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README.md
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@@ -5,15 +5,17 @@
<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>
<a href="https://freddyaboulton.github.io/gradio-webrtc/" target="_blank"><img alt="Static Badge" src="https://img.shields.io/badge/Docs-ffcf40"></a>
</div>
<div align="center">
<strong>中文|<a href="./README_en.md">English</a></strong>
</div>
<h3 style='text-align: center'>
Stream video and audio in real time with Gradio using WebRTC.
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。
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/
![picture-in-picture](docs/image.png)
![side-by-side](docs/image2.png)
</h3>
## Installation
```bash
@@ -31,6 +33,8 @@ https://freddyaboulton.github.io/gradio-webrtc/
## Examples
使用时需要一个 handler 作为组件的入参，并实现类似以下代码：
```python
import asyncio
import base64
@@ -84,18 +88,22 @@ class VideoChatHandler(AsyncAudioVideoStreamHandler):
output_frame_size=self.output_frame_size,
)
#处理客户端上传的视频数据
async def video_receive(self, frame: np.ndarray):
newFrame = np.array(frame)
newFrame[0:, :, 0] = 255 - newFrame[0:, :, 0]
self.video_queue.put_nowait(newFrame)
#准备服务端下发的视频数据
async def video_emit(self) -> VideoEmitType:
return await self.video_queue.get()
#处理客户端上传的音频数据
async def receive(self, frame: tuple[int, np.ndarray]) -> None:
frame_size, array = frame
self.audio_queue.put_nowait(array)
#准备服务端下发的音频数据
async def emit(self) -> AudioEmitType:
if not self.args_set.is_set():
await self.wait_for_args()
@@ -140,8 +148,8 @@ if __name__ == "__main__":
## Deployment
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.
The easiest way to do this is to use a service like Twilio.
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。
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。
```python
from twilio.rest import Client

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<h1 style='text-align: center; margin-bottom: 1rem'> Gradio WebRTC ⚡️ </h1>
<div style="display: flex; flex-direction: row; justify-content: center">
<img style="display: block; padding-right: 5px; height: 20px;" alt="Static Badge" src="https://img.shields.io/pypi/v/gradio_webrtc">
<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>
<a href="https://freddyaboulton.github.io/gradio-webrtc/" target="_blank"><img alt="Static Badge" src="https://img.shields.io/badge/Docs-ffcf40"></a>
</div>
<div align="center">
<strong><a href="./README.md">中文</a>|English</strong>
</div>
This repository is forked from the original gradio_webrtc repository, primarily adding `video_chat` as an allowed parameter to be enabled by default. This mode is consistent with the behavior of the original `modality="audio-video"` and `mode="send-receive"`, but the UI has been rewritten to include more interactive capabilities (more microphone controls, and the ability to display local video information). The visual presentation is shown below.
If `video_chat` is manually set to `False`, its usage is consistent with the original repository https://freddyaboulton.github.io/gradio-webrtc/
![picture-in-picture](docs/image.png)
![side-by-side](docs/image2.png)
## Installation
```bash
gradio cc install
gradio cc build --no-generate-docs
```
```bash
pip install dist/gradio_webrtc-0.0.30.dev0-py3-none-any.whl
```
## Docs
https://freddyaboulton.github.io/gradio-webrtc/
## Examples
When using it, you need a handler as the entry parameter of the component and implement code similar to the following:
```python
import asyncio
import base64
from io import BytesIO
import gradio as gr
import numpy as np
from gradio_webrtc import (
AsyncAudioVideoStreamHandler,
WebRTC,
VideoEmitType,
AudioEmitType,
)
from PIL import Image
def encode_audio(data: np.ndarray) -> dict:
"""Encode Audio data to send to the server"""
return {"mime_type": "audio/pcm", "data": base64.b64encode(data.tobytes()).decode("UTF-8")}
def encode_image(data: np.ndarray) -> dict:
with BytesIO() as output_bytes:
pil_image = Image.fromarray(data)
pil_image.save(output_bytes, "JPEG")
bytes_data = output_bytes.getvalue()
base64_str = str(base64.b64encode(bytes_data), "utf-8")
return {"mime_type": "image/jpeg", "data": base64_str}
class VideoChatHandler(AsyncAudioVideoStreamHandler):
def __init__(
self, expected_layout="mono", output_sample_rate=24000, output_frame_size=480
) -> None:
super().__init__(
expected_layout,
output_sample_rate,
output_frame_size,
input_sample_rate=24000,
)
self.audio_queue = asyncio.Queue()
self.video_queue = asyncio.Queue()
self.quit = asyncio.Event()
self.session = None
self.last_frame_time = 0
def copy(self) -> "VideoChatHandler":
return VideoChatHandler(
expected_layout=self.expected_layout,
output_sample_rate=self.output_sample_rate,
output_frame_size=self.output_frame_size,
)
#Process video data uploaded by the client
async def video_receive(self, frame: np.ndarray):
newFrame = np.array(frame)
newFrame[0:, :, 0] = 255 - newFrame[0:, :, 0]
self.video_queue.put_nowait(newFrame)
#Prepare the video data sent by the server
async def video_emit(self) -> VideoEmitType:
return await self.video_queue.get()
#Process audio data uploaded by the client
async def receive(self, frame: tuple[int, np.ndarray]) -> None:
frame_size, array = frame
self.audio_queue.put_nowait(array)
#Prepare the audio data sent by the server
async def emit(self) -> AudioEmitType:
if not self.args_set.is_set():
await self.wait_for_args()
array = await self.audio_queue.get()
return (self.output_sample_rate, array)
def shutdown(self) -> None:
self.quit.set()
self.connection = None
self.args_set.clear()
self.quit.clear()
css = """
footer {
display: none !important;
}
"""
with gr.Blocks(css=css) as demo:
webrtc = WebRTC(
label="Video Chat",
modality="audio-video",
mode="send-receive",
video_chat=True,
elem_id="video-source",
)
webrtc.stream(
VideoChatHandler(),
inputs=[webrtc],
outputs=[webrtc],
time_limit=150,
concurrency_limit=2,
)
if __name__ == "__main__":
demo.launch()
```
## Deployment
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.
The easiest way to do this is to use a service like Twilio.
```python
from twilio.rest import Client
import os
account_sid = os.environ.get("TWILIO_ACCOUNT_SID")
auth_token = os.environ.get("TWILIO_AUTH_TOKEN")
client = Client(account_sid, auth_token)
token = client.tokens.create()
rtc_configuration = {
"iceServers": token.ice_servers,
"iceTransportPolicy": "relay",
}
with gr.Blocks() as demo:
...
rtc = WebRTC(rtc_configuration=rtc_configuration, ...)
...
```
## Contributors
[csxh47](https://github.com/xhup)
[bingochaos](https://github.com/bingochaos)
[sudowind](https://github.com/sudowind)
[emililykimura](https://github.com/emililykimura)
[Tony](https://github.com/raidios)
[Cheng Gang](https://github.com/lovepope)