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Releases: BiaPyX/BiaPy

Version 3.3.9

19 Feb 16:46
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Quick patch:

  • Fix identation error in some models.

Full Changelog: v3.3.8...v3.3.9

Version 3.3.8

19 Feb 15:40
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Fix:

  • Separate SYSTEM.NUM_CPUS from SYSTEM.NUM_WORKERS

Full Changelog: v3.3.7...v3.3.8

Version 3.3.7

19 Feb 15:39
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Changes:

  • Now DATA.TEST.ARGMAX_TO_OUTPUT defaults to True
  • Add multi-head in instance segmentation workflow to identify the class of each instance

Fixes:

  • Change rotate to scipy so it can be used with 3D images
  • Change TTA to allow multiple heads as output of the network
  • Fix minor error in BMZ export
  • Fix edge case when using DATA.REFLECT_TO_COMPLETE_SHAPE
  • Reduce memory comsuption in merge functions

Full Changelog: v3.3.6...v3.3.7

Version 3.3.6

15 Feb 14:48
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Changes:

  • AUGMENTOR.RANDOM_ROT and AUGMENTOR.ROT90 now are implemented in BiaPy and not done through imgaug.
  • Add TRAIN.VERBOSE to visualize more or less info during each batch process print

Fixes:

  • Fix 4 dims length Zarr data creation during TEST.BY_CHUNKS.
  • Change slightly custom architectures (MODEL.SOURCE == biapy) so they can be converted into TorchScript via torch.jit.script() to create BMZ package.
  • Fix U-Net like models for SR to depend on PROBLEM.SUPER_RESOLUTION.UPSCALING factor and allow MODEL.Z_DOWN in super-resolution workflow
  • Limit number of workers per GPU for safety
  • Fix crappify issues for SSL

Version 3.3.5

13 Feb 14:13
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Fix patch:

  • Rename PROBLEM.NUM_CPUS to PROBLEM.NUM_WORKERS to clarify its usage.
  • Speed up SSL workflow

Version 3.3.4

08 Feb 18:25
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Changes:

  • Set TEST.DET_EXCLUDE_BORDER to False by default.
  • Add TEST.DET_PEAK_LOCAL_MAX_MIN_DISTANCE.
  • 3 int tuple for TEST.RESOLUTION in instance segmentation if TEST.ANALIZE_2D_IMGS_AS_3D_STACK.
  • Prevent usage of EfficientNet architectures for 3D.
  • Add PROBLEM.INSTANCE_SEG.WATERSHED_BY_2D_SLICE.

Fix:

  • Prevent creating multiple processes to manage data if low samples are available.
  • Solve EfficientNet issue with biapy backend as discussed here.
  • Bug in instance seg when no labels are provided.
  • Disable aug sample image generation if DA is disabled.
  • Fix SSL bug during training due to recent changes.

Version 3.3.3

03 Feb 16:55
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Fixes:

  • Change DATA.PREPROCESS.*.ACTIVATE to DATA.PREPROCESS.*.ENABLE as the rest of the variables in all the files (changed only in config.py by error).
  • Separate per_image, full_image and as_3D_stack instance files in different folders.
  • Separate instance segmentation metrics when multiple choices are selected. Before full_image and per_image metrics were mixed.
  • Simplify inference by setting as default patch/merge reconstruction of the prediction. This implied to remove TEST.STATS and leave only FULL_IMG to be optional.
  • TEST.FULL_IMG to False by default.

Version 3.3.2

01 Feb 12:44
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Quick patch to fix some issues:

  • Move sys.exit() call to main.py to prevent errors inside jupyter notebooks
  • Fix issue during BMZ export in classification
  • Rename DATA.PREPROCESSING.*.ACTIVATE to ENABLE as in other variables.
  • Remove DATA.PREPROCESS.MEDIAN_BLUR.FOOTPRINT as it is a Numpy array and it can not be declared through YACS

Version 3.3.1

31 Jan 09:01
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Quick patch to fix some issues:

  • Fix FORCE_RGB variable usage in classification
  • Adapt skimage's relabel_sequential() to be as the old function we were using so the matching metrics process doesn't get stuck anymore.

Version 3.3.0

29 Jan 15:39
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General changes

Major

  • Separate instance filtering and statistical measurements with TEST.POST_PROCESSING.MEASURE_PROPERTIES and TEST.POST_PROCESSING.MEASURE_PROPERTIES.REMOVE_BY_PROPERTIES
  • Add sphericity (3D), perimeter/surface area (2D/3D) and elongation (2D) calculations using the same formulas as described in MorphoLibJ
  • Multi-GPU prediction by chunks (Zarr/H5):
    • Add versatile axis order
    • Fix some overlap errors
  • Add data preprocessing options:
    • Resize
    • Gaussian blur
    • Median blur
    • Histogram matching
    • Contrast Limited Adaptive Histogram Equalization (CLAHE)
    • Canny or edge detection (only 2D - grayscale or RGB)
  • Change BiaPy into a class so we can call functions individually (e.g. BMZ model exportation)
  • Detection:
    • Add overlap in detection during multi-GPU prediction by chunks
    • Now point coords work in global position

Minor

  • Add TEST.DET_EXCLUDE_BORDER option

Bugs fixed:

  • 2D test time augmentation bug with MODEL.N_CLASSES solved
  • Fix bug when TEST.BY_CHUNKS selected using TEST.BY_CHUNKS.INPUT_IMG_AXES_ORDER of len 4.
  • Avoid dividing with zero during instance stats