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merge_imgs
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@ -389,6 +389,7 @@ class ConfusionMatrix:
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cls = detect_cur_cpu[5]
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c = int(cls)
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label = f'{names[c]} {conf:.2f} iou:{float(iou):.2f}'
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print(">>>>>>>>>>>>>>>>>>> label: {} C: {}".format(label, c))
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if fp_flag:
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annotator.box_label(xyxy, label, color=(125, 0, 125)) ##fp iou匹配上,类别错误 紫色框
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else:
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@ -465,7 +466,7 @@ class ConfusionMatrix:
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annotators_tp = self.create_annotator(images_tp, Annotator, names)
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annotators_all = self.create_annotator(images_all, Annotator, names)
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### 新建不同检测类别保存的文件夹,文件夹名称为类别索引
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date_path = 'confusion_0717_cls10_' + str(self.iou_thres)
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date_path = 'confusion_gift_cls4_' + str(self.iou_thres)
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paths_fn = self.makdirs_file(date_path, img_name, self.nc, str_c='FN')
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paths_fp = self.makdirs_file(date_path, img_name, self.nc, str_c='FP')
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paths_fp_bg = self.makdirs_file(date_path, img_name, self.nc, str_c='FP_bg')
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@ -485,7 +486,7 @@ class ConfusionMatrix:
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cls_flag_list_tp = [False for _ in range(self.nc)] ###混淆矩阵斜对角线上类别flag
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## 混淆矩阵可视化 flag 设置
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save_oneImg = False ### 将所有pred_box与gt_box匹配结果画在一张图片上
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save_oneImg = True #pred_box与gt_box匹配结果画在一张图片上
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save_byClass = True ### 将所有pred_box与gt_box匹配结果按box类别分类保存,其中tp、fn、fp按gt_box类别划分,fp_bg按pred_box划分
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cls_flag_list = []
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###=========================
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