Hi release team, Shall we proceed with the opencv transition? The opencv 3.2.0 in unstable is too ancient. The automatically generated ben file looks good:
https://release.debian.org/transitions/html/auto-opencv.html I'm planning to remove the mipsel architecture since it suffers a lot from OOM issue during compilation, so please ignore the FTBFS on mipsel: https://buildd.debian.org/status/package.php?p=opencv&suite=experimental AFAIK opencv 3.x -> 4.x breaks nearly all the reverse dependencies, due to API changes or header path change. I have already filed FTBFS bugs against those correcponding packages when opencv 4.0.1 landed onto experimental. Now it's 4.1.1 and I think the result won't be different. On 2019-01-14 15:44, Mo Zhou wrote: > On Sun, Jan 13, 2019 at 08:06:57PM +0100, Emilio Pozuelo Monfort wrote: >> >> What is the status with the rdeps? I looked at two bugs and they worry me: > > I haven't had enough time to test rdeps for another round. But I guess > the situation would be similar to the first round. > >> #915544 suggests the OpenCV C API is broken, and ffmpeg solved it by >> disabling >> ffmpeg support altogether. >> >> #915709 seems to point to the same brokenness. > > Quoted from upstream: > https://github.com/opencv/opencv/issues/10963#issuecomment-369259044 > > | OpenCV 3.x doesn't not support C compilation mode officially. > > And if you look at upstream Pull Requests you will find that upstream > is gradually removing legacy C APIs. > > So, those rdeps broken due to the C API are questionable because they > are using non-officially supported (deprecated) part of opencv ... > > There are another failing pattern, which stems from changes in C++ class > method, and is easy to fix ... > > I'm currently putting out the fire on the julia package so I cannot > make a statistics. > >> The way it looks, I don't think we can go ahead with this at this stage. > > Both result are acceptable to me -- wether we can go ahead or not. > Pausing the transition helps my laziness. Moving forward, although > radical and breaks some questionable rdeps, brings some new features > such as the DNN module which supports not only pre-trained tensorflow > model.
