CamShift Object Tracking Project

A Python project that utilizes OpenCV to create a CamShift object tracking system.

Requirements

• Python 3.x
• OpenCV
• NumPy

Setup

1. Install the required packages using pip:

    pip install opencv-python numpy

Usage

1. Clone the repository to your local machine using Git:

    git clone https://github.com/bkk31/camshift.git

2. Navigate to the project directory:

    cd camshift

3. Run the Python script using Python 3.x:

    python main.py

Notes

• This project uses OpenCV for image processing and CamShift algorithm for object tracking.
• Make sure to check the library documentation for any updates or changes to the API.
• Also, ensure that the video capture device is properly configured and connected.

Important Note:

• The CamShift algorithm in this project has been observed to work remarkably well on tracking human faces, providing accurate and smooth tracking results.
• However, its performance on tracking generic objects is somewhat limited, and may not always produce optimal results.
• This is due to the inherent characteristics of the CamShift algorithm, which is more suited for tracking objects with distinct color and texture features, such as human faces.

License

This project is licensed under the GNU General Public License version 3.0 (GPLv3). See the LICENSE file for details.

Contributing

Contributions are welcome! If you'd like to contribute to this project, please fork the repository and submit a pull request.