refactoring
- renamed orginal_path to original_path in File
new features:
- added patch iterator
bug fixes:
- install of 0.0.12 failed due to not finding requirements.txt. Requirements are now again specified in the setup.py.
breaking changes
- specific code for external software has been moved to accessories
- label weights in WeightedLabelSampler are now specified via a dictionary
refactoring
- parsing of annotation files has been refactored and now includes a JSON schema
- enhance shape and spacing error messages (Contributed by Jakub Kaczmarzyk)
new features:
- accessories are loaded with package import
- WholeSlideAnnotationParser based on JSON schema
- JSON schema can be used to serialize annotations
- albumentations callback (contributation by Thijs Gelton)
- HedCallback augmentation
- 'none' labels are sorted below other labels
- associater classes StemSplitterAssociater and AnyOneAssociater
- exact match option for associate_files
- clip polygon and check for valid boxed in detection patch label sampler
- MaskPatchLabelSampler now accepts a spacing
- auxiliary method to create yaml from folders with data (contributation by Thijs Gelton)
bug fixes:
- fix for randomness in uniform point sampler
setup file
- version is read from version.py
- requirements are now read from the requirements file (contribution by Thijs Gelton)
- url now points to github repo (contribution by Jakub Kaczmarzyk)
new features:
- image/annotations are now copied to separate folders
- added source configuration
- added one-hot-encoding preset
- dataset and labels are now sorted such that the generator will produce the same output when the seed is set
- minor refactoring
requirements:
- increased NumPy version to make it compatible with ASAP2.0
bug fixes:
- fixed sampling bugs
new features:
- increase speed sampling
bug fixes:
- fixed detection sampling bugs
new features:
-
detection support
-
pyvips image backend support
-
multiple spacings support
-
update call from producers to commander
-
fixed: copy data failed on first trial when using multiple cpus
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