Metadata-Version: 2.4
Name: PixMClass
Version: 0.1.6
Summary: Multiclass pixel classification
Home-page: https://github.com/jeanollion/pix_mclass
Download-URL: https://github.com/jeanollion/pix_mclass/releases/download/v0.1.6/pix_mclass-0.1.6.tar.gz
Author: Jean Ollion
Author-email: jean.ollion@sabilab.fr
Keywords: Segmentation,Classification,Microscopy,Cell
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Image Processing
Classifier: License :: OSI Approved :: GNU General Public License v3 or later (GPLv3+)
Classifier: Programming Language :: Python :: 3
Requires-Python: >=3
Description-Content-Type: text/markdown
License-File: LICENSE.txt
Requires-Dist: numpy
Requires-Dist: scipy
Requires-Dist: tensorflow>=2.7.1
Requires-Dist: dataset_iterator>=0.5.8
Requires-Dist: elasticdeform>=0.4.7
Dynamic: author
Dynamic: author-email
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
Dynamic: download-url
Dynamic: home-page
Dynamic: keywords
Dynamic: license-file
Dynamic: requires-dist
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# Multiclass pixel classifier
Deep learning segmentation method with very low annotation requirement.

Similar to [Ilastik pixel classification](https://www.ilastik.org/documentation/pixelclassification/pixelclassification) procedure, but based on a deep neural network.

Described and used in the work [Near-infrared co-illumination of fluorescent proteins reduces photobleaching and phototoxicity](https://doi.org/10.1038/s41587-023-01893-7). Please cite this work when using this method. 

Docuementation: see this [tutorial](https://github.com/jeanollion/bacmman/wiki/Train-and-use-PixMClass)
