update

prt/.txt

@@ -78,3 +78,7 @@ R 0.643 0.640 0.629 0.623 0.617 0.613 0.606 0.603 0.593 0.585 0.574 0.571 0.568
 P 0.700 0.710 0.720 0.730 0.740 0.750 0.760 0.770 0.780 0.790 0.800 0.810 0.820 0.830 0.840 0.850 0.860 0.870 0.880 0.890 0.900 0.910 0.920 0.930 0.940 0.950 0.960 0.970 0.980 0.990 
 T 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.006 0.006 0.006 0.007 0.007 0.008 0.009 0.009 0.010 0.013 0.018 0.021 0.023 0.026 0.028 0.035 0.038 0.039 0.042 0.049 0.052 0.065 0.088 
 R 0.984 0.984 0.984 0.984 0.984 0.984 0.984 0.984 0.984 0.984 0.984 0.984 0.984 0.984 0.984 0.984 0.984 0.984 0.984 0.984 0.984 0.984 0.984 0.984 0.984 0.984 0.984 0.984 0.984 0.984 
+0
+P 0.700 0.710 0.720 0.730 0.740 0.750 0.760 0.770 0.780 0.790 0.800 0.810 0.820 0.830 0.840 0.850 0.860 0.870 0.880 0.890 0.900 0.910 0.920 0.930 0.940 0.950 0.960 0.970 0.980 0.990 
+T 0.060 0.063 0.068 0.071 0.077 0.081 0.087 0.091 0.097 0.104 0.109 0.116 0.124 0.130 0.140 0.150 0.160 0.171 0.184 0.196 0.212 0.228 0.247 0.271 0.291 0.315 0.341 0.367 0.411 0.481 
+R 0.918 0.917 0.914 0.912 0.908 0.905 0.903 0.902 0.900 0.898 0.895 0.893 0.890 0.888 0.885 0.881 0.879 0.879 0.876 0.873 0.869 0.866 0.862 0.857 0.853 0.849 0.843 0.835 0.824 0.809 

ultralytics/data/utils.py

@@ -42,7 +42,8 @@ PIN_MEMORY = str(os.getenv("PIN_MEMORY", True)).lower() == "true"  # global pin_
 
 def img2label_paths(img_paths):
     """Define label paths as a function of image paths."""
-    sa, sb = f"{os.sep}images{os.sep}", f"{os.sep}labels{os.sep}"  # /images/, /labels/ substrings
+    # sa, sb = f"{os.sep}images{os.sep}", f"{os.sep}labels{os.sep}"  # /images/, /labels/ substrings
+    sa, sb = f"{os.sep}images{os.sep}", f"{os.sep}labels_class2{os.sep}"  # /images/, /labels/ substrings
     return [sb.join(x.rsplit(sa, 1)).rsplit(".", 1)[0] + ".txt" for x in img_paths]
 
 

ultralytics/models/yolo/detect/val.py

@@ -7,6 +7,7 @@ import cv2
 import numpy as np
 import torch
 
+
 from ultralytics.data import build_dataloader, build_yolo_dataset, converter
 from ultralytics.engine.validator import BaseValidator
 from ultralytics.utils import LOGGER, ops
@@ -145,7 +146,15 @@ class DetectionValidator(BaseValidator):
             # Predictions
             if self.args.single_cls:
                 pred[:, 5] = 0
+            
+            # =======Targets 2 分类======
+            column = pred[:,5]
+            condition2 = (column != 10)
+            pred[:,5][condition2] = 0
+            # ===========================
+
             predn = self._prepare_pred(pred, pbatch)
+
             stat["conf"] = predn[:, 4]
             stat["pred_cls"] = predn[:, 5]
 

ultralytics/utils/img_joint.py

@@ -41,10 +41,10 @@ def merge_imgs(path1, path2, save_path):
 # path1 = 'predict_labels110_0524/'
 # path2 = 'predict_labels110_0613/'
 
-path1 = '/home/lc/ieemoo-ai-gift/confusion_gift_cls4_0.45/FN/FN_3'
+path1 = '/home/lc/ieemoo-ai-gift/confusion_gift_cls2_0.45/FP_bg/FP_bg_1'
-path2 = '/home/lc/ieemoo-ai-gift/confusion_gift_cls4_0.45/allBox/allBox_1'
+path2 = '/home/lc/ieemoo-ai-gift/confusion_gift_cls2_0.45/allBox/allBox_1'
 
 #save_path = '/home/yujia/yj/yolov5-6.1/0518_cls10_v5s_new_delTP0.5/labelFn_5_allBox_merge/'
-save_path = '/home/lc/ieemoo-ai-gift/confusion_gift_cls4_0.45/FN/FN_3_joint/'
+save_path = '/home/lc/ieemoo-ai-gift/confusion_gift_cls2_0.45/FP_bg/FP_bg_1_joint/'
 # os.makedirs(save_path, exist_ok=True)
 merge_imgs(path1, path2, save_path)

val.py

@@ -1,4 +1,4 @@
 from ultralytics import YOLOv10
 
-model = YOLOv10('runs/detect/train/weights/best_gift_v10n.pt')
+model = YOLOv10('/home/lc/ieemoo-ai-gift/runs/detect/train/weights/best_gift_v10n.pt')
 metrics = model.val(batch=1, data='gift.yaml', imgsz=224)