PyAFBF 0.2.4

Sample image textures from anisotropic fractional Brownian fields

The Package PyAFBF is intended for the simulation of rough anisotropic image textures. Textures are sampled from a mathematical model called the anisotropic fractional Brownian field. More details can be found on the documentation.

Package features

• Simulation of rough anisotropic textures,

• Computation of field features (semi-variogram, regularity, anisotropy indices) that can serve as texture attributes,

• Random definition of simulated fields,

• Extensions to related fields (deformed fields, intrinsic fields, heterogeneous fields, binary patterns).

Installation from sources

The package source can be downloaded from the repository.

The package can be installed through PYPI with

pip install PyAFBF

To install the package in a Google Collab environment, please type

!pip install imgaug==0.2.6

!pip install PyAFBF

Communication to the author

PyAFBF is developed and maintained by Frédéric Richard. For feed-back, contributions, bug reports, contact directly the author, or use the discussion facility.

Licence

PyAFBF is under licence GNU GPL, version 3.

Citation

When using PyAFBF, please cite the original paper

8. Biermé, M. Moisan, and F.J.P. Richard. A turning-band method for the simulation of anisotropic fractional Brownian field. J. Comput. Graph. Statist., 24(3):885–904, 2015.

and the JOSS paper:

F.J.P. Richard. PyAFBF: a Python library for sampling image textures from the anisotropic fractional Brownian field. Journal of Open Source Software, 7(75):3821, 2022.

Contents

• Quick start guide

  • Getting started

  • Customed models

  • Tuning model parameters

  • Model features

  • Simulating with turning-band fields

• Example gallery

  • Basic examples

  • Extended anisotropic fields

  • Heterogeneous fields

  • Related anisotropic fields

• API: main classes

  • AFBF (field)

  • Turning band field (tbfield)

• API: auxiliary classes

  • Periodic functions (perfunction)

  • Coordinates (coordinates)

  • Spatial data (sdata)

  • Process (process)

  • Turning bands (tbparameters)

  • ndarray

Credits

PyAFBF is written and maintained by Frederic Richard, Professor at Aix-Marseille University, France.