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Releases: BiaPyX/BiaPy

Version 3.5.0

06 Aug 22:14
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Major

  • Move from Pytorch 2.2.0 to 2.4.0
  • Increase loss options
  • Add options to choose train/test metrics to measure (TRAIN.METRICS/TEST.METRICS). Also added more metrics to measure in Super-resolution, Image to Image and Self-supervised workflows. Closes #86
  • Allow central point to use an ellipse footprint in Detection workflow
  • Add U-NeXt V1 model
  • Update BMZ code to import, finetune and export v0_4 and v0_5 spec models. Move to bioimageio.core version 0.6.7
  • Avoid loading entire data when creating instance labels
  • Add TEST.DET_IGNORE_POINTS_OUTSIDE_BOX option for Detection workflow
  • Remove data clipping during DA so the user is aware of the transformations
  • Add LOSS.CLASS_REBALANCE option
  • Update all notebooks with more visualization cells and descriptions.

Minor

  • Remove TEST.EVALUATE option
  • Organize better semantic segmentation output
  • Add zoom as preprocessing in test data (only available TEST.BY_CHUNKS == True)
  • Reorganize median filter post-processing by creating TEST.POST_PROCESSING.MEDIAN_FILTER, TEST.POST_PROCESSING.MEDIAN_FILTER_AXIS and TEST.POST_PROCESSING.MEDIAN_FILTER_SIZE. Removing TEST.POST_PROCESSING.YZ_FILTERING, TEST.POST_PROCESSING.YZ_FILTERING_SIZE, TEST.POST_PROCESSING.Z_FILTERING and TEST.POST_PROCESSING.Z_FILTERING_SIZE
  • Go back to use channel 0 as semantic mask to grow the instances in BC channels. Also fix resolution and channel order in edt() call in BP.
  • Remove contrast/brightness EM transformations as they were not used
  • Be more permissive with provided csv file during point mask creation in detection workflow
  • Add -v option to consult BiaPy's version

Fixes

  • Fix resunet++ issue. Closes #95
  • Number of residual groups in RCAN.
  • Correctly read result images when reusing results. Closes #94
  • Avoid loading entire data when creating instance labels. Closes #92
  • Add load checkpoint after training again (last epoch training model has been using before)

New Contributors

Full Changelog: v3.4.6...v3.5.0

Version 3.4.6

06 Jun 13:07
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Minor:

  • Change BMZ interaction to allow training using BiaPy's normalization
  • Add pooch as a dependency
  • Add 'scale_range' norm option
  • Improve image and it corresponding gt file matching in instance seg. workflow

Full Changelog: v3.4.5...v3.4.6

Version 3.4.5

04 Jun 10:50
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Major:

  • Allow training with BMZ models.

Minor:

  • Add SYSTEM.DEVICE option to allow other backends apart from cpu such as macOS chipset

Bugs fixed:

  • Fix minor error when predicting multi-channel data using Zarr
  • Fix bug in per patch loss/IoU calculation with batch size > 1

Full Changelog: v3.4.4...v3.4.5

Version 3.4.4

20 May 13:30
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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

15 May 07:32
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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

29 Apr 14:43
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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

29 Apr 07:13
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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

Version 3.3.15

08 Mar 10:38
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Fix:

  • Preprocessing checking
  • PSNR calculation in I2I and SR workflows

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

Version 3.3.14

08 Mar 10:37
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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