This repository implements a convolutional neural network trained on grayscale images to recognize gestures from American Sign Language, covering 26 alphabets, 10 numbers, and additional signs. The model was trained on 2400 images per gesture captured via OpenCV, processed at 50x50 pixel resolution. The trained Keras model is then applied to real-time video streams to predict and output the recognized sign language gesture.