A real-time posture correction system using pose estimation to enhance gym workouts and promote safe exercise practices.
This project addresses the challenge of incorrect exercise form, a common issue in gyms that can lead to injuries. By leveraging pose estimation technology, we've developed a system that provides users with real-time feedback on their posture during workouts. This helps individuals perform exercises correctly, reducing the risk of injury and maximizing the effectiveness of their training.
- Real-time Pose Estimation: Utilizes MediaPipe, a powerful computer vision library, to accurately detect and track key body landmarks in real time.
- Posture Correction Feedback: Provides immediate visual feedback on a screen, guiding users to adjust their posture for optimal form.
- Customizable Pose Database: Includes a database of reference poses for various exercises, allowing users to select and practice specific movements.
- User-Friendly Interface: Offers an intuitive interface for easy navigation and exercise selection.
- Future Enhancement: Planned integration of wireless headset feedback for a more immersive and hands-free experience.
- Programming Language: Python
- Libraries: MediaPipe, OpenCV
- Dataset: Custom pose dataset focused on Bangladeshi and Indian Subcontinent ethnicities.
- Capture: The system captures video input from a smartphone or computer camera.
- Pose Detection: MediaPipe's pose estimation model identifies key body joints and their coordinates.
- Geometric Analysis: The system compares the detected pose with reference poses from the database.
- Feedback: Real-time feedback is provided on the screen, highlighting any deviations from the correct posture.
- Clone the Repository:
git clone https://github.com/1yakub/PoseEstimationProject - Install Dependencies:
pip install -r requirements.txt - Run the Application:
python main.py
- 3D Pose Estimation: Incorporate depth data for more accurate posture analysis.
- Exercise Recommendations: Suggest exercises based on individual fitness goals and progress.
- Gamification: Introduce gamified elements to make workouts more engaging.
Contributions are welcome! Please fork the repository and submit a pull request with your proposed changes.
Md. Yakub Hossain - [email protected]