Use hand gestures to type on a virtual keyboard
Generate depth map from an image
Convert images of screens to structured elements
Recognize micro-expressions in images
Enhance and upscale images with face restoration
Transform face landmark/skin,half of FaceSwap
Recognize text and formulas in images
Compute normals for images and videos
streamlit application to for ANPR/ALPR
Visual Retrieval with ColPali and Vespa
Convert floor plan images to vector data and JSON metadata
https://huggingface.co/spaces/VIDraft/mouse-webgen
Find images matching a text query
Streamlit Webrtc Example is a tool that enables users to interact with web cameras and microphones directly from a Streamlit web interface. It provides a straightforward way to capture and process audio-visual data in real-time. The example demonstrates how to use hand gestures to type on a virtual keyboard, showcasing its potential for innovative human-computer interaction.
pip install streamlit-webrtc
streamlit run your_script.py
What browsers are supported?
Most modern browsers like Chrome, Firefox, and Edge support WebRTC, making them compatible with this example.
How accurate is the hand gesture recognition?
Accuracy depends on your camera quality and lighting conditions. Ensure good lighting for better performance.
Can I customize the virtual keyboard layout?
Yes, you can modify the keyboard layout by editing the corresponding code in the example to suit your needs.
Is this tool suitable for production use?
While it's a powerful example, it may require additional optimizations and security measures for production environments.
Can I integrate this with other Streamlit components?
Absolutely! Streamlit's modular design allows easy integration with other components and functionality.