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libjpeg-turbo cffi bindings and helper classes

Project Description

Python cffi libjpeg-turbo bindings and helper classes.

The purpose of this package is to provide thread-safe and aware of GIL Python
bindings to libjpeg-turbo which work with numpy arrays on
Python 2, 3 and PyPy.

Tested with Python 2.7, Python 3.4 and PyPy on Ubuntu 14.04.

Covered TurboJPEG API:
so, currently, only decoding of jpeg files is possible, and
it is about 1.3 times faster than and
scipy.misc.imread() in a single thread and up to 9 times faster in
multithreaded mode.



1. numpy
2. libjpeg-turbo

On Ubuntu, the shared library is included in libturbojpeg package:
sudo apt-get install libturbojpeg

On Windows, you can download installer from the official libjpeg-turbo [Sourceforge](
repository, install it and copy turbojpeg.dll to the directory from the system PATH.

On Mac OS X, you can download the DMG from the official libjpeg-turbo [Sourceforge](
repository and install it.

If you have a custom library which is TurboJPEG API compatible,
just call jpeg4py.initialize with tuple containing that library's file name.

To install the module run:
python -m pip install jpeg4py
python install
or just copy src/jpeg4py to any place where python interpreter will be able
to find it.


To run the tests, execute:
PYTHONPATH=src python -m nose -w tests

Example usage:

import jpeg4py as jpeg
import matplotlib.pyplot as pp

if __name__ == "__main__":


Released under Simplified BSD License.
Copyright (c) 2014, Samsung Electronics Co.,Ltd.
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File Name & Checksum SHA256 Checksum Help Version File Type Upload Date
jpeg4py-0.1.2.tar.gz (11.2 kB) Copy SHA256 Checksum SHA256 Source Apr 9, 2017

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