Overview

The scikit-gtimage (standing for ‘’graph tools for image analysis’‘), skgtimage for package aims at providing graph-based tools for image interpretation. It implements a method, based on an inexact graph matching technique, for retrieving and identifying a set image regions, from an initial oversegmentation, using a priori declared qualitative inclusion and photometric relationships between the set of image regions. This package is distributed under the 3-Clause BSD license.

Installation

Dependencies

The proposed scikit-gtimage package is tested to work under Python 3.5.2 (should work for > 3.5.2), not with Python 2 !

The required dependencies are:

  • numpy (tested with 1.11.3)
  • scipy (tested with 0.18.1)
  • Pillow (tested with 4.0.0)
  • matplotlib (tested with 2.0.0)
  • networkx (tested with 1.11)
  • scikit-image (tested with 0.12.3)
  • scikit-learn (tested with 0.18.1)

Using miniconda, required dependencies can be installed as following:

  • install miniconda (python 3.5): https://conda.io/miniconda.html
  • conda install numpy
  • conda install scipy
  • conda install Pillow
  • conda install matplotlib
  • conda install networkx
  • conda install scikit-image
  • conda install scikit-learn

Optionally (not required), for displaying and exporting graphs, you need to install pygraphviz (using pip for instance: pip install pygraphviz). Note that pygraphviz requires graphviz.

Testing

Simply unzip the archive and run provided examples (from the root directory of the unzipped archive) :

python example1.py

python example2.py

Note: depending on your system, you may run: python3 example1.py , python3 example2.py

Using

Add the root directory of the archive to the PYTHONPATH environment variable.