The latest hurricane - Hurricane Iota, had 61 total fatalities, and 41 are still missing. After a hurricane, damage assessment is vital to the relief helpers and first responders so that resources and help can be planned and allocated appropriately. One way to measure the damage is to detect and quantify the number of damaged buildings, usually done by driving around the affected area and noting it down manually. This process can be labour-intensive and time-consuming and not the most efficient method as well. Hence in this project, we have tried to classify buildings between damaged and not damaged buildings using the satellite imagery data described below.
The data is provided to you has the following subfolders:
• train_another: the training data; 5000 images of each class (damage/no damage)
• validation_another: the validation data; 1000 images of each class (damage/no damage)
• test_another: the unbalanced test data; 8000/1000 images of damaged/undamaged classes
• test: the balanced test data; 1000 images of each class (damage/no damage)