Hi Mat
You'll probably have to come up with some heuristics for the kinds of errors you wish to identify. As a very crude first attempt, you may try to downscale the images before comparison to reduce sensitivity. Perhaps also take a look at what Matplotlib does in their test suite to compare different renderings of plots (I know they do image comparison too). Best regards Stéfan On Mon, Apr 3, 2017, at 12:00, mat saunders wrote: > I sent this to scikit-learn by accident, so forwarding to image. > > Hi, > > I am using SSIM to compare 2 video streams\sets of images and I find > it to be almost too accurate. I would like some fudge factor like > other image comparison tools have. I used to do it in an automated > test suite but due to file sizes and amounts I turned to scikit. > > I do quality assurance on a render engine and we just want to make > sure the images are meaningfully identical build to build. Currently > with SSIM I am seeing things as small as 4 pixels across a 1920x1080 > image different. I personally would like to ignore those 4 pixels but > still catch meaningful items. Say if 8 pixels near each other were > off keep those but if they are 8 pixels randomly through the image > ignore them. > > Does this sound like something logical, say using an adjacency of > pixels with a tolerance value for color and number of pixels as > arguments? > > See attached image for example of how little is different in the > entire image. It is a GIF zoomed in to the exact spot of 3 different > pixels so hopefully it works. I also attached the comparison image to > show how little changed. > > Another issue that we had is we had to turn off AA to get rid of > noise, it is amazing how accurate this library is!! > > Regards, > Mathew Saunders > _________________________________________________ > scikit-image mailing list > scikit-image@python.org > https://mail.python.org/mailman/listinfo/scikit-image > Email had 2 attachments: > * 3dots-again.gif 138k (image/gif) > * Pasted image at 2017_03_28 12_51 PM.png 560k (image/png)
_______________________________________________ scikit-image mailing list scikit-image@python.org https://mail.python.org/mailman/listinfo/scikit-image
