5-10% of the world population is deaf or hard-of-hearing and rely on sign language as their primary form of communication. In this project, I set out to prototype a real-time system to translate the American Sign Language (finger spelled alphabet) from video into text. I will walk you through the current pipeline which utilises convolutional neural networks, transfer learning and a webcam with Keras and OpenCV – and some of my learning when implementing deep learning for real-time classification.
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