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!

📥 Project Files & Source Code:
🔗 Get the full source code and datasets here: [ https://www.scratchlearn.com/projects/real-time-ai-fitness-counter.html ]

🔗 For 20+ more AI & Python projects visit: [ www.scratchlearn.com/explore-projects.html ]

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📌 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

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