Update app.py

app.py

@@ -13,6 +13,16 @@ app = FastAPI()
 device = 'cuda' if torch.cuda.is_available() else 'cpu'
 model = YOLO('kunin-mice-pose.v0.1.0.pt')
 
+# 添加认证函数
+def auth_user(username, password):
+    # 你可以添加多个用户
+    valid_credentials = {
+        "kunin": "123456",
+        "user1": "password1",
+        # 可以添加更多用户
+    }
+    return username in valid_credentials and valid_credentials[username] == password
+
 @spaces.GPU
 def process_video(video_path, process_seconds=20, conf_threshold=0.2, max_det=8):
     """
@@ -115,36 +125,47 @@ def process_video(video_path, process_seconds=20, conf_threshold=0.2, max_det=8)
     
     return output_path, report
 
-demo = gr.Interface(
-    fn=process_video,
-    inputs=[
-        gr.Video(label="输入视频"),
-        gr.Number(label="处理时长（秒，0表示处理整个视频）", value=20),
-        gr.Slider(
-            minimum=0.1,
-            maximum=1.0,
-            value=0.2,
-            step=0.05,
-            label="置信度阈值",
-            info="越高越严格，建议范围0.2-0.5"
-        ),
-        gr.Slider(
-            minimum=1,
-            maximum=10,
-            value=8,
-            step=1,
-            label="最大检测数量",
-            info="每帧最多检测的目标数量"
-        )
-    ],
-    outputs=[
-        gr.Video(label="检测结果"),
-        gr.Textbox(label="分析报告")
-    ],
-    title="🐁 小鼠行为分析 (Mice Behavior Analysis)",
-    description="上传视频来检测和分析小鼠行为 | Upload a video to detect and analyze mice behavior",
-    auth=("admin", "your_password_here"),  # 添加基本认证
-    article="""
+# 创建 Gradio 界面
+with gr.Blocks() as demo:
+    gr.Markdown("# 🐁 小鼠行为分析 (Mice Behavior Analysis)")
+    gr.Markdown("上传视频来检测和分析小鼠行为 | Upload a video to detect and analyze mice behavior")
+    
+    with gr.Row():
+        with gr.Column():
+            video_input = gr.Video(label="输入视频")
+            process_seconds = gr.Number(
+                label="处理时长（秒，0表示处理整个视频）", 
+                value=20
+            )
+            conf_threshold = gr.Slider(
+                minimum=0.1,
+                maximum=1.0,
+                value=0.2,
+                step=0.05,
+                label="置信度阈值",
+                info="越高越严格，建议范围0.2-0.5"
+            )
+            max_det = gr.Slider(
+                minimum=1,
+                maximum=10,
+                value=8,
+                step=1,
+                label="最大检测数量",
+                info="每帧最多检测的目标数量"
+            )
+            process_btn = gr.Button("开始处理")
+        
+        with gr.Column():
+            video_output = gr.Video(label="检测结果")
+            report_output = gr.Textbox(label="分析报告")
+    
+    process_btn.click(
+        fn=process_video,
+        inputs=[video_input, process_seconds, conf_threshold, max_det],
+        outputs=[video_output, report_output]
+    )
+    
+    gr.Markdown("""
     ### 使用说明
     1. 上传视频文件
     2. 设置处理参数：
@@ -160,8 +181,12 @@ demo = gr.Interface(
     - 处理时间与视频长度和分辨率相关
     - 置信度建议范围：0.2-0.5
     - 最大检测数量建议根据实际场景设置
-    """
-)
+    """)
 
 if __name__ == "__main__":
-    demo.launch(server_name="0.0.0.0", server_port=7860)
+    demo.launch(
+        server_name="0.0.0.0", 
+        server_port=7860,
+        auth=auth_user,
+        auth_message="请输入用户名和密码"
+    )