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2019-06-21 03:48:56 -0600
| commented answer | How do I load an OpenCV generated yaml file in python? Came here via Google--this is nowadays the correct answer and should be accepted!
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2019-06-21 03:47:08 -0600
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2019-02-15 13:33:38 -0600
| commented question | Error when compiling OpenCV 4.0 with CUDA 8 well, compiling 3.4.0 worked
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2019-02-15 12:26:46 -0600
| asked a question | Error when compiling OpenCV 4.0 with CUDA 8 Error when compiling OpenCV 4.0 with CUDA 8
Hi, I'm using an older Q5000 GPU in my machine that needs CUDA 8. It was tri |
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2019-02-15 12:26:45 -0600
| asked a question | Error when compiling OpenCV 4.0 with CUDA 8 Error when compiling OpenCV 4.0 with CUDA 8
Hi, I'm using an older Q5000 GPU in my machine that needs CUDA 8. It was tri |
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2019-02-15 12:26:45 -0600
| asked a question | Error when compiling OpenCV 4.0 with CUDA 8 Error when compiling OpenCV 4.0 with CUDA 8
Hi, I'm using an older Q5000 GPU in my machine that needs CUDA 8. It was tri |
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2019-02-15 12:26:44 -0600
| asked a question | Error when compiling OpenCV 4.0 with CUDA 8 Error when compiling OpenCV 4.0 with CUDA 8
Hi, I'm using an older Q5000 GPU in my machine that needs CUDA 8. It was tri |
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2019-02-15 12:26:37 -0600
| asked a question | Error when compiling OpenCV 4.0 with CUDA 8 Error when compiling OpenCV 4.0 with CUDA 8
Hi, I'm using an older Q5000 GPU in my machine that needs CUDA 8. It was tri |
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2018-10-11 13:53:54 -0600
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2018-09-27 16:31:19 -0600
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2018-09-27 13:14:20 -0600
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2018-09-27 13:14:20 -0600
| edited answer | Can cv::dft() be sped up with the right compiler flags? It looks like WITH_IPP=ON did the trick.
As a side note, padding can make a huge difference as well, as explained here |
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2018-09-27 12:21:04 -0600
| marked best answer | Can cv::dft() be sped up with the right compiler flags? For some time I have been using cv::dft() on a large image and it always took about 4-5 seconds. I noticed it now takes about 30 seconds for the same image and I wonder why. I recently recompiled OpenCV, without having saved the original compiler flags, so maybe I am missing a flag now that speeds up the dft function? This is the current build configuration: General configuration for OpenCV 3.2.0 =====================================
Version control: unknown
Extra modules:
Location (extra): /home/uname/opencv_contrib-3.2.0/modules
Version control (extra): unknown
Platform:
Timestamp: 2018-09-17T15:22:43Z
Host: Linux 4.4.0-135-generic x86_64
CMake: 3.5.1
CMake generator: Unix Makefiles
CMake build tool: /usr/bin/make
Configuration: RELEASE
C/C++:
Built as dynamic libs?: YES
C++ Compiler: /usr/bin/c++ (ver 5.4.0)
C++ flags (Release): -fsigned-char -W -Wall -Werror=return-type -Werror=non-virtual-dtor -Werror=address -Werror=sequence-point -Wformat -Werror=format-security -Wmissing-declarations -Wundef -Winit-self -Wpointer-arith -Wshadow -Wsign-promo -Wno-narrowing -Wno-delete-non-virtual-dtor -Wno-comment -fdiagnostics-show-option -Wno-long-long -pthread -fomit-frame-pointer -ffast-math -msse -msse2 -mno-avx -msse3 -mno-ssse3 -mno-sse4.1 -mno-sse4.2 -ffunction-sections -fvisibility=hidden -fvisibility-inlines-hidden -O3 -DNDEBUG -DNDEBUG
C++ flags (Debug): -fsigned-char -W -Wall -Werror=return-type -Werror=non-virtual-dtor -Werror=address -Werror=sequence-point -Wformat -Werror=format-security -Wmissing-declarations -Wundef -Winit-self -Wpointer-arith -Wshadow -Wsign-promo -Wno-narrowing -Wno-delete-non-virtual-dtor -Wno-comment -fdiagnostics-show-option -Wno-long-long -pthread -fomit-frame-pointer -ffast-math -msse -msse2 -mno-avx -msse3 -mno-ssse3 -mno-sse4.1 -mno-sse4.2 -ffunction-sections -fvisibility=hidden -fvisibility-inlines-hidden -g -O0 -DDEBUG -D_DEBUG
C Compiler: /usr/bin/cc
C flags (Release): -fsigned-char -W -Wall -Werror=return-type -Werror=non-virtual-dtor -Werror=address -Werror=sequence-point -Wformat -Werror=format-security -Wmissing-declarations -Wmissing-prototypes -Wstrict-prototypes -Wundef -Winit-self -Wpointer-arith -Wshadow -Wno-narrowing -Wno-comment -fdiagnostics-show-option -Wno-long-long -pthread -fomit-frame-pointer -ffast-math -msse -msse2 -mno-avx -msse3 -mno-ssse3 -mno-sse4.1 -mno-sse4.2 -ffunction-sections -fvisibility=hidden -O3 -DNDEBUG -DNDEBUG
C flags (Debug): -fsigned-char -W -Wall -Werror=return-type -Werror=non-virtual-dtor -Werror=address -Werror=sequence-point -Wformat -Werror=format-security -Wmissing-declarations -Wmissing-prototypes -Wstrict-prototypes -Wundef -Winit-self -Wpointer-arith -Wshadow -Wno-narrowing -Wno-comment -fdiagnostics-show-option -Wno-long-long -pthread -fomit-frame-pointer -ffast-math -msse -msse2 -mno-avx -msse3 -mno-ssse3 -mno-sse4.1 -mno-sse4.2 -ffunction-sections -fvisibility=hidden -g -O0 -DDEBUG -D_DEBUG
Linker flags (Release):
Linker flags (Debug):
ccache: NO
Precompiled headers: YES
Extra dependencies: /home/uname/anaconda3/lib/libpng.so /home/uname/anaconda3/lib/libtiff.so /usr/lib/x86_64-linux-gnu/libjasper.so /home/uname/anaconda3/lib/libjpeg.so gtk-3 gdk-3 pangocairo-1.0 pango-1.0 atk-1.0 cairo-gobject cairo gdk_pixbuf-2.0 gio-2.0 gobject-2.0 glib-2.0 gthread-2.0 avcodec-ffmpeg avformat-ffmpeg avutil-ffmpeg swscale-ffmpeg /home/uname/anaconda3/lib/libhdf5_hl.so /home/uname/anaconda3/lib/libhdf5.so /usr/lib/x86_64-linux-gnu/librt.so /usr/lib/x86_64-linux-gnu/libpthread.so /home/uname/anaconda3/lib/libz.so /usr/lib/x86_64-linux-gnu/libdl.so /usr/lib/x86_64-linux-gnu/libm.so dl m pthread rt cudart nppc nppial nppicc nppicom nppidei nppif nppig nppim nppist nppisu nppitc npps cublas cufft -L/usr/local/cuda/lib64
3rdparty dependencies: libwebp IlmImf libprotobuf
OpenCV modules:
To be built: cudev core cudaarithm flann hdf imgproc ml reg surface_matching video cudabgsegm cudafilters cudaimgproc cudawarping dnn freetype fuzzy imgcodecs photo shape videoio cudacodec highgui objdetect plot ts xobjdetect xphoto bgsegm bioinspired dpm face features2d line_descriptor saliency text calib3d ccalib cudafeatures2d cudalegacy cudaobjdetect ...
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2018-09-27 12:19:43 -0600
| received badge | ● Self-Learner
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2018-09-27 12:17:07 -0600
| answered a question | Can cv::dft() be sped up with the right compiler flags? It looks like WITH_IPP=ON did the trick.
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2018-09-27 03:26:37 -0600
| commented question | Simple GPU access tutorials with OpenCV Possibly something went wrong when you compiled OpenCV with CUDA. What's the output of getBuildInformation() in your Ope |
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2018-09-27 03:26:06 -0600
| answered a question | Simple GPU access tutorials with OpenCV Possibly something went wrong when you compiled OpenCV with CUDA. What's the output of getBuildInformation() in your Ope |
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2018-09-24 06:59:19 -0600
| commented question | Can cv::dft() be sped up with the right compiler flags? I guess (would take some more time and risk than recompiling my current version), but I had been using OpenCV 3.2.0 all |
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2018-09-24 06:50:34 -0600
| commented question | Simple GPU access tutorials with OpenCV The code looks fine. Can you see where the error comes from? What's the output of getCudaEnabledDeviceCount()?
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2018-09-24 06:50:33 -0600
| asked a question | Can cv::dft() be sped up with the right compiler flags? Can cv::dft() be sped up with the right compiler flags?
For some time I have been using cv::dft() on a large image and i |
