Biapy

Latest version: v3.4.3

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3.4.3

Minor:
- Improve the messaging of some errors to make them more comprehensible for the end user.
- Restrict `TEST.POST_PROCESSING.REPARE_LARGE_BLOBS_SIZE` usage to instance segmentation workflow and ``BP`` channels.
- Allow detection and denoising workflows use `unetr` and `multiresunet` models.
- Change affine `AUGMENTOR.AFFINE_MODE` to `reflect` by default.
- Now the grid in the aumented samples saved take into account the image size to alway create 5x5 grid.
- Adapt MAE's grid mask to be operative in 3D.

Bug fixes:
- 3D stack metric values.
- Fix errors in `DATA.PROBABILITY_MAP`.
- Prevent `TEST.POST_PROCESSING.CLEAR_BORDER` remove all instances in 2D.
- Fix minor bugs during some of the instance segmentation post-processing due image shape mismatch.
- Now `TEST.POST_PROCESSING.CLEAR_BORDER` and `TEST.POST_PROCESSING.VORONOI_ON_MASK` are above `TEST.POST_PROCESSING.MEASURE_PROPERTIES.REMOVE_BY_PROPERTIES` so the instances can be repaired before filtering and stats.
- Minor bugs in detection watershed
- Fix bug during detection mask creation for Zarr images with more than one channel
- Fix process_sample_by_chunks() function call in multi-gpu setting due to recent changes
- Fix errors in percentile clipping
- Avoid stuck processes to jump into inference phase in multi-gpu configuration when setting patience during training
- Fix cross-validation errors: 1) when using it in SR workflow due to its upsampling ; 2) in classification
- Fix bug in grid masking using mae in SSL workflow
- Add preprocessing function into classification
- Minor bug when `C` is not the last channel using Zarr inference

**Full Changelog**: https://github.com/BiaPyX/BiaPy/compare/v3.4.2...v3.4.3

3.4.2

Fix:
- Downgrade scikit-image version to avoid reloading the kernel in Colab notebooks
- I2I workflow inference edge case fixed when multiple images in multiple directories where found leading to an infinite loop.

**Full Changelog**: https://github.com/BiaPyX/BiaPy/compare/v3.4.1...v3.4.2

3.4.1

Minor:
- Add BiaPy version into YAML files

Fix:
- Update pyproject.toml specifiying a few libraries more to not be that restrictive and so BiaPy is smoothly installed in Colab

**Full Changelog**: https://github.com/BiaPyX/BiaPy/compare/v3.4.0...v3.4.1

3.4.0

Major:
- [Allow to train with large Zarr/H5 files without loading data in memory](https://github.com/BiaPyX/BiaPy/commit/009b4e2b4da15ecce2cb99cab36b0a9508adc073)
- [Adapt by_chunks to multichannel data](https://github.com/BiaPyX/BiaPy/commit/de38df853856caa2ffab5f5ae473cc0374d7b7d8)
- [Add option to reuse predictions in test](https://github.com/BiaPyX/BiaPy/commit/923ddad8aec028bc3362c4f0fc16a29c663a525c)

Minor:
- Calculate detection metrics in by_chunks setting
- [Add DATA.NORMALIZATION.CUSTOM_MODE option](https://github.com/BiaPyX/BiaPy/commit/cc62199b7c98872366e065097919f2fc77666829)
- [Add percentile normalization](https://github.com/BiaPyX/BiaPy/commit/e923efcb8b2497d5f8e36f2402d7be7794bf01d5)

Fix:
- [Correct bug when discading samples from training when using TRAIN.MINIMUM_FOREGROUND_PER](https://github.com/BiaPyX/BiaPy/commit/50eef618f5579c9669e03d2909290817afb591ff)
- [Fix PSNR calculation in I2I and SR workflows](https://github.com/BiaPyX/BiaPy/commit/6ab226aabbab57def0c24646b890e170d16c2f5a)
- Update notebooks and correct errors related to gdown package
- [Correct validation paths in generators when in memory is False](https://github.com/BiaPyX/BiaPy/commit/6fb537b1b7acee45934405f51c28a1bf209d7d23)


**Full Changelog**: https://github.com/BiaPyX/BiaPy/compare/v3.3.14...v3.4.0

3.3.15

Fix:
- Preprocessing checking
- PSNR calculation in I2I and SR workflows

**Full Changelog**: https://github.com/BiaPyX/BiaPy/compare/v3.3.14...v3.3.15

3.3.14

New functionality:
- Add multithread detection

Fix:
- ``dense`` contour creation in 3D
- Add grid masking to MAE
- Ensure validation logs prints metric/loss in the same order as with training data
- Solve problems in recently added Image to Image (I2I) workflow
- Correct TTA errors produced by recent changes when added multihead models

**Full Changelog**: https://github.com/BiaPyX/BiaPy/compare/v3.3.13...v3.3.14

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