Building Damage Assessment

This project uses YOLOv8 for building footprint detection and damage assessment from satellite images.

Project Structure

building_damage_assessment/
├── config/
│   └── config.yaml
├── src/
│   └── yolo_damage_assessment/
│       ├── train_yolo.py
│       └── utils/
│           └── logging_config.py
├── tests/
│   └── test_train_yolo.py
├── requirements.txt
├── setup.py
└── README.md

Local Installation

1. Clone the repository:

   git clone https://github.com/Zarasim/building-damage-assessment.git
   cd building-damage-assessment
   

2. Create a virtual environment and activate it:

   python -m venv venv
   source venv/bin/activate  # On Windows, use `venv\Scripts\activate`
   

3. Install the required packages:

   pip install -r requirements.txt
   

Local Usage

1. Update the config/config.yaml file with your specific settings.

2. Run the training script:

   python src/yolo_damage_assessment/train_yolo.py
   

   You can also specify custom paths for the configuration file and output directory:

   python src/yolo_damage_assessment/train_yolo.py --config path/to/your/config.yaml --output path/to/output/directory
   

Training on Google Colab

To train the model on Google Colab using a dataset stored on Google Drive:

1. Upload your dataset to Google Drive.

2. Create a new Colab notebook.

3. Mount your Google Drive:

   from google.colab import drive
   drive.mount('/content/drive')

4. Clone the repository:

   !git clone https://github.com/Zarasim/building-damage-assessment.git
   %cd building-damage-assessment
   

5. Install the required packages:

   !pip install -r requirements.txt
   

6. Update the config/config.yaml file to point to your dataset in Google Drive:

   import yaml
   
   with open('config/config.yaml', 'r') as file:
       config = yaml.safe_load(file)
   
   config['data']['yaml_path'] = '/content/drive/MyDrive/path/to/your/data.yaml'
   config['data']['test_image'] = '/content/drive/MyDrive/path/to/your/test_image.jpg'
   
   with open('config/config.yaml', 'w') as file:
       yaml.dump(config, file)

7. Run the training script:

   !python src/yolo_damage_assessment/train_yolo.py
   

   Or with custom paths:

   !python src/yolo_damage_assessment/train_yolo.py --config /content/drive/MyDrive/path/to/your/config.yaml --output /content/drive/MyDrive/path/to/output/directory
   

8. The trained model and results will be saved to the specified output directory in your Google Drive.

Testing

To run the tests, use pytest:

pytest tests/

License

This project is licensed under the MIT License.