My Project

This project utilizes the following Python libraries:

• OpenCV (opencv-python): A powerful library for computer vision tasks, including image and video processing.
• NumPy (numpy): The fundamental package for scientific computing with Python, providing support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays.
• Scikit-learn (scikit-learn): A comprehensive machine learning library that provides various algorithms for classification, regression, clustering, and more, including utilities for calculating pairwise distances.

Installation

To set up your environment, follow these steps:

1. Clone the repository (if applicable):

   git clone <repository-url>
   cd <repository-name>

2. Create a virtual environment (recommended):

   python -m venv venv

3. Activate the virtual environment:

   • On Windows:

     .\venv\Scripts\activate

   • On macOS/Linux:

     source venv/bin/activate

4. Install the required libraries:

   pip install -r requirements.txt

Usage

1. The project is a counter of your fingers with technics of convexHull, euclidean distance, and segmentation

2. Run the cells with extension of jupyter in vs code or use google colabs

3. Enjoy!!

Contributing

Course Python for computer Vision

License

OPEN SOURCE