Hi Stefan, Thank you for feedback I will look at it more closely and see what I can come up with. I did not know about the matplotlib comparison so I will see what they do. I did come across this the other day and wondered about down scaling. http://tech.jetsetter.com/2017/03/21/duplicate-image-detection/
Thanks, Mat Saunders On Mon, Apr 3, 2017 at 3:47 PM, Stefan van der Walt <stef...@berkeley.edu> wrote: > 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 > >
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