Metadata-Version: 2.1
Name: napari_dab_cellcount
Version: 0.1.4
Summary: A napari plugin for counting cells.
Home-page: https://github.com//ThakurNDLab/napari-dab-cellcount
Author: Jyotirmay Srivastava :: Heavily Inspired from Cellpose-napari
Author-email: jyotirmaysrivastava.in@gmail.com
License: MIT
Classifier: Development Status :: 4 - Beta
Classifier: Framework :: napari
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.9
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Topic :: Scientific/Engineering :: Image Processing
Requires-Python: >=3.9, <3.11
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: napari
Requires-Dist: napari-plugin-engine>=0.1.4
Requires-Dist: PyQt5
Requires-Dist: PyQt5.sip
Requires-Dist: numpy
Requires-Dist: numba
Requires-Dist: scipy
Requires-Dist: torch
Requires-Dist: opencv-python-headless
Requires-Dist: natsort
Requires-Dist: tqdm
Requires-Dist: imagecodecs
Requires-Dist: tifffile
Provides-Extra: docs
Requires-Dist: sphinx>=3.0; extra == "docs"
Requires-Dist: sphinxcontrib-apidoc; extra == "docs"
Requires-Dist: sphinx_rtd_theme; extra == "docs"
Requires-Dist: sphinx-prompt; extra == "docs"
Requires-Dist: sphinx-autodoc-typehints; extra == "docs"

A napari plugin to count cells using a U-Net for cell identification

Model uses ResNet architecture layers as encoders, and requires custom trained model weights (model trained using resnet50 imagenet1_v1 pretrained weights as starting point)

Current Model works well for DAB stained neuronal cells of 30micron mouse brain sections

Install using:
pip install napari_dab_cellcount

Run using:
napari napari_dab_cellcount
