osaic
osaic is a simple python module which let you create mosaics from
images by issuing a simple python -mosaic foo.jpg
command.
The basic idea is to take as input a set of images: the first is used as background for the final mosaic; the others are indexed by average colors and pated, as tiles, over the final mosaic.
In addition, users are enabled to specify the final size of the mosaic (relative to the size of the initial target image) and the number of tiles to use per side.
Dependencies
The module depends on python PIL
library (automatically fetched by
the installation script) for all the operations concerning image
processing. In addition, to add support for jpegs and pngs
images, and to enable the module to display mosaics on screen, please
install libjpeg
, libpng
and libtk
as well.
Install
To install osaic, you are enabled to grab it from both the mercurial repository and from the Python Package Index (PyPI). The former is preferred for bleeding-edge users, even tough the latter is not guaranteed to be very stable as well.
Mercurial
From sources:
cd /wherever/you/want hg clone https://bitbucket.org/iamFIREcracker/osaic python setup.py install
PyPI
From sources:
cd /path/to/workspace wget http://pypi.python.org/packages/source/o/osaic/osaic-2.0.0.tar.gz tar zxvf osaic-2.0.0.tar.gz cd osaic-2.0.0 python setup.py install
From the PyPI:
pip install osaic
Usage
osaic is a module that can be used both as a standalone application and as a standard python module.
Standalone application
A typical usage of the application is to display a mosaic composition created from a source image:
python -mosaic image.jpg
If you want to save the output to a file instead of showing it:
python -mosaic image.jpg -o mosaic-image.jpg
Finally, if you want to create a mosaic which is 4 times bigger than the original image, and with 100 tiles per side, just issue:
python -mosaic -z4 -t100 image.jpg
For everything else use the help message:
python -mosaic -h
Library
The module is a collection of objects and functions with different capabilities: functions for vectors, color transformations, image objects, image indexes and procedure wrappers.
Regarding operation with vectors, the module implement some basic functions not included in standard Python but useful while working with colors:
>>> dotproduct([1, 2, 3], [4, 5, 6]) 70 >>> difference([1, 2, 3], [1, 2, 3]) [0, 0, 0] >>> squaredistance([1, 2, 3], [0, 0, 0]) 30
It is possible to find also a couple of functions wrapping up common colors operations, like computation of the average color of an image and color quantization. The latter is particularly useful while trying to keep the CPU work load at low levels:
>>> average_color('almost-red.png') (240, 10, 20) >>> quantize_color((240, 10, 20), levels=2) (192, 64, 64)
As noted earlier, the module is built on top of the Python PIL
library. However, we chose not export such external objects, but
rather present to users some wrappers, namely ImageWrapper:
>>> img = Image.open('foo.png') >>> img.size (640, 480) >>> img.reratio(5 / 1) >>> img.crop((0, 0, 10, 10)) >>> img.size (10, 10) >>> img.show()
While creating mosaics, it comes in handy to have to possibility to
index a set of images and make it possible to search which of them is
the most similar, in terms of average color, to another one. The
ImageList
object is shipped with the module for this reason:
>>> img_list = ImageList(['1.png', '2.png', '3.png']) >>> img_list.search((255, 0, 0)) ImageTuple(filename='1.png', color=(255, 0, 0), image=None)
Finally, the module is shipped with a mosaicify
function which wraps
up all the operations needed to create mosaic, including source images
indexing, and search of neighbour images depending on the average
color:
>>> import osaic >>> osaic.mosaicify( ... target='foo.png', ... sources=['bar.png', 'asd.png', 'bazinga.png'], ... tiles=128, ... zoom=4, ... output='mosaic.png', ... )