Project Information
- Category: Machine Learning
- Status: Active Development
- GitHub: View Project
Python
TensorFlow
MediaPipe
OpenCV
Deep Learning
Project Overview
The Yoga Asana Trainer is an innovative application that uses computer vision and machine learning to detect and analyze yoga poses in real-time. It provides instant feedback and corrections to help users improve their yoga practice, making it an ideal tool for both beginners and experienced practitioners.
Key Features
- Real-time pose detection and analysis
- Accurate alignment feedback
- Support for multiple yoga poses
- Personalized correction suggestions
- Progress tracking and analytics
- User-friendly interface
Technical Implementation
Core Technologies
- Python for application development
- TensorFlow for pose estimation model
- MediaPipe for body landmark detection
- OpenCV for image processing
- Custom algorithms for pose analysis
Machine Learning Pipeline
- Real-time video frame processing
- Body landmark detection and tracking
- Pose classification using deep learning
- Alignment analysis algorithms
- Feedback generation system
Development Process
Data Collection and Training
- Diverse dataset of yoga poses
- Multiple practitioners and variations
- Various lighting conditions
- Different camera angles
Model Development
- Custom neural network architecture
- Transfer learning from pre-trained models
- Extensive model validation
- Performance optimization
Applications
The Yoga Asana Trainer can be utilized in various scenarios:
- Personal yoga practice
- Virtual yoga classes
- Yoga teacher training
- Fitness centers and studios
- Physical therapy and rehabilitation
Future Improvements
- Support for more complex yoga sequences
- Integration with wearable devices
- 3D visualization of poses
- Mobile application development
- Cloud-based progress tracking
- Community features and sharing
