Empowering Deaf and Mute Children through Computer Vision

Through the use of deep learning algorithms, this project aims to create a real-time video-based interactive sign language translation education system for people who are deaf or hard of hearing and have trouble learning how to communicate with others. The Flask framework and a pre-trained model for classification are part of the system to improve understanding and communication with sign language. In the future, the project proposes employing python libraries and tensor flow for image input prediction, which can effectively solve many communication problems. The proposed system presents an innovative and engaging approach to teaching and boosting communication abilities in deaf and dumb children. This paper highlights the proposed system's methodology, implementation, and results, demonstrating its effectiveness and potential for further development.