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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 (when numpy is fully implemented). It was tested with
Python 2.7, Python 3.3 and PyPy on Ubuntu 13.10.

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
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 install
or just copy src/jpeg4py to any place where python interpreter will be able
to find it.


To run the tests, execute:

for Python 2.7:
PYTHONPATH=src nosetests -w tests
for Python 3.3:
PYTHONPATH=src nosetests3 -w tests
for PyPy:
PYTHONPATH=src pypy 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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Filename, size & hash SHA256 hash help File type Python version Upload date
jpeg4py-0.1.0.tar.gz (11.0 kB) Copy SHA256 hash SHA256 Source None Mar 20, 2014

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