It's not in ImageView, it's just something I use privately. Given package load times, there's some tension between "having everything" and "making things easy to implement." So Images & ImageView largely focus on ingredients, and need users to put them together to make the soup. But I suppose we could have an ImageViewExtras package or something.
Anyway, I fully agree that having more options is great! --Tim On Saturday, December 06, 2014 05:19:41 AM Max Suster wrote: > Thanks a lot for pointing out the script. I will definitely have a close > look at the CUDA implementation. > > Regarding the live GUI trackbar with Images, I did not know that this was > implemented anywhere (i.e., did not see it in the documentation). > Personally, for my own needs, I also think there are advantages to having a > single unified package that allows both the basic image array handling, > GUI, and real-time tracking. . . and in the spirit of Christmas, the more > the merrier . . . > > Cheers, > Max > > On Saturday, December 6, 2014 2:07:41 PM UTC+1, Tim Holy wrote: > > I don't know if it will help at all in the context of OpenCV, but here's a > > test script that demonstrates farming out work to multiple GPUs: > > > > https://github.com/JuliaGPU/CUDArt.jl/blob/6409b57f7c80ed2459fd46c0e86ab8d > > e681fd9bc/test/test.jl#L185-L222 > > > > --Tim > > > > On Saturday, December 06, 2014 04:17:39 AM Max Suster wrote: > > > Glad to hear interest in this package :) > > > I have indeed started to work on getting the CUDA features into > > > > OpenCV.jl > > > > > (this was reorganized/relabelled from gpu to CUDA). > > > > > > My understanding is that OpenCV CUDA algorithms can use only a single > > > > GPU, > > > > > and to utilize multiple GPUs, its necessary to distribute the work > > > > between > > > > > several GPUs manually. I am experienced and not sure how to do this now > > > with the Julia interface, but if you do know, I would be happy to > > > collaborate on this. My main goal is to use OpenCV for real-time > > > > tracking > > > > > applications (e.g., principal skeleton tracking), and using GPU (with up > > > > to > > > > > 30x the speed for acquisition) would be invaluable. > > > > > > I have tested OpenCV with both boost C++ (multithreading) and > > > GPU-accelerated approaches, and it seems to me that the GPU approach is > > > most promising. One challenge however is that I found it very messy to > > > compile OpenCV 3.0 with CUDA on OSX 10.9.5 and it seems to me that a > > > > number > > > > > of people have reported bugs with the v3.0 build itself (at least on > > > > OSX). > > > > > The second issue (as I am sure you know) is that for the GPU features > > > > to > > > > > be worthwhile, you need a decent NVIDIA card and my GTX-Force 330M with > > > > a > > > > > Computing Capability (CC) of 1.2 is not exactly amazing Hopefully this > > > > will > > > > > change soon with a new Mac :) > > > > > > Since OpenCV is such a large API and it is used widely for so many > > > applications, it will nice to hear from those interested here what > > > > features > > > > > are worth expanding and which maybe less so. > > > > > > Max > > > > > > On Saturday, December 6, 2014 12:16:59 PM UTC+1, Simon Danisch wrote: > > > > Personal note: > > > > I needed to do a lot of interactive 2D and 3D visualizations with > > > > results > > > > > > from OpenCV and it was all just very cumbersome... > > > > This was actually one of the primers for me to start searching for a > > > > better language, in which you could do the 2D/3D visualizations, > > > > without > > > > > > performance penalty and with a high degree of interactivity. > > > > > > > > Am Samstag, 6. Dezember 2014 11:44:45 UTC+1 schrieb Max Suster: > > > >> Hi all, > > > >> > > > >> A few months ago I set out to learn Julia in an attempt to find an > > > >> alternative to MATLAB for developing computer vision applications. > > > >> Given the interest (1 > > > >> < > > > > https://groups.google.com/forum/#!searchin/julia-users/OpenCV/julia-user > > > > > >> s/PjyfzxPt8Gk/SuwKtjTd9j4J> ,2 > > > >> < > > > > https://groups.google.com/forum/#!searchin/julia-users/OpenCV/julia-user > > > > > >> s/81V5zSNJY3Q/DRUT0dR2qhQJ> ,3 > > > >> < > > > > https://groups.google.com/forum/%23!searchin/julia-users/OpenCV/julia-us > > > > > >> ers/iUPqo8drYek/pUeHECk91AQJ> ,4 > > > >> < > > > > https://groups.google.com/forum/%23!searchin/julia-users/OpenCV/julia-us > > > > > >> ers/6QunG66MfNs/C63pDfI-EMAJ> ) and wide application of OpenCV for > > > > fast > > > > > >> real-time computer vision applications, I set myself to put together > > > > a > > > > > >> simple interface for OpenCV in Julia. Coding in Julia and developing > > > >> the interface between C++ and Julia has been a lot of fun! > > > >> > > > >> OpenCV.jl aims to provide an interface for OpenCV > > > >> <http://opencv.org/> > > > >> > > > >> computer vision applications (C++) directly in Julia > > > >> <http://julia.readthedocs.org/en/latest/manual/>. It relies > > > > primarily on > > > > > >> Keno´s amazing Cxx.jl <https://github.com/Keno/Cxx.jl>, the Julia > > > > C++ > > > > > >> foreign function interface (FFI). You can find all the information > > > > on my > > > > > >> package at https://github.com/maxruby/OpenCV.jl. > > > >> > > > >> You can download and run the package as follows: > > > >> > > > >> Pkg.clone("git://github.com/maxruby/OpenCV.jl.git")using OpenCV > > > >> > > > >> > > > >> For MacOSX, OpenCV.jl comes with pre-compiled shared libraries, so it > > > > is > > > > > >> extremely easy to run. For Windows and Linux, you will need to first > > > >> compile the OpenCV libraries, but this is well documented and links > > > > to > > > > > >> the > > > >> instructions for doing so are included in the README.md file. > > > >> > > > >> The package currently supports most of OpenCV´s C++ API; however, at > > > > this > > > > > >> point I have created custom wrappings for core, imgproc, videoio and > > > >> highgui modules so that these are easy to use for anyone. > > > >> > > > >> The package also demonstrates/contains > > > >> > > > >> - preliminary interface with the Qt GUI framework (see imread() > > > > and > > > > > >> imwrite() functions) > > > >> - thin-wrappers for C++ objects such as std::vectors, std::strings > > > >> - conversion from Julia arrays to C++ std::vector > > > >> - conversion of Julia images (Images.jl) to Mat (OpenCV) - though > > > >> this has much room for improvement (i.e., color handling) > > > >> > > > >> Please let me know if there are any features you would like to see > > > > added > > > > > >> and I will try my best to integrate them. In the meantime, I will > > > >> continue > > > >> to integrate more advanced algorithms for computer vision and > > > > eventually > > > > > >> extend the documentation as needed. > > > >> > > > >> Cheers, > > > >> Max
