#!/usr/bin/env python

from distutils.core import setup

setup(
	name		= 'ffn',
	version		= '0.1.0',
	author		= 'Michal Januszewski',
	author_email	= 'mjanusz@google.com',
	packages	= ['ffn', 'ffn.inference', 'ffn.training', 'ffn.utils'],
	scripts		= ['build_coordinates.py', 'compute_partitions.py', 'run_inference.py', 'train.py'],
	url		= 'https://github.com/google/ffn',
	license		= 'LICENSE',
	description	= 'Flood-Filling Networks for volumetric instance segmentation',
	long_description= open('README.md').read(),
	install_requires= ['scikit-image', 'scipy', 'numpy', 'tensorflow', 'h5py', 'PIL', 'absl-py'],
)

#!/usr/bin/env python

from distutils.core import setup

setup(
	name		= 'ffn',
	version		= '0.1.0',
	author		= 'Michal Januszewski',
	author_email	= 'mjanusz@google.com',
	packages	= ['ffn', 'ffn.inference', 'ffn.training', 'ffn.training.models', 'ffn.utils'],
	scripts		= ['build_coordinates.py', 'compute_partitions.py', 'run_inference.py', 'train.py'],
	url		= 'https://github.com/google/ffn',
	license		= 'LICENSE',
	description	= 'Flood-Filling Networks for volumetric instance segmentation',
	long_description= open('README.md').read(),
	install_requires= ['scikit-image', 'scipy', 'numpy', 'tensorflow<2', 'h5py', 'Pillow', 'absl-py'],
)

Add ffn.training.models and switch to Pillow.
Add ffn.training.models and switch to Pillow.

It is still easier to use this repo via git clone rather than pip
install, e.g. from Colab. But this seemed worth updating anyway.
