Version 3.5.12

Minor:

• Avoid copying a temporal file to merge updated cfg with the input one
• Add a new function to know the differences between input config and current one
• Add BiaPy version to log

Bugs fixed:

• Always translate input configuration to the current version
• Allow BMZ affinity model consumption
• Fix area calculation in instance segmentation stats
• Add xarray version constraint as the latest xarray-2025.3.0 is crashing in bioimageio.core imports

Full Changelog: v3.5.11...v3.5.12

Version 3.5.11

Major:

• Adapt DFCAN to 3D and add SSIM-based loss
• Adapt RCAN to 3D
• Ensure appropiate data range when calculating metrics in SR, SSL and I2I workflows.
• Implement more data/sample filtering methods: 'target_mean', 'target_min', 'target_max', 'diff', 'diff_by_min_max_ratio', 'diff_by_target_min_max_ratio'
• Distribute better loading data code into classes
• Add in all most code Typing checks for Pydantic/Pylance
• Rename 'custom' normalization into 'zero_mean_unit_variance'
• Separate into a class the normalization module to reduce repeated code
• Avoid doing normalization for test GT data in I2I, SR, SSL and Denoising
• Organize metrics for I2I, SR and SSL depending on train and test
• Avoid creating X data during Instance segmentation saving disk space
• Improve Detection workflow when multihead output is created
• Add SSIM, W_MAE_SSIM and W_MSE_SSIM losses for I2I, SR and SSL workflows
• Move some variables from TEST.BY_CHUNKS to DATA.TEST

Minor:

• Change 2D image load to be more robust
• BMZ connection:
  • Add task description option
  • Add model version
  • Change env.yaml created
  • Change BMZ model import message error
  • Add more Instance segmentation model support when consuming BMZ models
• Allow multiple ddp runs without closing the process group initialization
• Add script to change a parameter in the RDF file of a BMZ model
• Update DDP messages and wait points
• Remove mixed precision in evaluation
• Add find_unused_parameters when using resunet_se with DDP
• Add more information while gathering training/validation data
• Add more options to tune RCAN model
• Add script for blur estimation
• Add script to measure similarity metrics common in I2I and SR workflows
• Add tensor conversion in metric calculation
• Add changes to convert_old_model_cfg_to_current_version in order to convert old configurations into new
• Upgrade filtering saving examples of the patches/images filtered so the user can check them
• Change DATA.FILTER_BY_IMAGE default value to False
• Wrap rotate function to allow float16

Bugs fixed:

• Fix minor bug in instance segmentation when test is not enabled and test path does not exist
• Instance masks folder name update to not set always contour info
• Solve bugs in U-Next V1 and U-Next V2 models when using more than one channel
• Fix 3D U-NeXt models
• BMZ connection:
  • Resize cover to ensure the shape
  • Avoid adding duplicate tags
  • Ensure only a patch is taken for BMZ input when working with H5/Zarr files
  • Ensure only pytorch_state_dict models are consumed
• Correct C channel activation during Instance segmentation when it is used alone.
• Fix minor error during MODEL.BMZ.EXPORT.DATASET_INFO check
• Solve minor bug in convert_old_model_cfg_to_current_version function
• Fix conversion to RGB in generators
• Fix problem with TEST.REDUCE_MEMORY
• Calculate metrics when reusing predictions (TEST.REUSE_PREDICTIONS). They are calculated as "merge_patches"
• Allow SSL pretrainings during model check
• Add restrictions in SR, SSL and I2I workflows to not use wdsr in 3D

Full Changelog: v3.5.10...v3.5.11

Version 3.5.10

Minor:

• Disable mixed precision calls
• Move data IO management to biapy/data and create imread/imwrite functions to avoid using skimage.io as they are deprecating these functions
• Change timm.optim call to avoid warning of future deprecation
• BioImage Model Zoo related (BMZ) changes:
  • Add function to autogenerate a documentation.md
  • Move BMZ related functions to bmz_utils.py
  • Add test_model at the end of BMZ model creation with a larger tolerance than the default so the differences due to casting are allowed
  • Create cover extracting a patch containing mask information
  • Add argument to provide the dataset id when exporting a BMZ model
  • Ensure weights_only=True during checkpoint loading stage when building a BMZ model

Bugs fixed:

• Checkpoint load on DDP right after training fixed
• Update installation restricting torchmetric version to avoid an issue in classification workflow

Full Changelog: v3.5.9...v3.5.10

Version 3.5.9

Major:

• Add synapse segmentation options for instance segmentation (in experimental state)

Minor:

• Add script to convert instance segmentation datasets into detection workflow format
• Print a better message when shapes does not match between samples
• Some variables for detection has been modified and now don't need to be set per class values:
  • Change TEST.POST_PROCESSING.REMOVE_CLOSE_POINTS_RADIUS default value to 0
  • Change TEST.POST_PROCESSING.DET_WATERSHED_FIRST_DILATION default value to [-1,-1]
  • Change TEST.DET_MIN_TH_TO_BE_PEAK default value to 0.2
  • Change TEST.DET_TOLERANCE default value to 10
• Add instance segmentation multihead test in run_checks.py
• Update convert_old_model_cfg_to_current_version function to cover new changes

Bugs fixed:

• Handle multiple data within Zarr/H5 during test
• Delete channel restriction when ensuring 3D shape (convert_instance_data_to_detection.py)
• Fix class prediction to the points in detection
• Fix error with diplib package
• Fix issue between TRAIN.PATIENCE and TRAIN.LR_SCHEDULER.REDUCEONPLATEAU_PATIENCE
• Solve issues with data type during detection watershed so the instance properties can be measured with diplib as it does not support int64 data type
• Fix issue when multiple raw images (lightmycells case) were provided
• Fix issue with BMZ model exportation
• Solve issues with run_checks.py due to recent changes. Now it is correctly reporting when a test crashes as it will crash too.

Full Changelog: v3.5.8...v3.5.9

Version 3.5.8

Bugs fixed:

• Fix Torchvision calls for semantic seg, detection and instance segmentation workflows

Full Changelog: v3.5.7...v3.5.8

Version 3.5.7

Major:

• Rebuilt CartoCell tutorial organization and update notebooks.
• Update templates to follow the same configuration as in the notebooks, which achieve good results in the example datasets.

Minor:

• Improve robustness loading 3D images
• Make SurfaceArea only requested in 3D images
• Update example dataset paths to raw and label in most cases to be consistent

Bugs fixed:

• Fix bug during TEST.REDUCE_MEMORY
• Fix errors while loading H5 nested data
• Solve bug when loading Zarr/H5 files into memory for training
• Fix missing import in some workflows
• Changes in instance segmentation's statistic calculation:
  • Add diplib library as a dependency to calculate surface area more precisely and enable elongation for 3D which is P2A in diplib
  • Correct centroid coordinates
  • Make SurfaceArea only requested in 3D images to accelerate the process
• Fix bug in the filtering while predicting by chunks

Full Changelog: v3.5.6...v3.5.7

Version 3.5.6

Major:

• Add configuration file backward-compatibility
• Add U-NeXt V2 model
• Actions added:
  • Add check_code_consistency.yml action to test code consistency (every week)
  • Add upload_biapy_to_pypi.yml to automatically create a PyPI package (when a new release is created)
  • Add create_release_container.yml file to automatically create and update docker containers to Dockerhub (when a new release is created)

Minor:

• Update BMZ model creation and compatibility:
  • Add cover creation and create environment.yaml to be packaged in the BMZ model
  • Add sigmoid activation as BMZ postprocessing so we are more compatible
  • Extract just the pytorch_state_dict from the checkpoint when creating BMZ package
  • Save correct input/output (prediction) for BMZ package
  • Move to bioimageio.core==0.7.0
  • Change slightly the normalization so it can match the one done in BMZ

Bugs fixed:

• Fix BMZ model compatibility checks
• Update notebooks to avoid BMZ error when fields are None
• Fix bug on BMZ zip creation in the notebooks
• Fix missing letter 'S' in configuration variable 'SIGNS'.
• Disabling percentile clipping as that is not done by default in BMZ's scale_range normalization

Full Changelog: v3.5.5...v3.5.6

Version 3.5.5

Major:

• Add backward compatibility loading checkpoint

Minor:

• Change TEST.POST_PROCESSING.MEASURE_PROPERTIES.REMOVE_BY_PROPERTIES.STAT to TEST.POST_PROCESSING.MEASURE_PROPERTIES.REMOVE_BY_PROPERTIES.STATS
• Only check lr scheduler when train in enabled

Bugs fixed:

• Fix a bug in DATA.FILTER_BY_IMAGE
• Update 3D_cell_detection_zarr_tutorial.yaml with new configuration

Full Changelog: v3.5.4...v3.5.5

Version 3.5.4

Major:

• Add BMZ exportation through configuration

Minor:

• Set automatically BMZ path and change it to PATHS.BMZ_EXPORT_PATH

Bugs fixed:

• Fix minor bug when loading model checkpoint
• Fix small bug in semantic seg. multiclass jaccard calculation

Full Changelog: v3.5.3...v3.5.4

Version 3.5.3

Major:

• Update BMZ model check to support more models and increase it's robustness.

Minor:

• Add class extraction for semantic seg. BMZ models.
• Adapt instance segmentation channels to a default value depending when loading BMZ models.
• Change LOAD_MODEL_FROM_CHECKPOINT default value to True.
• Increase UNETR building process robustness

Bugs fixed:

• Fix bug when filtering by entire images.
• Prevent top-5-accuracy when classes are less than 5 in classification workflow.
• Fix bug in single data generator used in classification and SSL workflows.
• Allow BMZ/Torchvision models override completely configuration with the variables they are imposing by making update_dependencies() config function more generic.
• Force entire image filtering when DATA.EXTRACT_RANDOM_PATCH is enabled.

Full Changelog: v3.5.2...v3.5.3