The Motion Amplification Vibration Monitoring System is an innovative project aimed at merging human and machine health monitoring using cutting-edge technology. By harnessing Video Magnification, Computer Vision, and Machine Learning Algorithms, our system provides comprehensive insights into machinery and human well-being.
- Eulerian Video Magnification: Enhance video footage to make subtle motion patterns, vibrations, and color changes more visible.
- Human Health Analysis: Utilize video footage to examine human movements, generate health parameter graphs using computer vision, and provide detailed health reports using machine learning algorithms.
- Use Cases:
- Respiratory Rate Monitoring: Identify irregular breathing patterns and track breath frequency.
- Heart Rate Monitoring: Continuously monitor heart rate to assess cardiovascular health and fitness levels.
- Aircraft Engine Health Analysis: Assess aircraft engine health by detecting vibrations and micro-scale defects to prevent unexpected failures.
- Flask: Python web framework for backend development.
- OpenCV: Computer vision library for video processing.
- TensorFlow/Keras: Machine learning framework for developing health analysis models.
- Universal Device Compatibility: Ensure flawless performance across a spectrum of devices, including web, windows and Android platforms.
- Real Time Motion Magnification using Frame-By-Frame Difference of Vibrations.
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Clone the repository:
git clone https://github.com/ARTHON9611/Electrothon_6.0-LEND-EN-.git
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Install dependencies:
pip install -r requirements.txt
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Run the Flask application:
python app.py
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Access the application through the provided URL in your web browser.
Contributions are welcome! Please open an issue or submit a pull request for any new features, improvements, or bug fixes.