Update app.py

app.py

@@ -103,14 +103,22 @@ def process_video(video_path, process_seconds=20, conf_threshold=0.2, max_det=8)
             for kpts in r.keypoints:
                 if isinstance(kpts, torch.Tensor):
                     kpts = kpts.cpu().numpy()
-                # 使用第一个关键点（比如头部）作为位置参考
-                if len(kpts) > 0:
-                    pos = kpts[0][:2]  # 取x,y坐标
-                    all_positions.append(pos)
-                    # 更新热图
-                    x, y = int(pos[0]), int(pos[1])
-                    if 0 <= x < width and 0 <= y < height:
-                        heatmap[y, x] += 1
+                # 打印关键点格式以便调试
+                # print(f"Keypoints shape: {kpts.shape}")
+                
+                # 确保关键点数据是正确的格式
+                if isinstance(kpts, np.ndarray):
+                    if len(kpts.shape) == 2:  # [n_points, 2/3]
+                        if kpts.shape[0] > 0:  # 确保有关键点
+                            # 使用第一个关键点
+                            if kpts.shape[1] >= 2:  # 确保有x,y坐标
+                                x, y = kpts[0, 0], kpts[0, 1]
+                                if isinstance(x, (int, float)) and isinstance(y, (int, float)):
+                                    x, y = int(x), int(y)
+                                    all_positions.append([x, y])
+                                    # 更新热图
+                                    if 0 <= x < width and 0 <= y < height:
+                                        heatmap[y, x] += 1
         
         # 收集检测信息
         frame_info = {