Hand-Tracking-Using-Opencv

About The Project

This Python script utilizes OpenCV and MediaPipe to perform real-time hand tracking using a webcam. The code captures video input from the default camera, processes the frames to detect and track hand landmarks using the MediaPipe Hands module, and subsequently visualizes the landmarks on the live feed. For each detected hand, the script identifies and prints the coordinates of the landmarks, with a distinctive filled circle highlighting the first landmark (index 0). The frame rate is calculated and displayed in the corner, providing insights into the processing speed. Overall, this script combines the power of computer vision libraries to create a hands-on experience, quite literally, by bringing hand-tracking capabilities to your fingertips. It's a practical demonstration of the intersection between software and real-world interaction, opening doors to diverse applications such as virtual reality, gaming, and accessibility interface.

Video.Ouput.mp4

Cam.Output.mp4

Built With

• Opencv
• Mediapipe

Getting Started

This will help you understand how you may give instructions on setting up your project locally. To get a local copy up and running follow these simple example steps.

Installation Steps

Option 1: Installation from GitHub

Follow these steps to install and set up the project directly from the GitHub repository:

1. Clone the Repository

   • Open your terminal or command prompt.
   • Navigate to the directory where you want to install the project.
   • Run the following command to clone the GitHub repository:

     git clone https://github.com/KalyanMurapaka45/Hand-Tracking-Using-Opencv.git
     

2. Create a Virtual Environment (Optional but recommended)

   • It's a good practice to create a virtual environment to manage project dependencies. Run the following command:

     conda create -p <Environment_Name> python==<python version> -y
     

3. Activate the Virtual Environment (Optional)

   • Activate the virtual environment based on your operating system:

     conda activate <Environment_Name>/
     

4. Install Dependencies

   • Navigate to the project directory:

     cd [project_directory]
     

   • Run the following command to install project dependencies:

     pip install -r requirements.txt
     

5. Run the Project

   • Start the project by running the appropriate command.

     python app.py
     

6. Access the Project

   • Open a web browser or the appropriate client to access the project.

Contributing

Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement". Don't forget to give the project a star! Thanks again!

1. Fork the Project
2. Create your Feature Branch
3. Commit your Changes
4. Push to the Branch
5. Open a Pull Request

License

Distributed under the MIT License. See LICENSE.txt for more information.

Contact

Hema Kalyan Murapaka - @kalyanmurapaka274@gmail.com

Acknowledgements

We'd like to extend our gratitude to all individuals and organizations who have played a role in the development and success of this project. Your support, whether through contributions, inspiration, or encouragement, has been invaluable. Thank you for being a part of our journey.