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https://github.com/HumanAIGC-Engineering/gradio-webrtc.git
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20
README.md
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README.md
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<a href="https://github.com/freddyaboulton/gradio-webrtc" target="_blank"><img alt="Static Badge" style="display: block; padding-right: 5px; height: 20px;" src="https://img.shields.io/badge/github-white?logo=github&logoColor=black"></a>
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<a href="https://freddyaboulton.github.io/gradio-webrtc/" target="_blank"><img alt="Static Badge" src="https://img.shields.io/badge/Docs-ffcf40"></a>
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</div>
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<div align="center">
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<strong>中文|<a href="./README_en.md">English</a></strong>
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</div>
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<h3 style='text-align: center'>
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Stream video and audio in real time with Gradio using WebRTC.
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本仓库是从原有的 gradio_webrtc 仓库 fork 而来,主要增加了`video_chat`作为允许的入参,并默认开启,这个模式和原有的`modality="audio-video"`且`mode="send-receive"`的行为保持一致,但重写了 UI 部分,增加了更多的交互能力(更多的麦克风操作,同时展示本地视频信息),其视觉表现如下图。
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如果手动将`video_chat`参数设置为`False`,则其用法与原仓库保持一致 https://freddyaboulton.github.io/gradio-webrtc/
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</h3>
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## Installation
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```bash
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## Examples
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使用时需要一个 handler 作为组件的入参,并实现类似以下代码:
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```python
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import asyncio
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import base64
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output_frame_size=self.output_frame_size,
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)
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#处理客户端上传的视频数据
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async def video_receive(self, frame: np.ndarray):
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newFrame = np.array(frame)
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newFrame[0:, :, 0] = 255 - newFrame[0:, :, 0]
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self.video_queue.put_nowait(newFrame)
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#准备服务端下发的视频数据
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async def video_emit(self) -> VideoEmitType:
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return await self.video_queue.get()
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#处理客户端上传的音频数据
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async def receive(self, frame: tuple[int, np.ndarray]) -> None:
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frame_size, array = frame
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self.audio_queue.put_nowait(array)
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#准备服务端下发的音频数据
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async def emit(self) -> AudioEmitType:
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if not self.args_set.is_set():
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await self.wait_for_args()
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@@ -140,8 +148,8 @@ if __name__ == "__main__":
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## Deployment
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When deploying in a cloud environment (like Hugging Face Spaces, EC2, etc), you need to set up a TURN server to relay the WebRTC traffic.
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The easiest way to do this is to use a service like Twilio.
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在云环境中部署(例如 huggingface,EC2 等)时,您需要设置转向服务器以中继 WEBRTC 流量。
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最简单的方法是使用 Twilio 之类的服务。国内部署需要寻找适合的替代方案。
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```python
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from twilio.rest import Client
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