update the UI

app.py

@@ -2,6 +2,9 @@ import gradio as gr
 from videopose_PSTMO import gr_video2mc
 import os
 
+# ffmpeg -i input_videos/kun_1280x720_30fps_0-14_0-32.mp4 -vf trim=0:5,setpts=PTS-STARTPTS input_videos/kun_test_5sec.mp4
+# ffmpeg -i input.mp4 -vf scale=320:-1 output.mp4
+
 
 def Video2MC(video, progress=gr.Progress(track_tqdm=True)):
 
@@ -10,13 +13,34 @@ def Video2MC(video, progress=gr.Progress(track_tqdm=True)):
 
     return output_path, output_path, output_video
 
+with gr.Blocks() as iface:
+
+    text1 = gr.Markdown(
+                        """
+                        <div align=center>
+                        <img src="https://github.com/Balloon-356/Video2MC/assets/114230565/2622c7b7-7b5d-458c-bd9a-dc0be37af370" />
+                        """
+                        # </div>
+                        # <h1 align="center">Video2MC: 基于3D人体姿态估计的MC动画自动生成</h1>
+                        )
+    
+    with gr.Row():
+
+        with gr.Column():
+            input_video = gr.Video()
+            with gr.Row():
+                btn_c = gr.ClearButton(input_video)
+                btn_s = gr.Button("Submit", variant='primary')
+            gr.Examples([os.path.join(os.path.dirname(__file__), 
+                    "input_videos/kun_test_5sec.mp4")], input_video)
+            
+        with gr.Column():
+            output_miframes = gr.File()
+            output_path = gr.Text()
+            output_video = gr.Video()
+        
+        
+    btn_s.click(Video2MC, inputs=[input_video], outputs=[output_miframes, output_path, output_video])
     
-iface = gr.Interface(fn=Video2MC, 
-                     inputs=gr.Video(), 
-                     outputs=["file", "text", gr.Video()],
-                     examples=[os.path.join(os.path.dirname(__file__), 
-                                     "input_videos/kun_test_5sec.mp4")], 
-                     cache_examples=False,
-                     )
 
 iface.queue(concurrency_count=10).launch()