Update app.py

app.py

@@ -9,6 +9,7 @@ import numpy as np
 import cv2
 from pathlib import Path
 import tempfile
+import imageio
 
 # 从环境变量获取密码
 APP_USERNAME = "admin"  # 用户名保持固定
@@ -295,13 +296,66 @@ def process_video(video_path, process_seconds=20, conf_threshold=0.2, max_det=8)
         alpha = 0.7
         heatmap_colored = cv2.addWeighted(heatmap_colored, alpha, np.full_like(heatmap_colored, 255), 1-alpha, 0)
     
+    # 准备GIF动画帧
+    trajectory_frames = []
+    heatmap_frames = []
+    
+    # 创建基础图像
+    base_trajectory = np.zeros((height, width, 3), dtype=np.uint8) + 255
+    base_heatmap = np.zeros((height, width), dtype=np.float32)
+    
+    # 每N帧生成一个动画帧
+    frame_interval = max(1, len(filtered_points) // 50)  # 控制GIF帧数
+    
+    for i in range(0, len(filtered_points), frame_interval):
+        current_points = filtered_points[:i+1]
+        
+        # 轨迹动画帧
+        frame_trajectory = base_trajectory.copy()
+        if len(current_points) > 1:
+            points = np.array(current_points, dtype=np.int32)
+            for j in range(len(points) - 1):
+                ratio = j / (len(points) - 1)
+                color = (
+                    int((1 - ratio) * 255),  # B
+                    50,                       # G
+                    int(ratio * 255)          # R
+                )
+                cv2.line(frame_trajectory, tuple(points[j]), tuple(points[j + 1]), color, 2)
+            
+            # 绘制当前位置点
+            cv2.circle(frame_trajectory, tuple(points[-1]), 8, (0, 0, 255), -1)
+        trajectory_frames.append(frame_trajectory)
+        
+        # 热图动画帧
+        frame_heatmap = base_heatmap.copy()
+        for x, y in current_points:
+            if 0 <= x < width and 0 <= y < height:
+                temp_heatmap = np.zeros((height, width), dtype=np.float32)
+                temp_heatmap[y, x] = 1
+                temp_heatmap = cv2.GaussianBlur(temp_heatmap, (31, 31), 10)
+                frame_heatmap += temp_heatmap
+        
+        if np.max(frame_heatmap) > 0:
+            frame_heatmap_norm = cv2.normalize(frame_heatmap, None, 0, 255, cv2.NORM_MINMAX)
+            frame_heatmap_color = cv2.applyColorMap(frame_heatmap_norm.astype(np.uint8), cv2.COLORMAP_JET)
+            frame_heatmap_color = cv2.addWeighted(frame_heatmap_color, 0.7, np.full_like(frame_heatmap_color, 255), 0.3, 0)
+            heatmap_frames.append(frame_heatmap_color)
+
+    # 保存GIF动画
+    trajectory_gif_path = output_path.replace('.mp4', '_trajectory_animation.jpg')  # 实际是GIF但用jpg后缀
+    heatmap_gif_path = output_path.replace('.mp4', '_heatmap_animation.jpg')  # 实际是GIF但用jpg后缀
+    
+    imageio.mimsave(trajectory_gif_path, trajectory_frames, duration=50)  # 50ms per frame
+    imageio.mimsave(heatmap_gif_path, heatmap_frames, duration=50)
+    
     # 保存图像
     trajectory_path = output_path.replace('.mp4', '_trajectory.png')
     heatmap_path = output_path.replace('.mp4', '_heatmap.png')
     cv2.imwrite(trajectory_path, trajectory_img)
     cv2.imwrite(heatmap_path, heatmap_colored)
     
-    return output_path, trajectory_path, heatmap_path, report
+    return output_path, trajectory_path, heatmap_path, trajectory_gif_path, heatmap_gif_path, report
 
 # 创建 Gradio 界面
 with gr.Blocks() as demo:
@@ -347,14 +401,17 @@ with gr.Blocks() as demo:
                 video_output = gr.Video(label="检测结果")
                 with gr.Row():
                     trajectory_output = gr.Image(label="运动轨迹")
+                    trajectory_gif_output = gr.Image(label="轨迹动画")
+                with gr.Row():
                     heatmap_output = gr.Image(label="热力图")
+                    heatmap_gif_output = gr.Image(label="热力图动画")
                 report_output = gr.Textbox(label="分析报告")
         
         gr.Markdown("""
         ### 使用说明
         1. 上传视频文件
         2. 设置处理参数：
-           - 处理时长：需要分析的视频时长（秒��
+           - 处理时长：需要分析的视频时长（秒
            - 置信度阈值：检测的置信度要求（越高越严格）
            - 最大检测数量：每帧最多检测的目标数量
         3. 等待处理完成
@@ -378,7 +435,8 @@ with gr.Blocks() as demo:
     process_btn.click(
         fn=process_video,
         inputs=[video_input, process_seconds, conf_threshold, max_det],
-        outputs=[video_output, trajectory_output, heatmap_output, report_output]
+        outputs=[video_output, trajectory_output, heatmap_output, 
+                trajectory_gif_output, heatmap_gif_output, report_output]
     )
 
 if __name__ == "__main__":