jpegtran-cffi is a Python package for fast JPEG transformations. Compared to other, more general purpose image processing libraries like wand-py or PIL/Pillow, transformations are generally more than twice as fast (see Benchmarks). In addition, all operations except for scaling are lossless, since the image is not being re-compressed in the process. This is due to the fact that all transformation operations work directly with the JPEG data.
This is achieved by using multiple C routines from the Enlightenment project's epeg library (for scaling) and the `turbojpeg`_ library from the libjpeg-turbo project (for all other operations). These routines are called from Python through the CFFI module, i.e. no external processes are launched.
The package also includes rudimentary support for getting and setting the EXIF orientation tag, automatically transforming the image according to it and obtaining the JFIF thumbnail image.
jpegtran-cffi was developed as part of a web interface for the spreads project, where a large number of images from digital cameras had to be prepared for display by a Raspberry Pi. With the Pi's rather slow ARMv6 processor, both Wand and PIL were too slow to be usable.
- CPython >=2.6 or >=3.3 or PyPy
- cffi >= 1.0
- libturbojpeg with headers
$ pip install jpegtran-cffi
There is a bug in some Ubuntu versions of the libturbojpeg package
that prevents the package from installing correctly. If you get the
relocation R_X86_64_32 against .data can not be used..., please
perform the following command:
sudo ln -s /usr/lib/x86_64-linux-gnu/libturbojpeg.so.0.1.0 /usr/lib/x86_64-linux-gnu/libturbojpeg.so
from jpegtran import JPEGImage img = JPEGImage('image.jpg') # JPEGImage can also be initialized from a bytestring blob = requests.get("http://example.com/image.jpg").content from_blob = JPEGImage(blob=blob) # Reading various image parameters print img.width, img.height # "640 480" print img.exif_orientation # "1" (= "normal") # If present, the JFIF thumbnail can be obtained as a bytestring thumb = img.exif_thumbnail # Transforming the image img.scale(320, 240).save('scaled.jpg') img.rotate(90).save('rotated.jpg') img.crop(0, 0, 100, 100).save('cropped.jpg') # Transformations can be chained data = (img.scale(320, 240) .rotate(90) .flip('horizontal') .as_blob()) # jpegtran can transform the image automatically according to the EXIF # orientation tag photo = JPEGImage(blob=requests.get("http://example.com/photo.jpg").content) print photo.exif_orientation # "6" (= 270°) print photo.width, photo.height # "4320 3240" corrected = photo.exif_autotransform() print corrected.exif_orientation # "1" (= "normal") print corrected.width, corrected.height # "3240 4320"
For more details, refer to the API Reference.
All operations were done on a 3.4GHz i7-3770 with 16GiB of RAM and a 7200rpm HDD with the following 2560x1920 8bit RGB JPEG:
Both wand-py and PIL were run with the fastest scaling algorithm available,
for wand-py this meant using
Image.sample instead of
and for PIL the nearest-neighbour filter was used for the
The MIT License (MIT)
Copyright (c) 2014 Johannes Baiter <firstname.lastname@example.org>
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