epyseg

EPySeg

EPySeg is a package for segmenting 2D epithelial tissues. EPySeg also ships with a graphical user interface that allows for building, training and running deep learning models. Training can be done with or without data augmentation (2D-xy and 3D-xyz data augmentation are supported). EPySeg relies on the segmentation_models library. EPySeg source code is available here. Cloud version available here.

Install

1. Install Miniconda (if not already present on your system)

2. Then in a command prompt type:

conda create -y -n TA python==3.10.12
conda activate TA
pip install -U pip
pip install -U epyseg
python -m epyseg

NB:

• To open a command prompt on Windows press 'Windows'+R then type 'cmd'
• To open a command prompt on MacOS press 'Command'+Space then type in 'Terminal'

Run

To open the graphical user interface, type the following in a command:

conda activate TA
python -m epyseg

Third party libraries

Below is a list of the 3^rd party libraries used by EPySeg and/or pyTA.

IMPORTANTLY: if you disagree with any license below, please uninstall EPySeg.

Library name	Use	Link	License
tensorflow	Deep learning library	https://pypi.org/project/tensorflow/	Apache 2.0
segmentation-models	Models	https://pypi.org/project/segmentation-models/	MIT
czifile	Reads Zeiss .czi files	https://pypi.org/project/czifile/	BSD (BSD-3-Clause)
Markdown	Python implementation of Markdown	https://pypi.org/project/Markdown/	BSD
matplotlib	Plots images and graphs	https://pypi.org/project/matplotlib/	PSF
numpy	Array/Image computing	https://pypi.org/project/numpy/	BSD
Pillow	Reads 'basic' images (.bmp, .png, .pnm, ...)	https://pypi.org/project/Pillow/	HPND
PyQt5	Graphical user interface (GUI)	https://pypi.org/project/PyQt5/	GPL v3
PyQt6	Graphical user interface (GUI)	https://pypi.org/project/PyQt6/	GPL v3
read-lif	Reads Leica .lif files	https://pypi.org/project/read-lif/	GPL v3
scikit-image	Image processing	https://pypi.org/project/scikit-image/	BSD (Modified BSD)
scipy	Great library to work with numpy arrays	https://pypi.org/project/scipy/	BSD
tifffile	Reads .tiff files (also reads Zeiss .lsm files)	https://pypi.org/project/tifffile/	BSD
tqdm	Command line progress	https://pypi.org/project/tqdm/	MIT, MPL 2.0
natsort	'Human' like sorting of strings	https://pypi.org/project/natsort/	MIT
numexpr	Speeds up image math	https://pypi.org/project/numexpr/	MIT
urllib3	Model architecture and trained models download	https://pypi.org/project/urllib3/	MIT
qtawesome	Elegant icons in pyTA	https://pypi.org/project/QtAwesome/	MIT
pandas	Data analysis toolkit	https://pypi.org/project/pandas/	BSD (BSD-3-Clause)
numba	GPU acceleration of numpy ops	https://pypi.org/project/numba/	BSD
elasticdeform	Image deformation (data augmentation)	https://pypi.org/project/elasticdeform/	BSD
CARE/csbdeep	pyTA uses custom trained derivatives of the CARE surface projection model to generate (denoised) surface projections	https://pypi.org/project/csbdeep/	BSD (BSD-3-Clause)