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Streamlit Camera Live is a Streamlit-based application designed for real-time face detection and recognition. This tool allows users to capture and analyze video streams directly from their camera, leveraging AI to identify and track faces in real-time. It is ideal for developers and users looking to integrate face recognition capabilities into their applications or streamline live video analysis.
• Real-time face detection: Identifies faces in live video streams with high accuracy.
• Multiple camera support: Compatible with both built-in and external cameras.
• Customizable settings: Adjust detection thresholds and frames per second for optimal performance.
• Snapshot capture: Capture and save images of detected faces for further analysis.
• Performance tuning: Options to balance between accuracy and processing speed.
• User-friendly interface: Intuitive controls for seamless operation.
pip install streamlit and pip install opencv-python to install dependencies.streamlit run your_script.py to start the application.What devices are supported by Streamlit Camera Live?
Streamlit Camera Live supports most modern webcams and cameras, including built-in laptop cameras and external USB cameras.
How accurate is the face detection?
The accuracy depends on lighting conditions, camera resolution, and the quality of the AI model used. For best results, ensure good lighting and a clear view of the subject.
What if my camera is not detected?
Check your camera settings, ensure it is properly connected, and restart the application. If issues persist, verify your camera drivers or try a different device.