TIAToolbox 0.7.0

Major and Feature Improvements

• Drops support for python 3.6
• Update minimum requirement to python 3.7
• Adds support for python 3.9
• Adds models base to the repository. Currently, PyTorch models are supported. New custom models can be added. The tiatoolbox also supports using custom weights to pre-existing built-in models.
  • Adds classification package and CNNPatchPredictor which takes predefined model architecture and pre-trained weights as input. The pre-trained weights for classification using kather100k data set is automatically downloaded if no weights are provided as input.
• Adds mask-based patch extraction functionality to extract patches based on the regions that are highlighted in the input_mask. If 'auto' option is selected, a tissue mask is automatically generated for the input_image using tiatoolbox TissueMasker functionality.
• Adds visualisation module to overlay the results of an algorithm.

Changes to API

• Command line interface for stain normalisation can be called using the keyword stain-norm instead of stainnorm
• Replaces FixedWindowPatchExtractor with SlidingWindowPatchExtractor .
• get_patchextractor takes the slidingwindow as an argument.
• Depreciates VariableWindowPatchExtractor

Bug Fixes and Other Changes

• Significantly improved python notebook documentation for clarity, consistency and ease of use for non-experts.
• Adds detailed installation instructions for Windows, Linux and Mac

Development related changes

• Moves flake8 above pytest in the travis.yml script stage.
• Adds set -e at the start of the script stage in travis.yml to cause it to exit on error and (hopefully) not run later parts of the stage.
• Readthedocs related changes
  • Uses requirements.txt in .readthedocs.yml
  • Uses apt-get installation for openjpeg and openslide
  • Removes conda build on readthedocs build
• Adds extra checks to pre-commit, e.g., import sorting, spellcheck etc. Detailed list can be found on this commit.