Welcome to the HandSignActionDetection project! This repository contains code and resources for detecting hand sign actions using machine learning and computer vision techniques.
HandSignActionDetection is a project aimed at recognizing and detecting various hand sign actions. The system utilizes a pre-trained model and OpenCV to accurately identify hand gestures in real-time.
- Real-time Hand Sign Detection: Utilizes OpenCV for real-time video processing.
- Pre-trained Model: Includes a trained model to classify different hand signs.
- Easy to Use: Simple and intuitive interface for testing and deploying hand sign detection.
checking.py: Script for checking the input data.model.ipynb: Jupyter notebook for model training and evaluation.nmod.h5: Pre-trained model file.opencv.py: Script for hand sign detection using OpenCV.
To get started with the HandSignActionDetection project, follow these steps:
- Clone the repository:
git clone https://github.com/kamlendra342/HandSignActionDetection.git cd HandSignActionDetection
Contributions are welcome! Feel free to open issues or submit pull requests to improve the project.
This project is licensed under the MIT License. See the LICENSE file for details.
For any questions or suggestions, please reach out to the project maintainer at kamlendra342.