viscy-transforms
Image transforms for virtual staining microscopy.
Part of the VisCy project.
Installation
From PyPI (when published)
pip install viscy-transforms
For development (from monorepo root)
# Using uv (recommended)
uv pip install -e packages/viscy-transforms
# Or via workspace sync
uv sync --package viscy-transforms
Usage
from viscy_transforms import NormalizeSampled, BatchedRandAffined
# Transforms follow MONAI dictionary transform pattern
# See documentation for full API reference
Features
- PyTorch-based image transforms optimized for microscopy data
- MONAI Dictionary transform compatibility for DataLoader pipelines
- Kornia-accelerated augmentations (affine, noise, blur)
- Specialized transforms for virtual staining workflows
Examples
To run the example notebook, install with the notebook extra:
pip install viscy-transforms[notebook]
See the batched transforms benchmark notebook for a comparison of batched GPU transforms vs standard MONAI transforms.
Dependencies
torch>=2.4.1korniamonai>=1.4numpy
Documentation
In the works!
License
BSD-3-Clause - see LICENSE in repository root.
1 maintainer
Metadata
1 maintainer
Release files for viscy-transforms 0.1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| viscy_transforms-0.1.0.tar.gz | 6.4 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| viscy_transforms-0.1.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 6.4 MB
Release files / viscy_transforms-0.1.0.tar.gz
| Download URL | viscy_transforms-0.1.0.tar.gz |
|---|---|
| Size | 6.4 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
eba7ea12edc155d3724009656d4670ce928429c5d87acce30a8b57987dbd5dc3
|
|
BLAKE2b-256 checksum How to use checksums |
86d32904b87395e4171cb994dacf5f020260aaef5760741c741a729e9b69dddf
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Aug 20, 2026.
Transparency logRelease files / viscy_transforms-0.1.0-py3-none-any.whl
| Download URL | viscy_transforms-0.1.0-py3-none-any.whl |
|---|---|
| Size | 45.8 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
1716fb9dfb99cb51c8c26c698902138810b0f7d62bfc878149026e6888192870
|
|
BLAKE2b-256 checksum How to use checksums |
5eb2f29a4cd2879dd4428a4c1b3e2f9f8529bbbd9eeb5093ee8b6c7f1d050974
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Aug 20, 2026.
Transparency log
