This module implements the Structural Similarity Image Metric (SSIM). Original code written by Antoine Vacavant from http://isit.u-clermont1.fr/~anvacava/code.html, with modifications by Christopher Godfrey and Jeff Terrace.
pip install pyssim
$ pyssim --help
usage: pyssim [-h] image1.png image path with* or image2.png
Compares an image with a list of images using the SSIM metric.
Example:
pyssim test-images/test1-1.png "test-images/*"
positional arguments:
image1.png
image path with* or image2.png
optional arguments:
-h, --help show this help message and exit
pyssim is known to work with Python 2.7 and 3.2 and we test these versions on Travis CI to make sure they keep working. 2.6 and 3.3 will probably work, but we omit them from testing due to complications with setting them up on Travis CI.
To run from a local git client:
PYTHONPATH="." python ssim
To run the lint checks:
pylint --rcfile=.pylintrc -r n ssim setup.py
To test:
$ PYTHONPATH="." python ssim test-images/test1-1.png "test-images/*"
test-images/test1-1.png - test-images/test1-1.png: 1
test-images/test1-1.png - test-images/test1-2.png: 0.9981071
test-images/test1-1.png - test-images/test2-1.png: 0.67301
test-images/test1-1.png - test-images/test2-2.png: 0.6488112
- [1] Z. Wang, A. C. Bovik, H. R. Sheikh and E. P. Simoncelli. Image quality assessment: From error visibility to structural similarity. IEEE Transactions on Image Processing, 13(4):600--612, 2004.
- [2] Z. Wang and A. C. Bovik. Mean squared error: Love it or leave it? - A new look at signal fidelity measures. IEEE Signal Processing Magazine, 26(1):98--117, 2009.