Version 3.4.6

v3.4.6

Change BMZ interaction to allow training using BiaPy's normalization

Version 3.4.5

v3.4.5

Update notebooks with the new version

Version 3.4.4

Major:

• Add I2I workflow notebooks

Minor:

• Allow I2I workflow to be operative for 3D images
• Add I2I YAML templates
• Add I2I 3D experiment in run_check.py

Fix:

• Correct models' activation check

Full Changelog: v3.4.3...v3.4.4

Version 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: v3.4.2...v3.4.3

Version 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: v3.4.1...v3.4.2

Version 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: v3.4.0...v3.4.1

Version 3.4.0

Major:

• Allow to train with large Zarr/H5 files without loading data in memory
• Adapt by_chunks to multichannel data
• Add option to reuse predictions in test

Minor:

• Calculate detection metrics in by_chunks setting
• Add DATA.NORMALIZATION.CUSTOM_MODE option
• Add percentile normalization

Fix:

• Correct bug when discading samples from training when using TRAIN.MINIMUM_FOREGROUND_PER
• Fix PSNR calculation in I2I and SR workflows
• Update notebooks and correct errors related to gdown package
• Correct validation paths in generators when in memory is False

Full Changelog: v3.3.14...v3.4.0

Version 3.3.15

Fix:

• Preprocessing checking
• PSNR calculation in I2I and SR workflows

Full Changelog: v3.3.14...v3.3.15

Version 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: v3.3.13...v3.3.14

Version 3.3.13

Fix:

• Fix normalization issue during test image reconstruction in SSL and SR workflows

Full Changelog: v3.3.11...v3.3.12