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freddyaboulton
2024-10-23 15:11:39 -07:00
parent ac8d2a8be8
commit 1688502e99
11 changed files with 83 additions and 38 deletions

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@@ -1,14 +1,3 @@
---
tags: [gradio-custom-component, Video, streaming, webrtc, realtime]
title: gradio_webrtc
short_description: Stream images in realtime with webrtc
colorFrom: blue
colorTo: yellow
sdk: gradio
pinned: false
app_file: space.py
---
<h1 style='text-align: center; margin-bottom: 1rem'> Gradio WebRTC ⚡️ </h1>
<div style="display: flex; flex-direction: row; justify-content: center">
@@ -30,15 +19,15 @@ pip install gradio_webrtc
1. [Object Detection from Webcam with YOLOv10](https://huggingface.co/spaces/freddyaboulton/webrtc-yolov10n) 📷
2. [Streaming Object Detection from Video with RT-DETR](https://huggingface.co/spaces/freddyaboulton/rt-detr-object-detection-webrtc) 🎥
3. [Text-to-Speech](https://huggingface.co/spaces/freddyaboulton/parler-tts-streaming-webrtc) 🗣️
4. [Conversational AI](https://huggingface.co/spaces/freddyaboulton/omni-mini-webrtc) 🤖🗣️
## Usage
The WebRTC component supports the following three use cases:
1. Streaming video from the user webcam to the server and back
2. Streaming Video from the server to the client
3. Streaming Audio from the server to the client
Streaming Audio from client to the server and back (conversational AI) is not supported yet.
1. [Streaming video from the user webcam to the server and back](#h-streaming-video-from-the-user-webcam-to-the-server-and-back)
2. [Streaming Video from the server to the client](#h-streaming-video-from-the-server-to-the-client)
3. [Streaming Audio from the server to the client](#h-streaming-audio-from-the-server-to-the-client)
4. [Streaming Audio from the client to the server and back (conversational AI)](#h-conversational-ai)
## Streaming Video from the User Webcam to the Server and Back
@@ -78,7 +67,7 @@ as a **numpy array** and returns the processed frame also as a **numpy array**.
* The `inputs` parameter should be a list where the first element is the WebRTC component. The only output allowed is the WebRTC component.
* The `time_limit` parameter is the maximum time in seconds the video stream will run. If the time limit is reached, the video stream will stop.
## Streaming Video from the User Webcam to the Server and Back
## Streaming Video from the server to the client
```python
import gradio as gr
@@ -143,6 +132,52 @@ with gr.Blocks() as demo:
* The numpy array should be of shape (1, num_samples).
* The `outputs` parameter should be a list with the WebRTC component as the only element.
## Conversational AI
```python
import gradio as gr
import numpy as np
from gradio_webrtc import WebRTC, StreamHandler
from queue import Queue
import time
class EchoHandler(StreamHandler):
def __init__(self) -> None:
super().__init__()
self.queue = Queue()
def receive(self, frame: tuple[int, np.ndarray] | np.ndarray) -> None:
self.queue.put(frame)
def emit(self) -> None:
return self.queue.get()
with gr.Blocks() as demo:
with gr.Column():
with gr.Group():
audio = WebRTC(
label="Stream",
rtc_configuration=None,
mode="send-receive",
modality="audio",
)
audio.stream(fn=EchoHandler(), inputs=[audio], outputs=[audio], time_limit=15)
if __name__ == "__main__":
demo.launch()
```
* Instead of passing a function to the `stream` event's `fn` parameter, pass a `StreamHandler` implementation. The `StreamHandler` above simply echoes the audio back to the client.
* The `StreamHandler` class has two methods: `receive` and `emit`. The `receive` method is called when a new frame is received from the client, and the `emit` method returns the next frame to send to the client.
* An audio frame is represented as a tuple of (frame_rate, audio_samples) where `audio_samples` is a numpy array of shape (num_channels, num_samples).
* You can also specify the audio layout ("mono" or "stereo") in the emit method by retuning it as the third element of the tuple. If not specified, the default is "mono".
* The `time_limit` parameter is the maximum time in seconds the conversation will run. If the time limit is reached, the audio stream will stop.
## 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.