app.py

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)):

    progress(1.0, desc="Step 0: Starting")
    output_path, output_video = gr_video2mc(video, progress)

    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.queue(concurrency_count=10).launch()