Preprocessing module for large histological images.
Reason this release was yanked:
missing dependecies
Project description
HistoPrep
Preprocessing large histological slides for machine learning made easy!
Description
This module allows you to cut and preprocess large histological slides. Some of the features include:
- Cut large whole slide image (WSI) into tiles of desired size.
- Dearray individual tissue microarray (TMA) spots from a large slide image.
- Easily detect and discard blurry images or images with artifacts after cutting.
- Save a lot of tears while preprocessing images.
Requirements
python >= 3.8
and openslide
sudo apt-get install openslide-tools
Installation
# install as a module
pip install histoprep
# install as an executable
git clone https://github.com/jopo666/HistoPrep
Usage
HistoPrep can be used either as a module...
import histoprep as hp
cutter = hp.Cutter('/path/to/slide', width=512, overlap=0.25)
cutter.save('/path/to/output_folder')
or as an excecutable!
python3 HistoPrep cut ./input_dir ./output_dir --width 512 --overlap 0.25 --img_type jpeg
Examples
Detailed examples with best practices:
Documentation
Work in progress! Each function does have a detailed __doc__
explaining the use of each argument.
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