Micro-Classify

Team Name: RadarVision
ID: 39446

Web App Repository

Prototype Repository

Contributors

Inchara J

Shravya H Jain

Diptangshu Bej

Anand Raut

Likith Manjunatha

Chethan A C

Tech Stack

Frontend: HTML, CSS, JavaScript.

Backend: Flask.

Machine Learning: Python, PyTorch, Scikit-learn, numpy.

Visualization: Matplotlib.

Deployment: Docker, gunicorn, nginx, AWS ec2, Route 53, certbot.

API Testing: Postman API.

Version Control & CI/CD: Git/GitHub.

Project Structure

Micro-Classify/
├── ml_model/                      # Machine learning model directory
│   ├── notebooks/                 # Jupyter notebooks for experiments and model training
│   ├── src/
│   │   ├── data/                  # Data handling scripts
│   │   ├── model/                 # Model training, evaluation, and prediction scripts
│   │   ├── utils/                 # Utility scripts (data preprocessing, visualization)
│   │   ├── main.py                # Main script python file to run the pretrained moddel
│   ├── requirements.txt           # Python dependencies for ML
│   ├── venv/                      # Virtual environment for ML
│   ├── .gitignore                 # Ignore unnecessary files (e.g., model weights, virtual env)
│   └── README.md                  # ML model documentation
├── docker-compose.yaml            # Docker Compose file (if containerizing)
├── Dockerfile                     # Dockerfile for backend (if containerizing)
├── .gitignore                     # Global .gitignore file
├── LICENSE                        # License file
└── README.md                      # Main project documentation

Model Metrics

Test Loss: 0.0244, Accuracy: 0.9918
Classification Report:
                      precision    recall  f1-score   support

  3_long_blade_rotor       0.99      0.99      0.99        72
 3_short_blade_rotor       0.99      0.96      0.98        85
                Bird       1.00      1.00      1.00        76
Bird+mini-helicopter       1.00      1.00      1.00        78
               drone       1.00      1.00      1.00        85
            rc_plane       0.98      1.00      0.99        90

            accuracy                           0.99       486
           macro avg       0.99      0.99      0.99       486
        weighted avg       0.99      0.99      0.99       486

Graphs

Loss Curve

Accuracy Curve

F1 score Curve

Web App

Contributing

1. Fork the repository

2. Create a new branch:

   git checkout -b feature

3. Make your changes

4. Add your changes:-

   git add <filename>

5. Commit your changes:

   git commit -m 'Add new feature'

6. Push to the branch:

   git push origin feature

7. Create a new Pull Request