the previous tutorials have not shown anybody else having this problem: compiling openCV and CUDA projects in vs2008 in windows 7 x64. but i have been stuck on it for over a week.
Zero problems building openCV samples and my own code and CUDA within their own projects. I cannot get them to build in a single project together no matter what i try to do in VS.
Here's a good guide, i'm sure it will help you: How to Build OpenCV 2.2 with GPU (CUDA) on Windows 7
self solve
this is NOT possible in windows, don't bother trying... i have since changed to ubuntu with no problems
It is possible when compiling OpenCV in x64 mode with checking "With Cuda" in CMAKE. Also you need to have the x64 Cuda Toolkit with Nvidia Performance Primitives and GPU Computing SDK.
Related
Building an OpenCV CUDA app on win10 with MSVC 2017 using the opencv[cuda] package installed by vcpkg. To check for usable devices, I call getCudaEnabledDeviceCount() and it returns -1, which OCV documents as meaning cuda support is enabled but the CUDA driver is incompatible.
Re-installing opencv[cuda] with vcpkg did not help.
Can you suggest a way to diagnose or fix?
Answer: The machine is an old gaming laptop whose most recent recommended nVidia display driver is 425.31. I had recently installed CUDA toolkit 10.2, whose runtime is actually incompatible with that driver. Rolling back to toolkit 10.1 resolved the problem.
I am trying to venture into accelerating my Fortran 2003 programs with OpenACC directives on my Ubuntu 18.04. workstation with Nvidia GeForce RTX 2070 card. To that end, I have installed Nvidia HPC-SDK version 20.7 which should comes with compilers I need (Fortran 2003 from Portland Group and Nvidia (both are version 20.7-0)) as well as profilers (nvprof and Nvidia Nsight Sytems (2020.3.1)).
After a few post-installation glitches, and owing mostly to the help from Robert Cravella (https://stackoverflow.com/users/1695960/robert-crovella) and Mat Colgrove (https://stackoverflow.com/users/3204484/mat-colgrove) I managed to get things going which made me very happy.
My workflow looks like this:
Compile my program:
pgfortran -acc -Minfo=accel -o my_program ./my_program.f90
I run it through profiler:
nsys profile ./my_program
And then import into nsight-sys with File -> Open and chose report1.qdrep
I believe this to be a proper workflow. However, while opening the report file, nsight-sys gives me the warning: "OpenACC injection initialization failed. Is the PGI runtime version greater than 15.7?" That's quite unfortunate, because I use OpenACC to accelerate my programs.
I am not quite sure what PGI runtime is, nor would I know how to check it or change it? I assume it is something with Portland Group (compiler), but I use the suite compilers shipped with Nvidia's HPC-SDK, so I wouldn't expect incompatibilities with the profiler tools shipped in the same package.
Is it an option, or possible at all, to update the PGI runtime thing?
And advice, please?
Cheers
Same answer as your previous post. There's a know issue with Nsight-Systems version 2020.3 which may sometimes cause an injection error when profiling OpenACC. I've been told that this was fixed in version 2020.4, hence the work around would be download and install 2020.4 or use a prior release.
https://developer.nvidia.com/nsight-systems
Version 2020.3 is what we shipped with the NVHPC 20.7 SDK. I'm not sure we have enough time to update to 2020.4 in our upcoming 20.9 release, but if not, we'll bundle it in a later release.
Thanks Mat,
In the meanwhile I managed to have everything running. I did as follows:
First installed CUDA toolkit, which came with the latest driver for my Nvidia RTX 2070 card, 11.1 to be precise. It needed a reboot, but that's OK. For CUDA toolkit to work, I had to set LD_LIBRARY_PATH to its libraries.
Then I installed Nvidia HPC-SDK, which I needed for Fortran 2003 compiler.
HPC-SDK is built for CUDA version 11.0 and comes with its own libraries and LD_LIBRARY_PATH should point to its libraries different from CUDA toolkit.
But, I kept the LD_LIBRARY_PATH to point to CUDA toolkit ones, and then compilers and profilers work in perfect harmony :-)
Thanks again, you and Robert helped me big time to get things running.
I have install Cuda 6.5 and opencv 2.4.9 with visual studio 2010, when I run gpu, I get error
Opencv Error: No GPU support(the library is compiled without PGU support) in the row_nogpu, file C:/builds/2_4_Packslave-win32-vc10-shared/opencv/modules/gpu/src/precomp.hpp line 135
I get this error, is any one can help what do I have to do?
Thanks
I believe, you have to actually build the libraries with CUDA support. I Imagine This Guide will be useful.
This can be caused because of following.
Use the flag WITH_CUDA=ON during cmake
You are trying to load the libraries which are compiled without GPU support, after you install opencv make sure you change the libraries path to that of GPU supported once.
In the post OpenCV 2.4.3rc and CUDA 4.2: "OpenCV Error: No GPU support" , it is said that C:\opencv\build\gpu\x86... libs must be added instead of C:\opencv\build\x86... ones. But there is no gpu folder for 2.4.4 realese. I added opencv_gpu244.lib lib file for release and opencv_gpu244d.lib for debug modes on vs 2010 conf. which are reside in C:\opencv\build\x64\vc10\lib. But i get opencv error ( no gpu support ): the library is compiled without cuda support. By the way i!'m using cuda toolkit 5.0.
The procedure described in the given answer, still applies to the current distribution of OpenCV. There is just 1 small difference. The pre-built distribution of OpenCV 2.4.4 does not contain GPU binaries. To add GPU support, you have to build the library yourself using CMake.
OpenCV 2.4.4 is optimized for Kepler architecture GPUs. In version 2.4.3, only the GPU binaries are approximately 1.4 GB. So you can guess, that adding the code for Compute capabilty 3.0 and 3.5 would make this even larger. So it is not feasible to ship these binaries, and that is why the gpu folder is not present in version 2.4.4 prebuilt distribution.
You should compile OpenCV libraries using CMake with CUDA support ( there is a checkbox ). Before releases include pre-compiled gpu files.
I've been asked to build a real-time face recognition application, and after some looking around I've decided to try EmguCV and OpenCV as the facial recognition library.
The issue I'm having at the moment is trying to get the SDK installed and working. I've followed the instructions found here to try and get it running, but I still can't run the samples. Whenever I try and run them, I get the error
The program can't start because nvcuda.dll is missing from your computer.
Try reinstalling the program to fix this problem.
I've tried most of the usual fixes, such as adding the bin folder to my environment path and copying the dll's into my system32 folder, but none of it seems to work.
EmguCV version 2.4.2.1777-windows-x64-gpu
Windows 8
AMD Radeon HD 6700 series graphics card.
I'm assuming this is an issue with the fact that I dont have an nVidia graphics card, but I'm not sure what I can do about it. For now, I'm going to try recompiling the source rather than using the downloaded .exe, and seeing if that helps.
Any suggestions?
Had the same problem, EmguCV 2.4.2 (no matter if x86 or x64) is compiled with GPU and you have to had nvidia GPU with CUDA support. So, if you want for eg. Fisherfaces from 2.4 in C# - wait for non-GPU release or buy/borrow CUDA card ;)
I happen to have the exact same problem as you. Everything is working fine on my computer (WinXP 32-bit) but not on Win7 64-bit computers.
This was because on my computer I already have OpenCV 2.4.2 installed and when I execute my program the path to the OpenCV dll points to the OpenCV folder and not to the dlls in the EmguCV folder. The original OpenCV dll don't have this dependency on NVidia's driver.
I used Dependency Walker to help me find out what was happening, as suggested here.
This link says that only the -gpu packages have gpu processing enabled but as you say the latest version (2.4.2) only a gpu package and no no-gpu package...
I read here that all I needed was to download the latest NVidia drivers to get the nvcuda.dll file but I downloaded many packages and never found this file: gpu computing sdk, cuda toolkit, display drivers, device drivers...
My workaround, instead of using an older version of EmguCV/OpenCV is to use the original dll from OpenCV 2.4.2.
I just used nvcuda.dll from dll-files.com.
It seems the issue is that the latest version on the site does not contain a non-GPU enhanced download, and that the GPU enhanced download requires an nVidia graphics card for CUDA integration.
I successfully downloaded and run the previous version which does not have GPU enhancements.
I had similar problem.
When I compile and run my application on computer with NVIDIA gpu it works fine.
Problem was when I moved app to another computer.
This second computer has no NVIDIA gpu and it threw 'Emgu.CV.CvInvoke' exception.
After many attempts I fortunately solved this problem.
As you mentioned before for now there is only gpu package for version 2.4.2.
I didn't notice this before.
For me solution was:
Copy files: 'cudart64_42_9.dll' and 'npp_42_9.dll' into Debug (application) folder
Copy file 'nvcuda.dll' into System32 folder.
After this steps aplication works on all computers even without NVIDIA gpu/ CUDA.
Other solution might be using opencv universal gpu version (for now is alpha 2.4.9) link: http://sourceforge.net/projects/emgucv/files/emgucv/2.4.9-alpha/
You can download source EmguCV from GIT and compile it, i have done this and works :
http://www.emgu.com/wiki/index.php/Download_And_Installation#Building_from_Git
It generates a non-GPU version of dlls
Regards.
here's also another copy of the dll's:
http://www.kimchiandchips.com/files/vvvv/nvcuda/
so 2 solutions:
Get NVidia CUDA DLL's from the above link. Ideally rename the 64 or 32bit version to nvcuda.dll based on your required platform. Put next to your opencv dll's
Upgrade to 2.4.9 which has universal GPU support
I also had some problems when doing my dissertation using EmguCV for face recognition.
Try to use the stablest version libemgucv-windows-x86-2.4.0.1717.exe
Try not to use the gpu download, this version has the least bugs and the 32-bit is better than the x64.
when compiling for the first time use visual studio 2012.
With this version you wont need to install all the above mentioned. You can see this example to know it really works : http://sourceforge.net/projects/emgufacerecog/