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.