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.