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Simple linear iterative clustering (SLIC) in a region of interest (ROI)

Project description

maskSLIC

Simple linear iterative clustering (SLIC) in a region of interest

Outline

This code demonstrates the adaption of SLIC for a defined region of interest. The main contribution is in the placement of seed points within the ROI.

The code is a modification of the SLIC implementation provided by Scikit-image (http://scikit-image.org/)

An online demo is available at: http://maskslic.birving.com/index

An outline of the method is available at: http://arxiv.org/abs/1606.09518

Figure 1: An example region and the automatically placed seed points using this method.

seed points

Figure 2: The final superpixel regions within the ROI

superpixels

Getting started

Install dependencies
pip install -r requirements.txt

build cython code
python setup.py build_ext --inplace

run example
python run_example.py

Using a python virtualenv is reccommended on linux to get the latest versions of the dependencies.

Development

This code is still a work in progress.

Project details


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Source Distribution

maskslic-0.3.4.post2.tar.gz (17.9 kB view hashes)

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