guoqing bakeup
This commit is contained in:
王庆刚
@ -40,6 +40,7 @@ from scipy.spatial.distance import cdist
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import matplotlib.pyplot as plt
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import shutil
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from datetime import datetime
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from openpyxl import load_workbook, Workbook
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# Vit版resnet, 和现场特征不一致，需将resnet_vit中文件提出
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# from config import config as conf
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@ -56,7 +57,7 @@ from tracking.utils.read_data import extract_data, read_tracking_output, read_de
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from config import config as conf
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from model import resnet18 as resnet18
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from test_ori import inference_image
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from feat_inference import inference_image
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IMG_FORMAT = ['.bmp', '.jpg', '.jpeg', '.png']
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@ -100,13 +101,13 @@ def creat_shopping_event(eventPath, subimgPath=False):
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'''================ 0. 检查 filename 及 eventPath 正确性和有效性 ================'''
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nmlist = eventName.split('_')
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if eventName.find('2024')<0 or len(nmlist)!=2 or len(nmlist[0])!=15 or len(nmlist[1])<11:
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# if eventName.find('2024')<0 or len(nmlist)!=2 or len(nmlist[0])!=15 or len(nmlist[1])<11:
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# return
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if eventName.find('2024')<0 or len(nmlist)!=2 or len(nmlist[1])<11:
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return
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if not os.path.isdir(eventPath):
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return
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'''================ 1. 构造事件描述字典，暂定 9 items ==============='''
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event = {}
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event['barcode'] = eventName.split('_')[1]
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@ -293,10 +294,10 @@ def get_std_barcodeDict(bcdpath, savepath):
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imgpaths.append(imgpath)
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stdBarcodeDict[barcode].extend(imgpaths)
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# pickpath = os.path.join(savepath, f"{barcode}.pickle")
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# with open(pickpath, 'wb') as f:
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# pickle.dump(stdBarcodeDict, f)
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# print(f"Barcode: {barcode}")
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pickpath = os.path.join(savepath, f"{barcode}.pickle")
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with open(pickpath, 'wb') as f:
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pickle.dump(stdBarcodeDict, f)
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print(f"Barcode: {barcode}")
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# k += 1
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# if k == 10:
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@ -352,7 +353,6 @@ def batch_inference(imgpaths, batch):
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feature = featurize(group, conf.test_transform, model, conf.device)
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features.append(feature)
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features = np.concatenate(features, axis=0)
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return features
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def stdfeat_infer(imgPath, featPath, bcdSet=None):
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@ -371,14 +371,20 @@ def stdfeat_infer(imgPath, featPath, bcdSet=None):
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stdBarcodeDict = {}
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stdBarcodeDict_ft16 = {}
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'''4处同名: (1)barcode原始图像文件夹; (2)imgPath中的 .pickle 文件名、该pickle文件中字典的key值'''
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k = 0
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for filename in os.listdir(imgPath):
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bcd, ext = os.path.splitext(filename)
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pkpath = os.path.join(featPath, f"{bcd}.pickle")
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if os.path.isfile(pkpath): continue
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if bcdSet is not None and bcd not in bcdSet:
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continue
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filepath = os.path.join(imgPath, filename)
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stdbDict = {}
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stdbDict_ft16 = {}
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stdbDict_uint8 = {}
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@ -399,12 +405,8 @@ def stdfeat_infer(imgPath, featPath, bcdSet=None):
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# uint8, 两种策略，1) 精度损失小, 2) 计算复杂度小
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# stdfeat_uint8, _ = ft16_to_uint8(feature_ft16)
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stdfeat_uint8 = (feature_ft16*128).astype(np.int8)
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except Exception as e:
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print(f"Error accured at: {filename}, with Exception is: {e}")
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@ -414,33 +416,30 @@ def stdfeat_infer(imgPath, featPath, bcdSet=None):
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stdbDict["imgpaths"] = imgpaths
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stdbDict["feats"] = feature
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pkpath = os.path.join(featPath, f"{barcode}.pickle")
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# pkpath = os.path.join(featPath, f"{barcode}.pickle")
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with open(pkpath, 'wb') as f:
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pickle.dump(stdbDict, f)
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pickle.dump(stdbDict, f)
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stdBarcodeDict[barcode] = feature
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##================== float16
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stdbDict_ft16["barcode"] = barcode
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stdbDict_ft16["imgpaths"] = imgpaths
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stdbDict_ft16["feats"] = feature_ft16
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pkpath_ft16 = os.path.join(featPath, f"{barcode}_ft16.pickle")
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with open(pkpath_ft16, 'wb') as f:
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pickle.dump(stdbDict_ft16, f)
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stdBarcodeDict_ft16[barcode] = pkpath_ft16
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# stdbDict_ft16["barcode"] = barcode
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# stdbDict_ft16["imgpaths"] = imgpaths
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# stdbDict_ft16["feats"] = feature_ft16
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# pkpath_ft16 = os.path.join(featPath, f"{barcode}_ft16.pickle")
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# with open(pkpath_ft16, 'wb') as f:
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# pickle.dump(stdbDict_ft16, f)
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# stdBarcodeDict_ft16[barcode] = pkpath_ft16
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##================== uint8
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stdbDict_uint8["barcode"] = barcode
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stdbDict_uint8["imgpaths"] = imgpaths
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stdbDict_uint8["feats"] = stdfeat_uint8
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pkpath_uint8 = os.path.join(featPath, f"{barcode}_uint8.pickle")
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with open(pkpath_uint8, 'wb') as f:
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pickle.dump(stdbDict_uint8, f)
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# stdBarcodeDict_ft16[barcode] = pkpath_ft16
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# stdbDict_uint8["barcode"] = barcode
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# stdbDict_uint8["imgpaths"] = imgpaths
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# stdbDict_uint8["feats"] = stdfeat_uint8
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# pkpath_uint8 = os.path.join(featPath, f"{barcode}_uint8.pickle")
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# with open(pkpath_uint8, 'wb') as f:
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# pickle.dump(stdbDict_uint8, f)
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t2 = time.time()
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print(f"Barcode: {barcode}, need time: {t2-t1:.1f} secs")
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@ -448,7 +447,7 @@ def stdfeat_infer(imgPath, featPath, bcdSet=None):
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# if k == 10:
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# break
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##================== float32
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# pickpath = os.path.join(featPath, f"barcode_features_{k}.pickle")
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# with open(pickpath, 'wb') as f:
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# pickle.dump(stdBarcodeDict, f)
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@ -456,7 +455,7 @@ def stdfeat_infer(imgPath, featPath, bcdSet=None):
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##================== float16
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# pickpath_ft16 = os.path.join(featPath, f"barcode_features_ft16_{k}.pickle")
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# with open(pickpath_ft16, 'wb') as f:
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# pickle.dump(stdBarcodeDict_ft16, f)
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# pickle.dump(stdBarcodeDict_ft16, f)
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return
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@ -477,7 +476,8 @@ def contrast_performance_evaluate(resultPath):
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# ]
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evtList = [(p.stem, p.stem.split('_')[1]) for p in Path(eventFeatPath).iterdir()
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if p.is_file()
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if p.is_file()
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and str(p).find('240910')>0
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and p.suffix=='.pickle'
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and len(p.stem.split('_'))==2
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and p.stem.split('_')[1].isdigit()
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@ -487,7 +487,7 @@ def contrast_performance_evaluate(resultPath):
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barcodes = set([bcd for _, bcd in evtList])
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'''标准特征集图像样本经特征提取并保存，运行一次后无需再运行'''
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# stdfeat_infer(stdBarcodePath, stdFeaturePath, barcodes)
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stdfeat_infer(stdBarcodePath, stdFeaturePath, barcodes)
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'''========= 构建用于比对的标准特征字典 ============='''
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stdDict = {}
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@ -639,6 +639,7 @@ def compute_precise_recall(pickpath):
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file, ext = os.path.splitext(pickfile)
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if ext != '.pickle': return
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if file.find('ft16') < 0: return
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with open(pickpath, 'rb') as f:
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results = pickle.load(f)
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@ -717,7 +718,8 @@ def generate_event_and_stdfeatures():
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'''=========================== 2. 提取并存储事件特征 ========================'''
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eventDatePath = [# r'\\192.168.1.28\share\测试_202406\0723\0723_1',
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eventDatePath = [r'\\192.168.1.28\share\测试_202406\0910\images',
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# r'\\192.168.1.28\share\测试_202406\0723\0723_1',
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# r'\\192.168.1.28\share\测试_202406\0723\0723_2',
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# r'\\192.168.1.28\share\测试_202406\0723\0723_3',
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# r'\\192.168.1.28\share\测试_202406\0722\0722_01',
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@ -751,12 +753,12 @@ def generate_event_and_stdfeatures():
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# break
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## 保存轨迹中 boxes 子图
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# for event in eventList:
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# basename = os.path.basename(event['filepath'])
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# savepath = os.path.join(subimgPath, basename)
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# if not os.path.exists(savepath):
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# os.makedirs(savepath)
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# save_event_subimg(event, savepath)
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for event in eventList:
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basename = os.path.basename(event['filepath'])
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savepath = os.path.join(subimgPath, basename)
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if not os.path.exists(savepath):
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os.makedirs(savepath)
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save_event_subimg(event, savepath)
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print("eventList have generated and features have saved!")
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@ -789,23 +791,23 @@ def ft16_to_uint8(arr_ft16):
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return arr_uint8, arr_ft16_
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def main():
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generate_event_and_stdfeatures()
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# generate_event_and_stdfeatures()
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# contrast_performance_evaluate(resultPath)
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# for filename in os.listdir(resultPath):
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# if filename.find('.pickle') < 0: continue
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# # if filename.find('0909') < 0: continue
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# pickpath = os.path.join(resultPath, filename)
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# compute_precise_recall(pickpath)
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contrast_performance_evaluate(resultPath)
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for filename in os.listdir(resultPath):
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if filename.find('.pickle') < 0: continue
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if filename.find('0911') < 0: continue
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pickpath = os.path.join(resultPath, filename)
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compute_precise_recall(pickpath)
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def main_std():
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std_sample_path = r"\\192.168.1.28\share\已标注数据备份\对比数据\barcode\barcode_500_1979_已清洗"
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std_sample_path = r"\\192.168.1.28\share\已标注数据备份\对比数据\barcode\barcode_500_2192_已清洗"
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std_barcode_path = r"\\192.168.1.28\share\测试_202406\contrast\std_barcodes_2192"
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std_feature_path = r"\\192.168.1.28\share\测试_202406\contrast\std_features_2192_ft32vsft16"
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@ -824,7 +826,8 @@ def main_std():
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# print("done")
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if __name__ == '__main__':
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main()
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# main()
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# main_std()
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