diffimg

Get the % difference in images using PIL's histogram + generate a diff image. Images should have the same color channels (for example, RGB vs RGBA). If the image dimensions differ, the 2nd image will be resized to match the first before calculating the diff.

Installation

Now available from PyPi: pip install diffimg

Usage

>>> from diffimg import diff
>>> diff('mario-circle-cs.png', 'mario-circle-node.png')
0.007319618135968298

The very simple diff function returns a raw ratio instead of a % by default.

diff(im1_file, 
     im2_file, 
     delete_diff_file=False, 
     diff_img_file=DIFF_IMG_FILE
     ignore_alpha=False)

im1_file, im2_file: filenames of images to diff.

delete_diff_file: a file showing the differing areas of the two images is generated in order to measure the diff ratio with the same dimensions as the first image. Setting this to True removes it after calculating the ratio.

diff_img_file: filename for the diff image file. Defaults to diff_img.png (regardless of inputed file's types).

ignore_alpha: ignore the alpha channel for the ratio and if applicable, sets the alpha of the diff image to fully opaque.

As command line tool

python -m diffimg image1 image2 [-r/--ratio] [-d/--delete] [-f/--filename DIFF_IMG_FILE]

--ratio outputs a number between 0 and 1 instead of the default Images differ by X%.

--delete removes the diff file after retrieving ratio/percentage.

--filename specifies a filename to save the diff image under. Must use a valid extension.

--ignore-alpha ignore the alpha channel.

Tests

$ ./test.py
......
----------------------------------------------------------------------
Ran 6 tests in 0.320s

OK

Formula

The difference is defined by the average % difference between each of the channels (R,G,B,A?) at each pair of pixels A_xy, B_xy at the same coordinates in each of the two images (why they need to be the same size), averaged over all pairs of pixels.

For example, compare two 1x1 images A and B (a trivial example, >1 pixels would have another step to find the average of all pixels):

A_1,1 = RGB(255,0,0) (pure red)

B_1,1 = RGB(100,0,0) (dark red)

((255-100)/255 + (0/0)/255 + (0/0)/255))/3 = (155/255)/3 = 0.202614379

So these two 1x1 images differ by 20.2614379% according to this formula.

Sample image 1

Sample image 2

Resulting diff image

Difference percentage output

Images differ by 0.731961813597%