app update

app.py

@@ -163,14 +163,9 @@ def check_online():
 def model_loading(img_path, conf, iou, infer_size, yolo_model="yolov8n.pt"):
     model = YOLO(yolo_model)
 
-    results = model.predict(source=img_path, imgsz=infer_size, conf=conf, iou=iou, return_outputs=True)
-    det = []
-    for i in results:
-        det.append(deepcopy(i))
-
-    det_list = det[0]["det"].tolist()
-
-    return det_list
+    results = model(source=img_path, imgsz=infer_size, conf=conf, iou=iou)
+    results = list(results)[0]
+    return results
 
 
 # 标签和边界框颜色设置
@@ -246,12 +241,15 @@ def yolo_det_img(img_path, model_name, infer_size, conf, iou):
     cls_index_det_stat = []  # 类别索引统计
 
     # 模型加载
-    predict_list = model_loading(img_path, conf, iou, infer_size, yolo_model=f"{model_name}.pt")
+    predict_results = model_loading(img_path, conf, iou, infer_size, yolo_model=f"{model_name}.pt")
+    xyxy_list = predict_results.boxes.xyxy.cpu().numpy().tolist()
+    conf_list = predict_results.boxes.conf.cpu().numpy().tolist()
+    cls_list = predict_results.boxes.cls.cpu().numpy().tolist()
 
     color_list = random_color(len(model_cls_name_cp), True)
 
     # 判断检测对象是否为空
-    if (predict_list != []):
+    if (xyxy_list != []):
 
         # ---------------- 加载字体 ----------------
         yaml_index = cls_name.index(".yaml")
@@ -267,23 +265,23 @@ def yolo_det_img(img_path, model_name, infer_size, conf, iou):
             # 韩语
             textFont = ImageFont.truetype(str(f"{ROOT_PATH}/fonts/malgun.ttf"), size=FONTSIZE)
 
-        for i in range(len(predict_list)):
+        for i in range(len(xyxy_list)):
             # id = int(i)  # 实例ID
-            obj_cls_index = int(predict_list[i][5])  # 类别索引
+            obj_cls_index = int(cls_list[i])  # 类别索引
             cls_index_det_stat.append(obj_cls_index)
 
             obj_cls = model_cls_name_cp[obj_cls_index]  # 类别
             cls_det_stat.append(obj_cls)
 
             # ------------ 边框坐标 ------------
-            x0 = int(predict_list[i][0])
-            y0 = int(predict_list[i][1])
-            x1 = int(predict_list[i][2])
-            y1 = int(predict_list[i][3])
+            x0 = int(xyxy_list[i][0])
+            y0 = int(xyxy_list[i][1])
+            x1 = int(xyxy_list[i][2])
+            y1 = int(xyxy_list[i][3])
 
             bbox_det_stat.append((x0, y0, x1, y1))
 
-            conf = float(predict_list[i][4])  # 置信度
+            conf = float(conf_list[i])  # 置信度
             score_det_stat.append(conf)
 
             # fps = f"{(1000 / float(results.t[1])):.2f}"  # FPS