cytounet 0.2.0

Deep Learning based Cell Segmentation

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Installation

From PyPI:

pip install cytounet

From source or to use without installing locally:

git clone https://github.com/Nelson-Gon/cytounet.git
# proceed with usual source build procedure

Or:

pip install git+https://github.com/Nelson-Gon/cytounet.git

Import

from cytounet.model import *
from cytounet.data import *
from cytounet.augmentation import *

Detailed Sample Usage

Please see the following examples:

• Predicting Embryonic DIC Image Labels with Keras

• Chinese Hamster Ovary Segmentation

Visually:

For more examples or to add your own, please see the examples folder.

Is it supported?

A checked box indicates support. You can either add more feature requests here or tackle unchecked boxes and make a pull request to add such support.

• Custom Number of Layers

• Single class segmentation

• Grayscale images

• Model Validation

• Multi-class segmentation

• Colored image input

• COCO Datasets

• CSV Based Annotations

• XML Based Annotations

Frequently Asked Questions

Please read our Wiki Pages

To raise an issue or question

If the wiki does not answer your question, please raise a new issue. You can also open an issue if you have any discussion, criticism, or bug reports.

Thank you very much.

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References

• Mouse Embryos Dataset obtained from Broad Bioimage Benchmark Collection. Source.

• Red Blood Cell Images provided by Anne Carpenter and Roger Wiegand, available here

• Chinese Hamster Ovary Cells provided by Koos et al.(2016)

Credits

• This repository started out as a clone of zhixuhao's original unet implementation.

This repository has considerably diverged from the original implementation hence the need to distribute it separately.

This decision was taken in part due to the relative inactivity of the original implementation which would have made it harder to collaborate. Please take a look at the list of changes from the original implementation.

• The Unet algorithm was introduced by Ronneberger et al. in their paper.