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0.0.3

Documentation:

  • Updated README
  • Updates to workflows: RODI and Finbenthic2

Preprocessing changes:

  • Added random state option to 01_train_test_split.py

Train script changes:

  • Explicit setting of wandb.init() so that it works in multi-GPU environments

Prediction script changes:

  • Feature extraction is now possible in 03_predict.py. Setting --feature_extraction to "pooled" or "unpooled" returs a pickled file containing the feature outputs of the DNN, before a classification head.
  • Feature extraction can be also done with pretrained models, if no checkpoint is passed to prediction script.
  • Added possibility of returning logits instead of sigmoid probabilities, using --return_logits 'True' in prediction script

Post-processing changes:

  • Added an argument --suffix to CV prediction combination, so that specification between grouped and non-grouped predictions in the same folder can be distinguished.
  • Added --out_prefix to evaluation script. metrics by default.

Other changes

  • Removed imsize as a parameter to Dataset and LitDataModule. This is passed via aug_args.
  • Added segmentation module to the package. Documentation coming later.

Environment:

  • Added onnx, onnxruntime, biopython, networkx and pycocotools to environment

0.0.2

Examples:

  • Added FinBenthic1 examples

Train script changes:

  • Loading pretrained weights without resuming a previous run is now possible
  • Last model checkpoint is saved
  • Learning rate monitoring

Prediction scripts changes:

  • Fixed bug in TTA. Changes to DataModules were also made in taxonomist.__init__

Post-processing changes:

  • Fixed a bug in grouping script where reference dataset was not checked properly

Evaluation changes:

  • Running evaluation without bootstrap is now possible
  • Re-designed and simplified comparison script