasets/FP/9311493002572/9311493002572_20241019-155840_back_addGood_5478c9a49bfc_595_13773168720.mp4: 640x512 5.3ms\n",
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"video 1/1 (42/52) /home/ieemoo0337/projects/datasets/FP/9311493002572/9311493002572_20241019-155840_back_addGood_5478c9a49bfc_595_13773168720.mp4: 640x512 5.2ms\n",
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"video 1/1 (43/52) /home/ieemoo0337/projects/datasets/FP/9311493002572/9311493002572_20241019-155840_back_addGood_5478c9a49bfc_595_13773168720.mp4: 640x512 5.2ms\n",
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"video 1/1 (44/52) /home/ieemoo0337/projects/datasets/FP/9311493002572/9311493002572_20241019-155840_back_addGood_5478c9a49bfc_595_13773168720.mp4: 640x512 5.2ms\n",
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"video 1/1 (45/52) /home/ieemoo0337/projects/datasets/FP/9311493002572/9311493002572_20241019-155840_back_addGood_5478c9a49bfc_595_13773168720.mp4: 640x512 5.2ms\n",
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"video 1/1 (46/52) /home/ieemoo0337/projects/datasets/FP/9311493002572/9311493002572_20241019-155840_back_addGood_5478c9a49bfc_595_13773168720.mp4: 640x512 5.2ms\n",
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"video 1/1 (47/52) /home/ieemoo0337/projects/datasets/FP/9311493002572/9311493002572_20241019-155840_back_addGood_5478c9a49bfc_595_13773168720.mp4: 640x512 5.3ms\n",
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"video 1/1 (48/52) /home/ieemoo0337/projects/datasets/FP/9311493002572/9311493002572_20241019-155840_back_addGood_5478c9a49bfc_595_13773168720.mp4: 640x512 5.2ms\n",
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"video 1/1 (49/52) /home/ieemoo0337/projects/datasets/FP/9311493002572/9311493002572_20241019-155840_back_addGood_5478c9a49bfc_595_13773168720.mp4: 640x512 5.3ms\n",
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"video 1/1 (50/52) /home/ieemoo0337/projects/datasets/FP/9311493002572/9311493002572_20241019-155840_back_addGood_5478c9a49bfc_595_13773168720.mp4: 640x512 5.2ms\n",
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"video 1/1 (51/52) /home/ieemoo0337/projects/datasets/FP/9311493002572/9311493002572_20241019-155840_back_addGood_5478c9a49bfc_595_13773168720.mp4: 640x512 5.6ms\n",
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"video 1/1 (52/52) /home/ieemoo0337/projects/datasets/FP/9311493002572/9311493002572_20241019-155840_back_addGood_5478c9a49bfc_595_13773168720.mp4: 640x512 5.5ms\n"
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]
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},
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{
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||
"name": "stdout",
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||
"output_type": "stream",
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||
"text": [
|
||
"output_text: ```python\n",
|
||
"{\n",
|
||
" \"index\": 3\n",
|
||
"}\n",
|
||
"```\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"import os\n",
|
||
"import torch\n",
|
||
"from Qwen_agent import item_analysis\n",
|
||
"\n",
|
||
"std_img = '/home/ieemoo0337/projects/datasets/FP/9311493002572/9421029085075.jpg'\n",
|
||
"video_path = '/home/ieemoo0337/projects/datasets/FP/9311493002572/9311493002572_20241019-155840_back_addGood_5478c9a49bfc_595_13773168720.mp4'\n",
|
||
"\n",
|
||
"stream_dict = {\n",
|
||
" \"goodsName\" : \"优诺优丝黄桃果粒风味发酵乳\",\n",
|
||
" \"measureProperty\" : 0,\n",
|
||
" \"qty\" : 1,\n",
|
||
" \"price\" : 25.9,\n",
|
||
" \"weight\": 560, # 单位克\n",
|
||
" \"barcode\": \"6922646102433\",\n",
|
||
" \"video\" : video_path,\n",
|
||
" \"goodsPic\" : std_img,\n",
|
||
" \"measureUnit\" : \"组\",\n",
|
||
" \"goodsSpec\" : \"405g\"\n",
|
||
"}\n",
|
||
"\n",
|
||
"result = item_analysis(stream_dict)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 9,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"{'item1': {'Text': 'Bundaberg GUAVA SPARKLING DRINK',\n",
|
||
" 'Color': '红色',\n",
|
||
" 'Shape': '圆柱形',\n",
|
||
" 'Material': '玻璃',\n",
|
||
" 'Category': '饮料'},\n",
|
||
" 'item2': {'Text': 'Bundaberg GUAVA SPARKLING DRINK',\n",
|
||
" 'Color': '黄色',\n",
|
||
" 'Shape': '圆柱形',\n",
|
||
" 'Material': '玻璃',\n",
|
||
" 'Category': '饮料'},\n",
|
||
" 'is_Same': True}"
|
||
]
|
||
},
|
||
"execution_count": 9,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"result"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 9,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"YOLOv5 🚀 ad85022 Python-3.10.16 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)\n",
|
||
"\n",
|
||
"/home/ieemoo0337/projects/detecttracking/models/experimental.py:79: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" ckpt = torch.load(attempt_download(w), map_location=device) # load\n",
|
||
"Fusing layers... \n",
|
||
"Model summary: 213 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n",
|
||
"/home/ieemoo0337/projects/detecttracking/contrast/feat_extract/inference.py:49: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
|
||
" self.model.load_state_dict(torch.load(modpath, map_location=conf.device))\n",
|
||
"video 1/1 (1/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.9ms\n",
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||
"video 1/1 (2/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.2ms\n",
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||
"video 1/1 (3/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.1ms\n",
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||
"video 1/1 (4/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.1ms\n",
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"video 1/1 (5/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.1ms\n",
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"video 1/1 (6/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.1ms\n",
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||
"video 1/1 (7/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.1ms\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"load model resnet18 \n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
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||
"text": [
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"video 1/1 (8/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.2ms\n",
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"video 1/1 (9/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.2ms\n",
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"video 1/1 (10/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.2ms\n",
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"video 1/1 (11/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.2ms\n",
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"video 1/1 (12/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.1ms\n",
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"video 1/1 (13/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.2ms\n",
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"video 1/1 (14/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.2ms\n",
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"video 1/1 (15/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.2ms\n",
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"video 1/1 (16/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.2ms\n",
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"video 1/1 (17/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.2ms\n",
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"video 1/1 (18/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.3ms\n",
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"video 1/1 (114/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.9ms\n",
|
||
"video 1/1 (115/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.9ms\n",
|
||
"video 1/1 (116/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.8ms\n",
|
||
"video 1/1 (117/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 6.3ms\n",
|
||
"video 1/1 (118/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.9ms\n",
|
||
"video 1/1 (119/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 6.0ms\n",
|
||
"video 1/1 (120/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 6.0ms\n",
|
||
"video 1/1 (121/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 6.2ms\n",
|
||
"video 1/1 (122/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 6.1ms\n",
|
||
"video 1/1 (123/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 6.0ms\n",
|
||
"video 1/1 (124/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.7ms\n",
|
||
"video 1/1 (125/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.6ms\n",
|
||
"video 1/1 (126/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.5ms\n",
|
||
"video 1/1 (127/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.7ms\n",
|
||
"video 1/1 (128/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 6.6ms\n",
|
||
"video 1/1 (129/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.6ms\n",
|
||
"video 1/1 (130/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.7ms\n",
|
||
"video 1/1 (131/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.6ms\n",
|
||
"video 1/1 (132/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.7ms\n",
|
||
"video 1/1 (133/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.7ms\n",
|
||
"video 1/1 (134/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.7ms\n",
|
||
"video 1/1 (135/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.7ms\n",
|
||
"video 1/1 (136/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.7ms\n",
|
||
"video 1/1 (137/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.6ms\n",
|
||
"video 1/1 (138/138) /home/ieemoo0337/projects/datasets/FP/8935024140147/8935024140147_20241018-133922_back_returnGood_5478c9a53bd4_55_15027299265.mp4: 640x512 5.6ms\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"output_text: ```python\n",
|
||
"{\n",
|
||
" \"index\": 2\n",
|
||
"}\n",
|
||
"```\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"from stream_pipeline import stream_pipeline\n",
|
||
"from Qwen_agent import get_best_image\n",
|
||
"sub_imgs = stream_pipeline(stream_dict)\n",
|
||
"bestimg = get_best_image(sub_imgs)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 10,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/jpeg": 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",
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",
|
||
"text/plain": [
|
||
"<PIL.Image.Image image mode=RGB size=362x239>"
|
||
]
|
||
},
|
||
"execution_count": 10,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"bestimg"
|
||
]
|
||
}
|
||
],
|
||
"metadata": {
|
||
"kernelspec": {
|
||
"display_name": "hexiao_env",
|
||
"language": "python",
|
||
"name": "python3"
|
||
},
|
||
"language_info": {
|
||
"codemirror_mode": {
|
||
"name": "ipython",
|
||
"version": 3
|
||
},
|
||
"file_extension": ".py",
|
||
"mimetype": "text/x-python",
|
||
"name": "python",
|
||
"nbconvert_exporter": "python",
|
||
"pygments_lexer": "ipython3",
|
||
"version": "3.10.16"
|
||
}
|
||
},
|
||
"nbformat": 4,
|
||
"nbformat_minor": 2
|
||
}
|