增加测试维度

gift_demo.py

@@ -5,7 +5,7 @@ from ultralytics import YOLOv10
 import cv2
 import torch
 
-from ultralytics.utils.show_trace_pr import ShowPR
+from ultralytics.utils.show_pr import ShowPR
 # from trace_detect import run, _init_model
 import numpy as np
 image_ext = [".jpg", ".jpeg", ".webp", ".bmp", ".png"]
@@ -43,7 +43,7 @@ def get_image_list(path):
 
 
 def _init():
-    model = YOLOv10('runs/detect/train/weights/best_gift_v10n.pt')
+    model = YOLOv10('ckpts/20250620/best_gift_v10n.pt')
     return model
 
 
@@ -72,6 +72,7 @@ def get_trace_event(model, path):
 
 def main(path):
     model = _init()
+    tags_tmp, result_all_tmp = [], []
     tags, result_all = [], []
     classify = ['commodity', 'gift']
     for cla in classify:
@@ -79,12 +80,15 @@ def main(path):
         for root, dirs, files in os.walk(pre_pth):
             if not dirs:
                 if cla == 'commodity':
-                    tags.append(0)
+                    tags_tmp.append(0)
                 else:
-                    tags.append(1)
+                    tags_tmp.append(1)
                 res_single = get_trace_event(model, root)
-                result_all.append(res_single)
+                result_all_tmp.append(res_single)
-    spr = ShowPR(tags, result_all, title_name='yolov10n')
+    for tag, result in zip(tags_tmp, result_all_tmp):
+        tags += [tag]*len(result)
+        result_all += result
+    spr = ShowPR(tags, result_all, title_name='yolov10n', )
     # spr.change_precValue()
     spr.get_pic()
 

pipline_test/read_trackdata_filter.py

@@ -49,10 +49,14 @@ def read_tracking_output(filepath):
                     break
                     
             if start_idx != -1 and end_idx != -1:
+                content = []
                 for i in range(start_idx, end_idx):
                     line = lines[i].strip()
                     if line:
-                        gift_data.append(line)
+                        content.append(line)
+                # 将所有内容合并成一行字符串
+                if content:
+                    gift_data.append(' '.join(content))
         except Exception as e:
             print(f"Error extracting gift data: {e}")
 
@@ -63,28 +67,13 @@ def read_tracking_output(filepath):
 
 
 def extract_data_realtime(datapath):
-    boxes, feats = [], []
+    boxes, feats, gift_data = read_tracking_output(datapath)
-    tracker_feats = {}
+    
-    with open(datapath, 'r', encoding='utf-8') as lines:
+    if not boxes or not feats:
-        for line in lines:
+        return np.array([]), {}, []
-            line = line.strip()  # 去除行尾的换行符和可能的空白字符
+        
-            if not line:  # 跳过空行
+    trackerboxes = boxes[0]  # 因为read_tracking_output返回的是list中的numpy数组
-                continue
+    trackerfeats = feats[0]
-
-            if line.endswith(','):
-                line = line[:-1]
-            ftlist = [float(x) for x in line.split()]
-
-            if len(ftlist) != 265:
-                continue
-            boxes.append(ftlist[:9])
-            feats.append(ftlist[9:])
-
-    trackerboxes = np.array(boxes)
-    trackerfeats = np.array(feats)
-
-    if len(trackerboxes) == 0 or len(trackerboxes) != len(trackerfeats):
-        return np.array([]), {}
 
     frmIDs = np.sort(np.unique(trackerboxes[:, 7].astype(int)))
     for fid in frmIDs:
@@ -373,9 +362,15 @@ for event in os.listdir(video_path):
         # print('imgfile_list', imgfile_list)
         for track_data in track_list:
             track_path = os.path.join(event_path, track_data)
-            boxes, feat = extract_data_realtime(track_path)
+            boxes, feat, gift_data = extract_data_realtime(track_path)
             camera_id = track_data.split('_')[0]
             imgfile = [x for x in imgfile_list if x.split('_')[0] == camera_id][0]
+            
+            # 打印gift数据
+            if gift_data:
+                print(f"\nGift data for {event}/{track_data}:")
+                print(gift_data[0])  # 现在gift_data只包含一个元素，即合并后的字符串
+                    
             if len(boxes) > 0:
                 if del_staticBox:   ##根据距离删除box
                     boxes_ = compute_box_dist(boxes)

trace_demo.py

@@ -43,7 +43,7 @@ def get_image_list(path):
 
 
 def _init():
-    model = YOLOv10('ckpts/20250514/best_gift_v10n.pt')
+    model = YOLOv10('ckpts/20250620/best_gift_v10n.pt')
     return model
 
 

train.py

@@ -17,5 +17,5 @@ model = YOLOv10('ckpts/weights/yolov10n.pt')
 #model.train(data='coco.yaml', epochs=1, batch=64, imgsz=640)
 #model.train(data='coco128_cls10_0924.yaml', epochs=300, batch=64, imgsz=640, resume=False)
 #model.train(data='coco128_cls10_1010.yaml', epochs=300, batch=128, imgsz=640, resume=False)
-model.train(data='gift.yaml', epochs=400, batch=32, imgsz=224, resume=False, save_dir='/ckpts')
+model.train(data='gift.yaml', epochs=600, batch=32, imgsz=224, resume=False, save_dir='/ckpts')
 #model.train(data='coco128_cls10_1010_1205.yaml', epochs=300, batch=32, imgsz=640, resume=True)

ultralytics/utils/show_pr.py

@@ -0,0 +1,109 @@
+import os.path
+import os
+import matplotlib.pyplot as plt
+import numpy as np
+
+
+# [tag, bandage, null]
+# [0, 1, 2]
+class ShowPR:
+    def __init__(self, tags, prec_value, title_name=None):
+        self.tags = tags
+        self.prec_value = prec_value
+        self.thres = [i * 0.01 for i in range(101)]
+        self.title_name = title_name
+
+    def change_precValue(self, thre=0.5):
+        values = []
+        for i in range(len(self.prec_value)):
+            value = []
+            for j in range(len(self.prec_value[i])):
+                if self.prec_value[i][j] > thre:
+                    value.append(1)
+                else:
+                    value.append(0)
+            values.append(value)
+        return values
+
+    def _calculate_pr(self, prec_value):
+        FN, FP, TN, TP = 0, 0, 0, 0
+        for output, target in zip(prec_value, self.tags):
+            # print("output >> {} , target >> {}".format(output, target))
+            if output != target:
+                if target == 0:
+                    FP += 1
+                elif target == 1:
+                    FN += 1
+            else:
+                if target == 0:
+                    TN += 1
+                elif target == 1:
+                    TP += 1
+        if TP == 0:
+            prec, recall = 0, 0
+        else:
+            prec = TP / (TP + FP)
+            recall = TP / (TP + FN)
+        if TN == 0:
+            tn_prec, tn_recall = 0, 0
+        else:
+            tn_prec = TN / (TN + FN)
+            tn_recall = TN / (TN + FP)
+            # print("TP>>{}, FP>>{}, TN>>{}, FN>>{}".format(TP, FP, TN, FN))
+        return prec, recall, tn_prec, tn_recall
+
+    def calculate_multiple(self):
+        recall, recall_TN, PrecisePos, PreciseNeg = [], [], [], []
+        for thre in self.thres:
+            # prec_value = []
+            # if self.prec_value >= thre:
+            #     prec_value.append(1)
+            # else:
+            #     prec_value.append(0)
+            prec_value = [1 if num >= thre else 0 for num in self.prec_value]
+            prec, recall_pos, tn_prec, tn_recall = self._calculate_pr(prec_value)
+            print(
+                f"thre>>{thre:.2f},  recall>>{recall_pos:.4f},  precise_pos>>{prec:.4f},  recall_tn>>{tn_recall:.4f},  precise_neg>>{tn_prec:4f}")
+            PrecisePos.append(prec)
+            recall.append(recall_pos)
+            PreciseNeg.append(tn_prec)
+            recall_TN.append(tn_recall)
+        return recall, recall_TN, PrecisePos, PreciseNeg
+
+    def write_results_to_file(self, recall, recall_TN, PrecisePos, PreciseNeg):
+        file_path = os.sep.join(['./ckpts/tracePR', self.title_name + '.txt'])
+        with open(file_path, 'w') as file:
+            file.write("threshold,   recall,   recall_TN,   PrecisePos,   PreciseNeg\n")
+            for thre, rec, rec_tn, prec_pos, prec_neg in zip(self.thres, recall, recall_TN, PrecisePos, PreciseNeg):
+                file.write(
+                    f"thre>>{thre:.2f},  recall>>{rec:.4f},  precise_pos>>{prec_pos:.4f},  recall_tn>>{rec_tn:.4f},  precise_neg>>{prec_neg:4f}\n")
+
+    def show_pr(self, recall, recall_TN, PrecisePos, PreciseNeg):
+        # self.calculate_multiple()
+        x = self.thres
+        plt.figure(figsize=(10, 6))
+        plt.plot(x, recall, color='red', label='recall:TP/TPFN')
+        plt.plot(x, recall_TN, color='black', label='recall_TN:TN/TNFP')
+        plt.plot(x, PrecisePos, color='blue', label='PrecisePos:TP/TPFN')
+        plt.plot(x, PreciseNeg, color='green', label='PreciseNeg:TN/TNFP')
+        plt.legend()
+        plt.xlabel('threshold')
+        # if self.title_name is not None:
+        #     plt.title(f"PrecisePos & Recall  ratio:{ratio:.2f}", fontdict={'fontsize': 12, 'fontweight': 'black'})
+        # plt.grid(True, linestyle='--', alpha=0.5)
+        # 启用次刻度
+        # plt.minorticks_on()
+
+        # 设置主刻度的网格线
+        plt.grid(which='major', linestyle='-', alpha=0.5, color='gray')
+
+        # 设置次刻度的网格线
+        plt.grid(which='minor', linestyle=':', alpha=0.3, color='gray')
+        plt.savefig(os.sep.join(['./ckpts/tracePR', self.title_name + '.png']))
+        plt.show()
+        plt.close()
+        self.write_results_to_file(recall, recall_TN, PrecisePos, PreciseNeg)
+
+    def get_pic(self):
+        recall, recall_TN, PrecisePos, PreciseNeg = self.calculate_multiple()
+        self.show_pr(recall, recall_TN, PrecisePos, PreciseNeg)

ultralytics/utils/show_trace_pr.py

@@ -110,7 +110,7 @@ class ShowPR:
     def get_pic(self):
         for ratio in self.ratios:
             # ratio = 0.5
-            if ratio < 0.2 or ratio > 0.95:
+            if ratio < 0.1 or ratio > 0.95:
                 continue
             recall, recall_TN, PrecisePos, PreciseNeg = self.calculate_multiple(ratio)
             self.show_pr(recall, recall_TN, PrecisePos, PreciseNeg, ratio)