Now that you posted the code (along with timing markers), it's much clearer. Your timings are just for the computation, and don't include transfer time.
My "misleading" statement was not intended as an accusation :-), merely trying to help explain the gaussian blur result: if you included transfer time in one but not the other, that might explain it. But from your posted code, it's clear that wasn't the problem. --Tim On Monday, December 08, 2014 09:54:03 AM Max Suster wrote: > Its an exact comparison side-by-side of the same code, and actually already > tested by others in the OpenCV forum. > The Mat/UMat image is available for display with imshow -- the step "imshow( > "edges", gray);" in both cases -- which is how the test was set up. The > main point is the time it takes to complete the entire process and the fact > that cvtColor with OpenCL can generate an image for viewing much more > quickly. > > I never intended to be misleading, and I am sorry that you interpret it > this way. > > Max > > On Monday, December 8, 2014 6:22:39 PM UTC+1, Tim Holy wrote: > > I wonder if the bigger problem might be that your numbers for the > > grayscale > > conversion (which were very promising) might be misleading. Are you sure > > the > > calculation is "done" (and the results are available to the CPU) by the > > time > > it finishes? If we assume a best-case scenario of 6GB/s of data transfer > > to the > > GPU, then transferring 3MB to the GPU and 1MB back takes about 0.7ms. > > That's > > many times longer than what you reported for that calculation. Or did you > > not > > include transfer time in your results? > > > > --Tim > > > > On Monday, December 08, 2014 05:50:32 PM Simon Danisch wrote: > > > That's interesting, gaussian blur should definitely be faster on the > > > > gpu! > > > > > Maybe this thread helps? > > > http://answers.opencv.org/question/34127/opencl-in-opencv-300/ > > > It seems like things are a little complicated, as it isn't really clear > > > > if > > > > > the data is currently in VRAM or RAM... > > > > > > 2014-12-08 17:39 GMT+01:00 Max Suster <mxss...@gmail.com <javascript:>>: > > > > Thanks for the feedback. I realize that the copying needs to be > > > > skipped > > > > > > if possible . . . > > > > I have been playing a bit with the OpenCL UMat and it will need indeed > > > > some tweeking because UMat is not always advantageous. > > > > While there 10x gain with cvtColor and other functions such as > > > > GasussianBlur are actually a little slower. > > > > > > > > I will have closer look at this tonight. > > > > > > > > Max > > > > > > > > On Monday, December 8, 2014 4:15:28 PM UTC+1, Simon Danisch wrote: > > > >> If you're interested here are some more links: > > > >> https://software.intel.com/en-us/articles/opencl-and-opengl-> >> > > > > interoperability-tutorial > > > > > >> Valentine's and mine prototype for OpenGL OpenCL interoperability in > > > >> Julia: > > > >> https://github.com/vchuravy/qjulia_gpu > > > >> > > > >> 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-use > > > > > >>> rs/PjyfzxPt8Gk/SuwKtjTd9j4J> ,2 > > > >>> < > > > > https://groups.google.com/forum/#!searchin/julia-users/OpenCV/julia-use > > > > > >>> rs/81V5zSNJY3Q/DRUT0dR2qhQJ> ,3 > > > >>> < > > > > https://groups.google.com/forum/%23!searchin/julia-users/OpenCV/julia-u > > > > > >>> sers/iUPqo8drYek/pUeHECk91AQJ> ,4 > > > >>> < > > > > https://groups.google.com/forum/%23!searchin/julia-users/OpenCV/julia-u > > > > > >>> sers/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
