Biapy

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**: https://github.com/BiaPyX/BiaPy/compare/v3.5.9...v3.5.10

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](https://github.com/BiaPyX/BiaPy/blob/master/biapy/utils/scripts/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**: https://github.com/BiaPyX/BiaPy/compare/v3.5.8...v3.5.9

Bugs fixed:
- Fix Torchvision calls for semantic seg, detection and instance segmentation workflows

**Full Changelog**: https://github.com/BiaPyX/BiaPy/compare/v3.5.7...v3.5.8

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**: https://github.com/BiaPyX/BiaPy/compare/v3.5.6...v3.5.7

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**: https://github.com/BiaPyX/BiaPy/compare/v3.5.5...v3.5.6

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**: https://github.com/BiaPyX/BiaPy/compare/v3.5.4...v3.5.5