harshbg/Sign-Language-Interpreter-using-Deep-Learning
A sign language interpreter using live video feed from the camera.
Trains a convolutional neural network (CNN) using TensorFlow and Keras to recognize 44 American Sign Language (ASL) characters from hand gesture images captured via webcam, achieving >95% accuracy. The pipeline includes hand histogram calibration, gesture dataset creation with image augmentation, and real-time inference on live video feed. OpenCV handles hand segmentation and preprocessing to isolate gestures before feeding them into the trained model.
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Python
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MIT
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Sep 09, 2025
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