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| 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 | |
| Count = 0 | |
| def Video2MC(video, progress=gr.Progress(track_tqdm=True)): | |
| progress(1.0, desc="Step 0: Starting") | |
| output_path, output_video = gr_video2mc(video, progress) | |
| global Count | |
| Count += 1 | |
| print(f"Count: {Count}") | |
| return output_path, output_path, output_video | |
| with gr.Blocks() as iface: | |
| text1 = gr.Markdown( | |
| f""" | |
| <div align=center> | |
|  | |
| </div> | |
| """ | |
| ) | |
| with gr.Tab("English"): | |
| text2 = gr.Markdown( | |
| """ | |
| <h1 align="center">Video2MC: 3D-HPE based Mine-imator animation generation</h1> | |
| ## Introduction | |
| Using computer vision algorithms, I have achieved cost-effective "motion capture," and I am now officially releasing the Video2MC algorithm for automatic generation of Mine-imator animations! | |
| Before using, it is **highly recommended** to watch my [introductory video](https://www.bilibili.com/video/BV1SP411W7pw), as it will help you quickly understand what this project is about. | |
| Enjoy it! | |
| """ | |
| ) | |
| with gr.Accordion("Related Links", open=False): | |
| text_req = gr.Markdown( | |
| """ | |
| ## Related Links | |
| Github: https://github.com/Balloon-356/Video2MC | |
| My Bilibili (Contact): https://space.bilibili.com/244384103 | |
| **Introductory video:** https://www.bilibili.com/video/BV1SP411W7pw | |
| Implementation details: https://www.bilibili.com/read/cv25704198 | |
| """ | |
| ) | |
| with gr.Accordion("How to Use", open=False): | |
| text_req = gr.Markdown( | |
| """ | |
| ## How to Use | |
| 1. Upload a video by dragging it into the box on the bottom left. The video must meet the **requirements**. | |
| 2. Click "Submit", and the algorithm will start running. Please wait patiently, and you can see the current progress in the box on the right. (A 5s video takes about 5min.) | |
| 3. Algorithm finished. You can download the .miframes file and preview the video rendered by the 3D-HPE algorithm (for previewing motion capture results). | |
| 4. Import the .miframes file into the Mine-imator to create a Minecraft animation (you can learn how to use it on the Mine-imator forums). | |
| 5. Fine-tune the motions of the skeleton model in Mine-imator. | |
| """ | |
| ) | |
| with gr.Accordion("Video Requirements", open=False): | |
| text_req = gr.Markdown( | |
| """ | |
| ## Video Requirements | |
| 1. Please upload short videos, preferably not exceeding 10 seconds. (Otherwise, the algorithm will run for several tens of mins and it still works.) | |
| 2. The video should only contain one person, positioned at the center of the frame, fully visible from head to toe, facing the camera. | |
| 3. Just as shown in the "example" below. | |
| """ | |
| ) | |
| 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]) | |
| with gr.Tab("中文"): | |
| text2 = gr.Markdown( | |
| """ | |
| <h1 align="center">Video2MC：基于3D-HPE的MC动画自动生成</h1> | |
| ## 简单介绍 | |
| 利用计算机视觉算法，我实现了低成本“动作捕捉”，在此正式发布MC动画自动生成算法Video2MC！ | |
| 使用前，强烈建议先观看我的[B站视频](https://www.bilibili.com/video/BV1SP411W7pw)，快速了解该项目的用法。 | |
| 注：目前使用的是CPU，代码运行较慢。GPU算力过于昂贵，若有需求请私信联系。 | |
| """ | |
| ) | |
| with gr.Accordion("相关链接", open=False): | |
| text_req = gr.Markdown( | |
| """ | |
| ## 相关链接 | |
| Github项目：https://github.com/Balloon-356/Video2MC | |
| B站帐号（私信联系）：https://space.bilibili.com/244384103 | |
| **介绍视频：** https://www.bilibili.com/video/BV1SP411W7pw | |
| 实现原理：https://www.bilibili.com/read/cv25704198 | |
| """ | |
| ) | |
| with gr.Accordion("使用说明", open=False): | |
| text_req = gr.Markdown( | |
| """ | |
| ## 使用说明 | |
| 1. 上传一段视频（拖入下方左侧的框中）。视频需要满足“视频要求”。 | |
| 2. 点击“Submit”提交视频，此时算法开始运行。请耐心等待，右侧的框中将显示算法运行的进度。（5s的视频大约需要5分钟） | |
| 3. 运行结束。可以在右侧的框中下载.miframes文件，并且可以通过算法渲染得到的骨架动作视频预览效果。 | |
| 4. 将.miframes文件导入到Mine-imator软件中，生成一段动画。（导入方法可在互联网上查询） | |
| 5. 微调人物动作，导出动画。 | |
| """ | |
| ) | |
| with gr.Accordion("视频要求", open=False): | |
| text_req = gr.Markdown( | |
| """ | |
| ## 视频要求 | |
| 1. 请尽量上传时长较短的视频（10s内最好），否则算法将运行很长时间。 | |
| 2. 视频中应该只包含一个人，且人位于视频中心、全身完整地出现在视频中，面向相机。 | |
| 3. 如"example"中展示的视频一样。 | |
| """ | |
| ) | |
| 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() |