This project focuses on developing a neural network for detecting signs using computer vision techniques. The goal is to recognize and classify various signs captured through image or video input.
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Hand Sign Recognition: The neural network is designed to recognize and classify hand signs in real-time.
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Multiple Gestures: Supports the detection of a variety of hand gestures, providing a versatile solution for sign language or gesture-based communication.
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MediaPipe and OpenCV: Utilizes the MediaPipe library for hand tracking and OpenCV for image and video processing.
- Python 3.x
- OpenCV
- NumPy
- MediaPipe
- TensorFlow (or other deep learning framework)
- [Other dependencies...]
- Clone the repository:
https://github.com/Sajithrajan03/Sign_Detection_NNDL.git cd .\hand-gesture-recognition-mediapipe\
Results:
