AkramOM606/American-Sign-Language-Detection
A real-time American Sign Language (ASL) detection system using computer vision and deep learning. This project uses a combination of OpenCV, MediaPipe, and TensorFlow to detect and classify ASL hand signs from camera input. The system can recognize a wide range of ASL characters, and can be used to facilitate communication for sign language users.
This application helps bridge communication gaps by translating American Sign Language (ASL) hand signs into text in real-time. It takes live camera video of someone signing, processes the hand movements, and outputs the corresponding ASL characters. This tool is designed for anyone communicating with ASL users, such as educators, support staff, or family members.
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Use this if you need to understand ASL signs in real-time from a camera feed to facilitate communication.
Not ideal if you need to translate spoken language to ASL or require a certified ASL interpreter.
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15
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14
Language
Jupyter Notebook
License
MIT
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Last pushed
Mar 22, 2025
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