Examples

Tutorials

1. classification tutorial

   • dataset preparation (raw images -> train/valid/infer splits)

   • augmentations usage example

   • pretrained model finetuning

   • various classification metrics

   • metrics visualizaiton

   • FocalLoss and OneCycle usage examples

   • class imbalance handling

   • model inference

2. segmentation tutorial

   • car segmentation dataset

   • augmentations with albumentations library

   • training in FP16 with NVIDIA Apex

   • using segmentation models from catalyst/contrib/models/cv/segmentation

   • training with multiple criterion (Dice + IoU + BCE) example

   • Lookahead + RAdam optimizer usage example

   • tensorboard logs visualization

   • predictions visualization

   • Test-time augmentations with ttach library

Pipelines

1. Full description of configs with comments:

   • Eng

   • Rus

2. classification pipeline

   • classification model training and inference

   • different augmentations and stages usage

   • metrics visualization with tensorboard

3. segmentation pipeline

   • binary and semantic segmentation with U-Net

   • model training and inference

   • different augmentations and stages usage

   • metrics visualization with tensorboard

RL tutorials & pipelines

For Reinforcement Learning examples check out our Catalyst.RL repo.