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Streamlit Webrtc Example is a Streamlit application that demonstrates how to integrate real-time video streaming and gesture recognition into a web-based interface. It allows users to interact with a virtual keyboard using hand gestures, making it a unique example of combining computer vision and web technologies. This example is particularly useful for developers looking to build gesture-based applications or explore WebRTC capabilities within Streamlit.
• Real-Time Video Streaming: Utilizes WebRTC to stream video from your webcam directly in the browser. • Hand Gesture Recognition: Detects specific hand gestures to type on a virtual keyboard. • Cross-Device Compatibility: Works on multiple devices with webcam support. • Customizable Gestures: Allows users to define or customize gestures for different characters or actions. • Performance Optimization: Efficient video processing to maintain smooth performance.
Install Required Packages: Ensure you have Streamlit and the necessary dependencies installed. Run pip install streamlit webrtc.
Configure Webcam: Allow the application to access your webcam when prompted in the browser.
Calibrate Gestures: Follow on-screen instructions to calibrate your hand gestures for recognition.
Start Typing: Use hand gestures to select keys on the virtual keyboard. The text will appear in the display area.
Provide Feedback: Adjust your hand positioning or lighting if gestures are not recognized accurately.
What do I need to run the Streamlit Webrtc Example?
You need a webcam, a modern web browser, and the necessary Python packages installed (Streamlit and webrtc).
Can I customize the gestures or add new ones?
Yes, the example allows you to define custom gestures for different keys or actions by modifying the gesture recognition logic.
What if the gesture recognition is not working?
Ensure your webcam is properly configured, adjust the lighting conditions, and recalibrate your gestures if necessary.