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Hurricane Satellite Imagery Damage Detection

Fork of repository Deep Learning Based Damage Detection on Post-Hurricane Satellite Imagery We added additional data to try and improve detection from kaggle competition

Final write up
Report
Slides

  • The dataset:
    1. train_another : the training data; 5000 images of each class
    2. validation_another: the validation data; 1000 images of each class
    3. test_another : the unbalanced test data; 8000/1000 images of damaged/undamaged classes
    4. test : the balanced test data; 1000 images of each class

Notebooks:

  • exploration.ipynb - has some initial charts and data exploration steps. This was the first thing we did
  • resnet50.ipynb - trying out the pretrained resnet model and retraining to our dataset with 50 epochs from hugging face
  • CNN.ipynb - modified from research paper very slightly, this introduces a basic CNN model with keras
  • vit.ipynb - trying to use a pretrained ViT model from HuggingFace and adapting to our dataset.
  • newResnet.ipynb - some changes to the 50 epochs resnet model