Releases: BiaPyX/BiaPy
Releases · BiaPyX/BiaPy
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)
- Add
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
- Add cover creation and create
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
toTEST.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 toTrue
. - 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
Version 3.5.2
Major:
- Add
'resunet_se'
to I2I workflow - Extend BMZ model support
- Remove
DATA.TRAIN.MINIMUM_FOREGROUND_PER
. Now for training, validation and test a sample filtering can be made withDATA.TRAIN.FILTER_SAMPLES
,DATA.VAL.FILTER_SAMPLES
andDATA.TEST.FILTER_SAMPLES
respectively.
Minor:
- Add
MODEL.LOAD_MODEL_FROM_CHECKPOINT
variable DATA.PREPROCESS.MEDIAN_BLUR.FOOTPRINT
changed toDATA.PREPROCESS.MEDIAN_BLUR.KERNEL_SIZE
- Add robust semantic mask check using
DATA.*.CHECK_DATA
- Divide BMZ model check into two functions so they can be reused easily by the GUI
- Change BMZ COLLECTION_URL to a new version of it
Bugs fixed:
- Fix bug in detection workflow when predicting with Zarr/H5 by chunks
- Minor fix during instance training data creation using Zarr
- Correct minor errors during BMZ model import/export
Full Changelog: v3.5.1...v3.5.2
Version 3.5.1
Major:
- Add GRN, ConvNeXtBlock_V2 and UpConvNeXtBlock_V2 blocks
Minor:
- Change
CENTRAL_POINT_DILATION
from int to list - Add support for fixed_zero_mean_unit_variance preprocessing for BMZ models
- Adapt BMZ model check function to work properly with models in 0.4 and 0.5 version
Bugs fixed:
- Bug in instance segmentation using only
C
channel - Correct tags in BMZ model creation
- Adapt BMZ model check function to work properly with models in 0.4 and 0.5 version
Full Changelog: v3.5.0...v3.5.1
Version 3.5.0
Major
- Move from Pytorch
2.2.0
to2.4.0
- 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
version0.6.7
- 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
andTEST.POST_PROCESSING.MEDIAN_FILTER_SIZE
. RemovingTEST.POST_PROCESSING.YZ_FILTERING
,TEST.POST_PROCESSING.YZ_FILTERING_SIZE
,TEST.POST_PROCESSING.Z_FILTERING
andTEST.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 inedt()
call inBP
. - 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
- @anepaniagua made their first contribution in #85
Full Changelog: v3.4.6...v3.5.0
Version 3.4.6
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
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
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