{ "info": { "author": "Peter Jack Naylor", "author_email": "peter.jack.naylor@gmail.com", "bugtrack_url": null, "classifiers": [ "License :: OSI Approved :: MIT License", "Operating System :: OS Independent", "Programming Language :: Python" ], "description": "dynamic_watershed\n=================\n\nPackage description\n--------------\n\nWe implement the splitting algorithm for splitting nuclei nucleas described in in 'Nuclei segmentation in histopathology images using deep neural networks'. This algorithm is essentially a dynamic watershed.\nThe main function is named: `post_process`.\n\n\nInstallation\n--------------\n\ndynamic_watershed can be installed by unzipping the source code in one directory and using this command: ::\n\n python setup.py install\n\nYou can also install it directly from the Python Package Index with this command (not working yet): :: \n\n pip install dynamic_watershed\n\nExample\n--------------\n```python\n>>> from dynamic_watershed import post_process\n>>> from skimage.io import imread\n>>> probability_image = imread('example.png')\n>>> p1, p2 = 7, 0.5\n>>> result_segmentation = post_process(probability_image, p1, thresh=p2)\n```\n\nLicence\n--------\n\nSee file LICENCE.txt in this folder.\n\n\nContribute\n-----------\ndynamic_watershed is an open-source software. 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