P2: AI-Powered Gym Tracker with Python and MediaPipe
#OpenCV #ComputerVision #AI #MachineLearning #datascience #data
In this project, I developed an AI-powered gym tracker using Pose Estimation techniques. With MediaPipe and Python, I designed a system that detects poses from a live webcam feed, extracts joint coordinates, calculates joint angles, and tracks workout repetitions in real-time. The results are displayed on the screen using OpenCV, creating an interactive and practical fitness tool.
🔧 Technologies and Tools Used
• Python 3: Programming language for implementation.
• MediaPipe: Pose estimation library for detecting body poses.
• OpenCV: For video capture and visualization of results.
• NumPy: To perform numerical computations for joint angle calculations.
💡 How the System Works
1. Setup MediaPipe: Configure MediaPipe’s pose estimation solution in Python for real-time use.
2. Capture Webcam Feed: Use OpenCV to stream live video and detect body poses.
3. Joint Coordinates Extraction: Identify and extract key body points (joints) detected by MediaPipe.
4. Angle Calculation: Use NumPy and trigonometry to compute angles between joints for movement analysis.
5. AI Gym Tracker: Build a system to count workout repetitions based on pose transitions (e.g., curls).
📋 Step-by-Step Workflow
1. Install and Import Dependencies: Install MediaPipe, OpenCV, and other required libraries.
2. Make Real-Time Pose Detections: Set up a live webcam feed and process the detected body poses.
3. Extract Key Joints: Identify specific body parts and extract joint coordinates for further analysis.
4. Calculate Joint Angles: Compute angles using trigonometry to track specific movements accurately.
5. Build a Curl Counter: Develop logic to count repetitions of exercises based on angle thresholds.
🔥 Project Features
• Real-Time Feedback: Displays detected poses and rep count live on the screen.
• Interactive Visualization: Renders body landmarks with OpenCV for better user experience.
• Efficient Pose Analysis: Leverages AI to monitor workout performance and ensure form accuracy.
✨ Let’s Collaborate!
I’m always open to feedback and ideas from the community! 😊
Do you have suggestions to improve this gym tracker system or innovative ways to use pose estimation? Let’s connect and discuss!
Feel free to share your thoughts in the comments or message me directly. Together, we can explore new possibilities for AI-powered applications!
🔗 Explore the project here: https://github.com/iamramzan/P2-AI-Po...
