Update app.py

app.py

@@ -168,7 +168,7 @@ def process_video(video_path, process_seconds=20, conf_threshold=0.2, max_det=8)
     
     pbar.close()  # 关闭进度条
     video_writer.release()
-    logger.info(f"视频处��完成，共处理 {frame_count} 帧")
+    logger.info(f"视频处理完成，共处理 {frame_count} 帧")
 
     # 生成分析报告
     confidences = [float(det['confidence'].strip('%'))/100 for info in detection_info for det in info['detections']]
@@ -299,7 +299,7 @@ def process_video(video_path, process_seconds=20, conf_threshold=0.2, max_det=8)
     base_trajectory = np.zeros((height, width, 3), dtype=np.uint8) + 255
     base_heatmap = np.zeros((height, width), dtype=np.float32)
     
-    frame_interval = max(1, len(filtered_points) // 50)
+    frame_interval = max(1, len(filtered_points) // 30)
     
     for i in range(0, len(filtered_points), frame_interval):
         current_points = filtered_points[:i+1]
@@ -343,6 +343,10 @@ def process_video(video_path, process_seconds=20, conf_threshold=0.2, max_det=8)
     trajectory_path = output_path.replace('.mp4', '_trajectory.png')
     heatmap_path = output_path.replace('.mp4', '_heatmap.png')
     cv2.imwrite(trajectory_path, trajectory_img)
+    if np.max(heatmap) > 0:
+        heatmap_normalized = cv2.normalize(heatmap, None, 0, 255, cv2.NORM_MINMAX)
+        heatmap_colored = cv2.applyColorMap(heatmap_normalized.astype(np.uint8), cv2.COLORMAP_JET)
+        heatmap_colored = cv2.addWeighted(heatmap_colored, 0.7, np.full_like(heatmap_colored, 255), 0.3, 0)
     cv2.imwrite(heatmap_path, heatmap_colored)
     
     logger.info("轨迹图和热力图生成完成")
@@ -490,4 +494,15 @@ with gr.Blocks() as demo:
     )
 
 if __name__ == "__main__":
+    try:
+        # GPU相关操作
+        if torch.cuda.is_available():
+            logger.info("使用GPU进行轨迹和热力图计算")
+            # ... GPU操作 ...
+        else:
+            logger.info("使用CPU进行轨迹和热力图计算")
+            # ... CPU操作 ...
+    except Exception as e:
+        logger.error(f"处理轨迹和热力图时出错: {str(e)}")
+        raise
     demo.launch(server_name="0.0.0.0", server_port=7860)