Test time agumentations #81
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* refactor data loading into its own module * update type annotations * move the logging module out * move old logging into utils * rename tests to match module name * bump torch * draft fcmae encoder * add stem to the encoder * wip: masked stem layernorm * wip: patchify masked features for linear * use mlp from timm * hack: POC training script for FCMAE * fix mask for fitting * remove training script * default architecture * fine-tuning options * fix cli for finetuning * draft combined data module * fix import * manual validation loss reduction * update linting new black version has different rules * update development guide * update type hints * bump iohub * draft ctmc v1 dataset * update tests * move test_data * remove path conversion * configurable normalizations (#68) * inital commit adding the normalization. * adding dataset_statistics to each fov to facilitate the configurable augmentations * fix indentation * ruff * test preprocessing * remove redundant field * cleanup --------- Co-authored-by: Ziwen Liu <[email protected]> * fix ctmc dataloading * add example ctmc v1 loading script * changing the normalization and augmentations default from None to empty list. * invert intensity transform * concatenated data module * subsample videos * livecell dataset * all sample fields are optional * fix multi-dataloader validation * lint * fixing preprocessing for varying array shapes (i.e aics dataset) * update loading scripts * fix CombineMode * always use untrainable head for FCMAE * move log values to GPU before syncing Lightning-AI/pytorch-lightning#18803 * custom head * ddp caching fixes * fix caching when using combined loader * compose normalizations for predict and test stages * black * fix normalization in example config * fix normalization in example config * prefetch more in validation * fix collate when multi-sample transform is not used * ddp caching fixes * fix caching when using combined loader * typing fixes * fix test dataset * fix invert transform * add ddp prepare flag for combined data module * remove redundant operations * filter empty detections * pass trainer to underlying data modules in concatenated * hack: add test dataloader for LiveCell dataset * test datasets for livecell and ctmc * fix merge error * fix merge error * fix mAP default for over 100 detections * bump torchmetric * fix combined loader training for virtual staining task * fix non-combined data loader training * add fcmae to graph script * fix type hint * format * add back convolutiuon option for fcmae head --------- Co-authored-by: Eduardo Hirata-Miyasaki <[email protected]>
* rename file * rename the architecture * fix merge
* test on python 3.12 * black * CI: only install CPU wheels for torch * install torch first * install torchvision together with torch * bumping monai --------- Co-authored-by: Eduardo Hirata-Miyasaki <[email protected]>
* add reference and minor edits * add back abstracts
* fix architecture name * add boxes to the diagram * deleting some extra redundant lines --------- Co-authored-by: Eduardo Hirata-Miyasaki <[email protected]>
* add the scale metadata from the input. * add change to config file * adding a try except * passing None for default behaviour and letting iohub handle the scale default. * making default metadta_store to none and adding letting iohub handle the exceptions * fix docstring * fix type hint * read input store directly * revert change to the example config --------- Co-authored-by: Ziwen Liu <[email protected]>
* rename file * rename the architecture * fix merge
* rename file * rename the architecture * fix merge
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Closing in favor of #91 . |
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This PR adds test time augmentations to the prediction step.