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Understanding Clouds from Satellite Images

This is Catalyst + pytorch segmentation model baseline for https://www.kaggle.com/c/understanding_cloud_organization/

My solution was below:

  1. Unet/efficientnet-b3/image size 320x480/5fold
  2. Unet/efficientnet-b0/image size 320x480/cosineanealing/5fold
  3. Unet/efficientnet-b3/image size 384x576/cosineanealing/5fold
  4. FPN/resnet34/image size 384x576/mixup/5fold
  5. Ensemble above 20 models
  6. Triplet thresholding(label threshold/mask threshold/min componet)

Usage

$ python split_fold.py --config config/base_config.yml
$ python train.py --config config/seg/* #run all config in the folder
$ python ensemble.py  #I was lazy, parameter of ensembing is hard coded in ensemble.py