scikit-ipp 1.2.0

Image processing library powered by Intel(R) IPP

scikit-IPP (skipp)

scikit-ipp is optimization of open-source image processing library scikit-image by using Intel® Integrated Performance Primitives (Intel® IPP) library.

scikit-ipp is a standalone package, provided scikit-image-like API to some of Intel® IPP functions.

• Documentation
• Source Code
• About Intel® IPP

Getting started

scikit-ipp is easily built from source with the majority of the necessary prerequisites available on conda. The instructions below detail how to gather the prerequisites, setting one's build environment, and finally building and installing the completed package. scikit-ipp can be built for all three major platforms (Windows, Linux, macOS).

The build-process (using setup.py) happens in 2 stages:

1. Running cython on C and Cython sources
2. Compiling and linking

Building scikit-ipp using conda-build

The easiest way to build scikit-ipp is using the conda-build with the provided recipe.

Prerequisites

• Python version >= 3.6
• conda-build version >= 3
• C compiler

Building scikit-ipp

cd <checkout-dir>
conda build -c intel conda-recipe

This will build the conda package and tell you where to find it (.../scikit-ipp*.tar.bz2).

Installing the built scikit-ipp conda package

conda install <path-to-conda-package-as-built-above>

To actually use your scikit-ipp, dependent packages need to be installed. To ensure, do

Linux or Windows:

conda install -c intel numpy ipp

Building documentation for scikit-ipp

Prerequisites for creating documentation

• sphinx >= 3.0
• sphinx_rtd_theme >= 0.4
• sphinx-gallery >= 0.3.1
• matplotlib > = 3.0.1

Building documentation

1. Install scikit-ipp into your python environment
2. cd doc && make html
3. The documentation will be in doc/_build/html

Examples

Introductory examples for scikit-ipp link