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Recent Releases of viscy

viscy - VisCy 0.3.2

[!NOTE] Our paper Robust virtual staining of landmark organelles with Cytoland is now published in Nature Machine Intelligence! This version of VisCy is compatible with the models and demos described in the paper.

This release includes maintenance patches and documentation improvements.

What's Changed

  • Fix swapped colormap in the neuromast tutorial by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/256
  • Document AugmentedPredictionVSUNet by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/261
  • Update HF demo links by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/264
  • Replace black with ruff by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/262

Full Changelog: https://github.com/mehta-lab/VisCy/compare/v0.3.1...v0.3.2

- Python
Published by ziw-liu 11 months ago

viscy - VisCy 0.3.2rc0

[!WARNING] This is a release candidate for testing.

What's Changed

  • Fix swapped colormap in the neuromast tutorial by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/256
  • Document AugmentedPredictionVSUNet by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/261
  • Update HF demo links by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/264
  • Replace black with ruff by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/262

Full Changelog: https://github.com/mehta-lab/VisCy/compare/v0.3.1...v0.3.2rc0

- Python
Published by ziw-liu 12 months ago

viscy - VisCy 0.3.1

This release includes maintenance patches and documentation improvements.

What's Changed

  • Add CLI tutorials for VCP by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/239
  • Update README.md to align with the title of the cytoland paper by @mattersoflight in https://github.com/mehta-lab/VisCy/pull/243
  • Update VCP tutorials by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/244
  • Delay cellpose import by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/245
  • Add contact information by @melissawm in https://github.com/mehta-lab/VisCy/pull/248
  • Add neuromast notebook by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/249
  • Skip broken test with pycocotools on python 3.13 by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/252
  • Fix DLMBL excercise setup script by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/253
  • Tweak VCP tutorials by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/251
  • Readme updates by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/246

New Contributors

  • @melissawm made their first contribution in https://github.com/mehta-lab/VisCy/pull/248

Full Changelog: https://github.com/mehta-lab/VisCy/compare/v0.3.0...v0.3.1

- Python
Published by ziw-liu about 1 year ago

viscy - VisCy 0.3.1rc0

[!WARNING] This is a release candidate for testing.

What's Changed

  • Add CLI tutorials for VCP by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/239
  • Update README.md to align with the title of the cytoland paper by @mattersoflight in https://github.com/mehta-lab/VisCy/pull/243
  • Update VCP tutorials by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/244
  • Delay cellpose import by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/245
  • Add contact information by @melissawm in https://github.com/mehta-lab/VisCy/pull/248
  • Add neuromast notebook by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/249
  • Skip broken test with pycocotools on python 3.13 by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/252
  • Fix DLMBL excercise setup script by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/253
  • Tweak VCP tutorials by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/251
  • Readme updates by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/246

New Contributors

  • @melissawm made their first contribution in https://github.com/mehta-lab/VisCy/pull/248

Full Changelog: https://github.com/mehta-lab/VisCy/compare/v0.3.0...v0.3.1rc0

- Python
Published by ziw-liu about 1 year ago

viscy - VisCy 0.3.0

VisCy 0.3.0 brings performance improvements to the image translation task, especially for very large datasets in distributed training. It also incorporates the representation learning task as a core feature.

Breaking change

The top-level CLI now supports both image translation and representation learning tasks. This required changes to configuration files. Concretely, data and model fields now require import paths to be specified. See the updated examples for reference on migrating existing virtual staining configs.

What's Changed

  • Add script to visualize effective receptive field by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/144
  • adding VS hugginface demo by @edyoshikun in https://github.com/mehta-lab/VisCy/pull/172
  • Single-cell representation learning by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/153
  • Vendor pad shape function by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/189
  • Fix module name spelling by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/190
  • Add new author to citation by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/188
  • Add links to hosted files and napari-iohub wiki by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/192
  • Bump MONAI to unpin NumPy by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/194
  • Add badges to readme by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/197
  • Simplify development installation by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/198
  • Fix validation loss aggregation in VSUNet by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/202
  • Expose prefetchfactor and persistentworker for the HCS datamodule by @edyoshikun in https://github.com/mehta-lab/VisCy/pull/203
  • Explicit target shape argument in the HCS data module by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/212
  • Rank nearest neighbors in embedding space by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/211
  • Gradio example by @edyoshikun in https://github.com/mehta-lab/VisCy/pull/158
  • Adding NTXENT loss by @edyoshikun in https://github.com/mehta-lab/VisCy/pull/204
  • Fix the wrong import name for pairwisedistancematrix() by @edyoshikun in https://github.com/mehta-lab/VisCy/pull/215
  • Fixing the TripletDataModule() after changes to HCSDataModule by @edyoshikun in https://github.com/mehta-lab/VisCy/pull/216
  • Sharded distributed sampler for cached dataloading in DDP by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/195
  • Tweak README by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/206
  • Expose the option to not return negative samples in the triplet data module by @edyoshikun in https://github.com/mehta-lab/VisCy/pull/225
  • Script to use ConvNeXt v1 Tiny as a feature extractor by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/228
  • Fix dice score by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/230
  • Evaluate existing segmentation by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/213
  • Check if the sliding window size is valid by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/229
  • Memory-mapped caching for image translation training by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/218
  • Update license metadata by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/233
  • Update supported python version range by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/200
  • Add DOI badge by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/235
  • Bump iohub by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/236
  • VCP tutorials by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/227
  • Remove outdated docs by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/238

Full Changelog: https://github.com/mehta-lab/VisCy/compare/v0.2.1...v0.3.0

- Python
Published by ziw-liu about 1 year ago

viscy - VisCy 0.3.0rc4

[!WARNING] This is a release candidate for testing.

What's Changed

  • Update supported python version range by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/200
  • Add DOI badge by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/235
  • Bump iohub by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/236
  • VCP tutorials by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/227

Full Changelog: https://github.com/mehta-lab/VisCy/compare/v0.3.0rc3...v0.3.0rc4

- Python
Published by ziw-liu about 1 year ago

viscy - VisCy 0.3.0rc3

[!WARNING] This is a release candidate for testing.

What's Changed

  • Script to use ConvNeXt v1 Tiny as a feature extractor by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/228
  • Fix dice score by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/230
  • Evaluate existing segmentation by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/213
  • Check if the sliding window size is valid by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/229
  • Memory-mapped caching for image translation training by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/218
  • Update license metadata by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/233

Full Changelog: https://github.com/mehta-lab/VisCy/compare/v0.3.0rc2...v0.3.0rc3

- Python
Published by ziw-liu about 1 year ago

viscy - VisCy 0.3.0rc2

[!WARNING] This is a release candidate for testing.

What's Changed

  • Explicit target shape argument in the HCS data module by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/212
  • Rank nearest neighbors in embedding space by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/211
  • Gradio example by @edyoshikun in https://github.com/mehta-lab/VisCy/pull/158
  • Adding NTXENT loss by @edyoshikun in https://github.com/mehta-lab/VisCy/pull/204
  • Fix the wrong import name for pairwisedistancematrix() by @edyoshikun in https://github.com/mehta-lab/VisCy/pull/215
  • Fixing the TripletDataModule() after changes to HCSDataModule by @edyoshikun in https://github.com/mehta-lab/VisCy/pull/216
  • Sharded distributed sampler for cached dataloading in DDP by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/195
  • Tweak README by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/206
  • Expose the option to not return negative samples in the triplet data module by @edyoshikun in https://github.com/mehta-lab/VisCy/pull/225

Full Changelog: https://github.com/mehta-lab/VisCy/compare/v0.3.0rc1...v0.3.0rc2

- Python
Published by ziw-liu about 1 year ago

viscy - VisCy 0.3.0rc1

[!WARNING] This is a release candidate for testing.

VisCy 0.3.0 incorporates the representation learning task as a core feature.

Breaking change

The top-level CLI now supports both image translation and representation learning tasks. This required changes to configuration files. Concretely, data and model fields now require import paths to be specified. See the updated examples for reference on migrating existing virtual staining configs.

What's Changed

  • Add script to visualize effective receptive field by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/144
  • adding VS hugginface demo by @edyoshikun in https://github.com/mehta-lab/VisCy/pull/172
  • Single-cell representation learning by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/153
  • Vendor pad shape function by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/189
  • Fix module name spelling by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/190
  • Add new author to citation by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/188
  • Add links to hosted files and napari-iohub wiki by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/192
  • Bump MONAI to unpin NumPy by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/194
  • Add badges to readme by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/197
  • Simplify development installation by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/198
  • Fix validation loss aggregation in VSUNet by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/202
  • Expose prefetchfactor and persistentworker for the HCS datamodule by @edyoshikun in https://github.com/mehta-lab/VisCy/pull/203

Full Changelog: https://github.com/mehta-lab/VisCy/compare/v0.2.1...v0.3.0rc1

- Python
Published by ziw-liu over 1 year ago

viscy - VisCy 0.3.0rc0

[!WARNING] This is a release candidate for testing.

VisCy 0.3.0 incorporates the representation learning task as a core feature.

Breaking change

The top-level CLI now supports both image translation and representation learning tasks. This required changes to configuration files. Concretely, data and model fields now require import paths to be specified. See the updated examples for reference on migrating existing virtual staining configs.

What's Changed

  • Add script to visualize effective receptive field by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/144
  • adding VS hugginface demo by @edyoshikun in https://github.com/mehta-lab/VisCy/pull/172
  • Single-cell representation learning by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/153
  • Vendor pad shape function by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/189
  • Fix module name spelling by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/190
  • Add new author to citation by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/188
  • Add links to hosted files and napari-iohub wiki by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/192

Full Changelog: https://github.com/mehta-lab/VisCy/compare/v0.2.1...v0.3.0rc0

- Python
Published by ziw-liu over 1 year ago

viscy - v0.2.1

Patch release to update README and example notebooks.

What's Changed

  • version lighting CLI example by @mattersoflight in https://github.com/mehta-lab/VisCy/pull/128
  • Updated code (contrastive learning) by @alishbaimran in https://github.com/mehta-lab/VisCy/pull/130
  • Configurable drop path rate in contrastive models by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/131
  • Config-based prediction with Xarray-based output format by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/132
  • Plot tracks in latent space and real space by @mattersoflight in https://github.com/mehta-lab/VisCy/pull/135
  • Fix deprecated custom forward method by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/151
  • updating the notebook after running it at DLMBL2024 by @edyoshikun in https://github.com/mehta-lab/VisCy/pull/149

Full Changelog: https://github.com/mehta-lab/VisCy/compare/v0.2.0...v0.2.1

- Python
Published by edyoshikun over 1 year ago

viscy - VisCy 0.2.0

VisCy 0.2.0 adds the following features:

  • Application scripts for single-cell infection classification through semantic segmentation
  • Tutorial notebook that demonstrates the virtual staining pipeline
  • Test time augmentations in the virtual staining prediction writer
  • (Alpha) Experimental support for single-cell phenotyping through contrastive learning

This release maintains compatibility with the virtual staining model weights from the v0.1.0 release (download link).

What's Changed

  • Update dataset URL for demos by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/103
  • Bump lightning and matplotlib by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/105
  • Cellular infection phenotyping using annotated viral sensor data & label-free images by @Soorya19Pradeep in https://github.com/mehta-lab/VisCy/pull/70
  • Pin numpy due to MONAI bug by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/111
  • Updating demo notebook for training by @edyoshikun in https://github.com/mehta-lab/VisCy/pull/100
  • Test time augmentations by @edyoshikun in https://github.com/mehta-lab/VisCy/pull/91
  • Update demo setup script by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/112
  • Single-cell phenotyping with contrastive learning by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/113
  • Migrate from wandb to tensorboard by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/122
  • Adding link to demos and library of VS models wiki by @edyoshikun in https://github.com/mehta-lab/VisCy/pull/119
  • Tune augmentations with CLI and config for contrastive models by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/126
  • DLMBL 2024 notebook by @edyoshikun in https://github.com/mehta-lab/VisCy/pull/114

New Contributors

  • @Soorya19Pradeep made their first contribution in https://github.com/mehta-lab/VisCy/pull/70

Full Changelog: https://github.com/mehta-lab/VisCy/compare/v0.1.1...v0.2.0

- Python
Published by edyoshikun almost 2 years ago

viscy - VisCy 0.2.0rc0

VisCy 0.2.0 adds the following features:

  • Application scripts for single-cell infection classification through semantic segmentation
  • Tutorial notebook that demonstrates the virtual staining pipeline
  • Test time augmentations in the virtual staining prediction writer

This release maintains compatibility with the virtual staining model weights from the v0.1.0 release (download link).

What's Changed

  • Update dataset URL for demos by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/103
  • Bump lightning and matplotlib by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/105
  • Cellular infection phenotyping using annotated viral sensor data & label-free images by @Soorya19Pradeep in https://github.com/mehta-lab/VisCy/pull/70
  • Pin numpy due to MONAI bug by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/111
  • Updating demo notebook for training by @edyoshikun in https://github.com/mehta-lab/VisCy/pull/100
  • Test time augmentations by @edyoshikun in https://github.com/mehta-lab/VisCy/pull/91

New Contributors

  • @Soorya19Pradeep made their first contribution in https://github.com/mehta-lab/VisCy/pull/70

Full Changelog: https://github.com/mehta-lab/VisCy/compare/v0.1.1...v0.2.0rc0

- Python
Published by ziw-liu almost 2 years ago

viscy - VisCy 0.1.1

Patch release to update the README.

What's Changed

  • README update by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/96

Full Changelog: https://github.com/mehta-lab/VisCy/compare/v0.1.0...v0.1.1

- Python
Published by ziw-liu almost 2 years ago

viscy - VisCy 0.1.0

This is first release of VisCy, the machine learning pipeline to train and deploy computer vision models for single-cell phenotyping.

With 0.1.0 the following key features are available:

  • Training, evaluation, inference, and deployment of virtual staining models based on 2D Residual U-Net, 2.5D U-Net, 3D U-Net, and UNeXt2 architectures
  • Data module implementations for HCS OME-Zarr datasets, as well public test datasets like LiveCell and CTMC v1.
  • Composing datasets and transformations for training and validation
  • Distributed (DDP) training

The weights of the virtual staining models reported in the preprint can be found in the binaries section below.

What's Changed

  • Migration from microDL by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/1
  • Update README by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/22
  • Bump iohub version by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/25
  • readme + dependencies tested with python 3.10 by @mattersoflight in https://github.com/mehta-lab/VisCy/pull/30
  • Demo notebooks by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/29
  • 3D augmentation and 2.1D U-Net by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/27
  • Fix datamodule by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/28
  • Improve augmentation by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/31
  • Fix inference by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/32
  • viscy -> VisCy by @mattersoflight in https://github.com/mehta-lab/VisCy/pull/34
  • Update readme.md typo for cd VisCy by @edyoshikun in https://github.com/mehta-lab/VisCy/pull/41
  • 2.1D upscale decoder by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/37
  • dlmbl 2023 archive by @mattersoflight in https://github.com/mehta-lab/VisCy/pull/44
  • Fix center slice metrics for 3D output by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/51
  • Configure the number of image samples logged at each epoch and batch by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/49
  • Example workflow by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/45
  • Project icon by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/38
  • Fix predicting new channels in an existing store by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/57
  • Document data methods by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/50
  • Visualize feature maps by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/53
  • Baseline 3D-LUNeXt by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/58
  • Preprocess CLI and source scaling during prediction by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/59
  • Configurable augmentations by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/61
  • Bump dependencies and update documentation by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/64
  • checkpoint as a model config parameter for warmup cosine learning rates by @edyoshikun in https://github.com/mehta-lab/VisCy/pull/66
  • Masked autoencoder pre-training for virtual staining models by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/67
  • Filter empty detections in labels by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/74
  • Add CITATION.cff by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/79
  • Fix 3D to 2D prediction with UNeXt2 model by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/80
  • 2D FCMAE by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/71
  • Rename UNeXt2 by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/84
  • Test on Python 3.12 by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/88
  • Add preprint reference to README by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/85
  • Fix architecture name in network diagram script by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/86
  • Add the scale metadata to the output_stores by @edyoshikun in https://github.com/mehta-lab/VisCy/pull/89
  • bumping to cellpose 3 by @edyoshikun in https://github.com/mehta-lab/VisCy/pull/92
  • Scale metadata handling for positions by @edyoshikun in https://github.com/mehta-lab/VisCy/pull/93
  • Demo for VSCyto2D and VSCyto3D by @edyoshikun in https://github.com/mehta-lab/VisCy/pull/94
  • Fix demos on other platforms by @ziw-liu in https://github.com/mehta-lab/VisCy/pull/95

Full Changelog: https://github.com/mehta-lab/VisCy/commits/v0.1.0

- Python
Published by ziw-liu almost 2 years ago