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https://github.com/ragul-rofi/handrecognition-opencv
Real-time hand gesture recognition using OpenCV
https://github.com/ragul-rofi/handrecognition-opencv
handrecognition opencv pyhton3
Last synced: about 1 month ago
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Real-time hand gesture recognition using OpenCV
- Host: GitHub
- URL: https://github.com/ragul-rofi/handrecognition-opencv
- Owner: ragul-rofi
- License: mit
- Created: 2024-12-21T18:44:06.000Z (about 1 month ago)
- Default Branch: main
- Last Pushed: 2024-12-21T18:59:20.000Z (about 1 month ago)
- Last Synced: 2024-12-21T19:36:02.700Z (about 1 month ago)
- Topics: handrecognition, opencv, pyhton3
- Language: Python
- Homepage:
- Size: 0 Bytes
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Hand Gesture Recognition using OpenCV
This project uses OpenCV to recognize hand gestures in real-time via a webcam. The program detects the hand and counts the number of fingers raised based on the convexity defects in the hand contour.
## Features
- Real-time hand gesture recognition using webcam.
- Detects the number of fingers raised.
- Uses convexity defects for finger detection.
- Works on most webcams.
## Requirements
To run this project, you will need to install the following Python libraries:
- **OpenCV**: For image processing and computer vision tasks.
- **NumPy**: For numerical operations (specifically for vector math).
You can install these libraries using pip:
```bash
pip install opencv-python opencv-python-headless numpy
```
## Project Structure
The project consists of a single Python script:
- **main.py**: The main script that captures webcam feed, processes the image, detects hand contours, and counts the number of fingers.
## How to Run
1. Ensure that you have Python 3.x installed on your machine.
2. Install the required libraries by running the command:
```bash
pip install opencv-python opencv-python-headless numpy
```
3. Clone or download the project.
4. Open a terminal or command prompt and navigate to the directory containing `main.py`.
5. Run the script:
```bash
python main.py
```
6. A window will appear showing the webcam feed with hand gesture recognition. The program will print the number of fingers detected in the console.
7. To exit the program, press the `q` key.
## Future Improvements
- Improve finger detection accuracy for more complex gestures.
- Add gesture-based control to interact with the computer (e.g., mouse control).
- Implement a model to recognize different hand gestures for control purposes.
## License
This project is open-source and available under the MIT License. See the [LICENSE](LICENSE) file for more information.