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A collection of various models, archtectures and augmentations for Image Segmentation

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Laplace's Demon

Code for my solution of: https://www.kaggle.com/c/understanding_cloud_organization/overview

All the important code are in py scripts. Don't waste time looking at the ipynb notebooks, they are just spurious experiments I did.

Architectures tried:

  • Unet
  • FPNet
  • LinkNet

Encoders tried:

  • Efficientnetb2
  • Efficientnetb4
  • resnet18
  • resnet34
  • resnet50

Augmentations that work:

  • CLAHE
  • Horizontal and vertical rotate
  • etc

TODO:

  • psudo-labelling
  • deep supervision
  • variable size training/testing
  • TTA

I got very busy during the end phase of the competition and couldn't do more experiments. I didn't even get time to try ensembling.

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A collection of various models, archtectures and augmentations for Image Segmentation

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