Pose Estimation in Images

Pose Estimation is a computer vision technique that detects human figures and predicts key points, such as joints and limbs, in images. This project demonstrates how machine learning models can identify and visualize poses in images, making it useful for applications in fitness, gaming, surveillance, and more.

Features

• Accurately detects key points such as elbows, knees, shoulders, and more in real-time.
• Supports single-person and multi-person pose estimation using models like OpenPose, HRNet, and PoseNet.
• Integration with live video feeds for dynamic pose estimation.
• Provides visual overlays to highlight detected poses, enhancing data visualization.

Installation

To set up the pose estimation system on your local machine, follow these steps:

1. Clone the Repository

   git clone https://github.com/username/pose-estimation.git
   cd pose-estimation

2. Set Up Virtual Environment (Optional but Recommended)

   python3 -m venv venv
   source venv/bin/activate   # On Windows: venv\Scripts\activate

3. Install Required Packages

   pip install -r requirements.txt

Usage

To start the pose estimation system, run the main script:

python pose_estimate.py

The system will process input images or video feeds and display detected poses with visual key points.

System Demo