Model package

This package is supposed to contain the ML model code, which includes image augmentations.

Features

The package is organized as a proper Python package installable via pip (so that no hacks like sys.append or export PYTHONPATH are needed).
Augmentations defined in image_augmentations.py in a testible and extensible way:
- to support a new augmentation from albumentations, just add it to TRANSFORMS and method create_transform will automatically plug it in,
- method get_random_transform_classes uses albumentations names, which allows us to unit-test it separately,
- method apply_augmentation uses inputs/outputs of the level of PIL.Image and albumentations, which makes it understandable for regular data scientists,
- method apply_random_augmentations is what the Flask server will be used: it accepts a PIL image ans some configurations and returns the transformed image and meta-info as a Dict.
All methods in this package are covered via unit tests in test_image_augmentations.py (they're pretty dumb because we don't want to test the logic of albumentations transforms, we just want to make sure that the methods work).
To improve code quality, we implemented linters + auto-formatters (black, flake, isort) and type checker (mypy).