Version 3.3.8

Fix:

• Separate SYSTEM.NUM_CPUS from SYSTEM.NUM_WORKERS

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

Version 3.3.7

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

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

Fix patch:

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

Version 3.3.4

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

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

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

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

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

Version 3.2.0

General changes

Major

• Fix TTA bug in full image prediction
• Add Bioimage Model Zoo (BMZ) as a source to load pretrained models for inference
• Add option to export a model into BMZ format
• Add TorchVision as a source for building models
• Add TEST.BY_CHUNKS.INPUT_IMG_AXES_ORDER to control the order of the Zarr/H5 input image axes
• Change project structure to be able to call BiaPy through command line

Minor

• Add CODE_OF_CONDUCT.md
• Changed variable default values:
  • PROBLEM.INSTANCE_SEG.DATA_CHECK_MW to False
  • PROBLEM.DETECTION.DATA_CHECK_MW to False
  • DATA.VAL.SPLIT_TRAIN to 0.1
  • Remove TEST.MATCHING_SEGCOMPARE not used
• Add imagecodec as dependency so all TIFF files are loaded
• Increase timeout in TEST.BY_CHUNKS setting

Bugs fixed:

• Fix bug using TEST.BY_CHUNKS when no GPU is used
• Fix bug in cross validation for workflows that do not require GT (e.g. denoising)
• Fix semantic seg issues in multiclass
• Fix bug in image saving when Z axis is less than 5