AI Fitness Tracker: Real-Time Exercise Counter in Python + OpenCV & MediaPipe + Source Code #ai

🏋 Smart AI Fitness Tracker + Source Code – Build your own real-time exercise counting system using Python, MediaPipe, OpenCV, and Tkinter! 🚀 In this project, we create an AI-powered fitness tracking system that detects and counts exercises in real-time. It supports push-ups, squats, chest flys, and dumbbell lifts using pose estimation with MediaPipe and Computer Vision. 👉 Who is this for? Perfect for developers, students, AI enthusiasts, fitness trainers, and health-tech innovators. ✅ What You’ll Learn in This Project: AI-based exercise tracking fundamentals MediaPipe + OpenCV + Tkinter integration Real-time pose estimation for motion analysis Automatic workout counting (Push-ups, Squats, Chest flys, Dumbbell lifts) Handling angles, occlusions, and motion variations Building a Tkinter fitness UI Applications in fitness tech, personal coaching, and rehabilitation 💡 By the end, you’ll have your own Smart AI Fitness Assistant! 🎓 Want this full project (source code + dataset + documentation) AND 21 more Computer Vision projects with certificate? 👉 Visit here → [ https://www.udemy.com/course/computer-vision-mastery-real-time-projects-opencv-python-ai-yolo/?referralCode=C219F7481A635FD9196A ] 🔗 For 20+ more AI & Python projects visit: [ www.scratchlearn.com/explore-projects.html ] 🔔 Don’t forget to Like, Share & Subscribe for more AI + Python projects! 📌 Timestamps 00:00 – Project Outcome 00:37 – Project Introduction 02:02 – Python Installation 03:29 – VS Code Installation 05:29 – Project Overview 07:21 – Package Explanations 10:04 – Angle Calculation Logic 11:51 – Fitness Counting Implementation 20:41 – Tkinter Variables Setup 23:00 – Model Inference Explanation 31:30 – Tkinter GUI Implementation 35:14 – Package Installation 37:25 – Code Execution 44:38 – Conclusion #aiprojects #pythonprojects #computervision #opencv #fitnesstracker #mediapipe #deeplearning #ai #python #scratchlearn