Human Pose Estimation Project

• Running Site

Overview

This project aims to implement a human pose estimation system using deep learning techniques. Human pose estimation involves detecting key points on a person's body, such as joints and limbs, to understand their pose or position in an image or video.

Features

• Key Point Detection: The system detects key points on human bodies, such as wrists, elbows, shoulders, knees, and ankles.
• Pose Estimation: Using the detected key points, the system estimates the pose of the person in terms of body joints and limb orientations.
• Real-time Processing: The system is optimized for real-time performance, allowing for efficient processing of images and videos.
• Multi-person Pose Estimation: The system supports the detection and estimation of multiple people in the same image or video frame.
• Customizable: The architecture allows for easy customization and integration with other deep learning models or frameworks.

Technology Used

• HTML
• CSS
• JavaScript
• PoseNet
• TensorFlow

Requirements

• Python 3.x
• TensorFlow 2.x
• TensorFlow.js
• TensorFlow.js PoseNet
• OpenCV
• NumPy
• Matplotlib