pfunzomaba/South-African-Sign-Language-Translator

The primary goal is to bridge the communication gap between individuals who use South African Sign Language (SASL) and those who do not understand or are not proficient in SASL. # South-African-Sign-Language-Translator The aim is to develop and implement an AI-driven sign language translator system that can facilitate seamless and accurate communication between individuals using sign language and those who do not, thereby enhancing accessibility for individuals with hearing impairments in various social, educational, and professional environments. The project leverages OpenCV for processing webcam frames, including detecting hands in the frame, cropping the region of interest, and displaying the predicted label on the image. It uses a pre-trained image classification model from the cvzone.ClassificationModule to predict the label for the captured hand gesture. This project manages user inputs through key presses ('a' for adding to the displayed text, 'r' for deleting the last character, and 'd' for resetting the displayed text).