Hello Jürgen,
> maybe you want to do some normalization on the image as a
> preprocessing step before actually doing the comparison?
Yes, perhaps a two-stage algorithm is the way to go. However, a
complete shift of the image might be an indication of a problem, too,
so in the end I want an
Ok awesome
On Sat, 27 Jul 2024, 21:35 Werner LEMBERG, wrote:
>
> > Yes, I might be a moment due to friends visiting and such, but
> > definitely can.
>
> Great!
>
> > Could you get me going pointing me to a few image pairs and an
> > indication (like you did on SE) of the defect you see?
>
>
> Yes, I might be a moment due to friends visiting and such, but
> definitely can.
Great!
> Could you get me going pointing me to a few image pairs and an
> indication (like you did on SE) of the defect you see?
The example I gave on SE is *the* example – a small object of about
the size of a
Hi Werner,
hi all,
maybe you want to do some normalization on the image as a preprocessing
step before actually doing the comparison?
E.g. first crop the image, and then do the comparison. Of course, if
there is even a _large_ shift, you will no more detect it at all after
On Sat, Jul 27, 2024 at 8:18 PM Werner LEMBERG wrote:
> Can you provide a demo?
>
Yes, I might be a moment due to friends visiting and such, but definitely
can.
Could you get me going pointing me to a few image pairs and an indication
(like you did on SE) of the defect you see?
> Werner the case you have on SE seems to indicate you need a
> translation invariant test, I think.
Whatever you say :-) Great that there are people on this list who can
actually contribute to the topic.
> In your case you could compute min diff over all possible
> translations that would
At my previous work I had written the image comparison framework for our
regression test suite, it worked very well for us and it was in
python/numpy/scipy (which threads well internally).
Werner the case you have on SE seems to indicate you need a translation
invariant test, I think. Another
FWIW, I wrote a version of the comparison in Go that does the entire
comparison in-memory, without shelling out to any program. I did this
because it parallelized much better (ie. is faster), but it also means
you can easily test alternative algorithms.
See here:
I've posted a question on StackExchange, searching for a better
regtest comparison algorithm
https://computergraphics.stackexchange.com/questions/14143/search-for-special-image-difference-metric
Werner
