marvinhoxha/Arm-UNICEF-Disaster-Vulnerability

Identifying thatch-roofed houses for disaster planning in rural Malawi using aerial images # Arm-UNICEF-Disaster-Vulnerability Identifying thatch-roofed houses for disaster planning in rural Malawi using aerial images ## Description * Over 80% of Malawi's population resides in rural areas. * Natural disasters and global challenges like Covid-19 affect these communities. * Current damage assessment methods overlook crucial data, such as identifying houses with grass-thatched roofs. * This competition leverages machine learning on aerial imagery to accurately count these structures. # Set Up ## Create a virtual environment ``` python -m venv venv source /venv/bin/activate ``` ## Install requirements ``` pip install -r requirements.txt ``` ## Resize Images ``` python resize_images.py ``` ## Prepare data for training in Yolo format ``` python prepare_data.py ``` ## Augment data ``` python data_aug.py ``` ## Train models ``` python trainYolo.py ``` # Dataset ## Download the dataset You can download the dataset from here ### Example image