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:

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:

   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:

   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 file for more information.