PoseNet

Overview

PoseNet is a real-time human pose estimation system that detects key points on a person’s body using deep learning techniques. This project is designed for applications such as motion tracking, fitness analysis, augmented reality, and more.

Features

• Real-time pose estimation
• Detects key points such as eyes, nose, shoulders, elbows, knees, and more
• Works with both images and live video feeds
• Lightweight and efficient for real-time performance
• Can be integrated with other applications like gesture recognition or activity monitoring

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/PoseNet.git
   cd PoseNet

2. Install dependencies:

   pip install -r requirements.txt

3. Download the required model weights (if applicable) and place them in the designated directory.

Usage

To run pose estimation on an image:

python pose_estimation.py --image path/to/image.jpg

To run real-time pose estimation using a webcam:

python pose_estimation.py --webcam

Dependencies

• Python 3.x
• OpenCV
• TensorFlow / PyTorch (depending on implementation)
• NumPy

Contributing

Contributions are welcome! Feel free to submit issues or pull requests.

License

This project is licensed under the MIT License.

Contact

For any questions, feel free to reach out to [codeisfunforme@gmail.com] or open an issue on GitHub.