This project aims to recognize and generate sign language from a video using YOLOv5 for object detection. The goal is to help bridge the communication gap for individuals who rely on sign language.
The system utilizes YOLOv5 (You Only Look Once version 5), a state-of-the-art real-time object detection model, to identify hand gestures in sign language videos. Once the gestures are detected, they are translated into corresponding text or actions. This system can be helpful in educational tools, accessibility for the hearing impaired, and communication platforms.
- Object Detection with YOLOv5: YOLOv5 is used to detect hand gestures in real-time from video frames.
- Sign Language Translation: Detected gestures are mapped to predefined sign language words or sentences.
- Real-Time Processing: The model processes the video frames in real time for fast and efficient sign language recognition.
- Easy Integration: The model can be integrated into applications like mobile apps or websites for accessibility purposes.