cloned openCV and modified the build script to include 64bit arm according to suggested answer
But getting many errors and it is not building.
Any work around for this?
I can post the log if needed.
Related
I have been pulling my hair out trying to get mingw and opencv working on Windows for Visual Studio Code for the past three days.
I am using mingw 8.1, and opencv 4.5.2(tried 4.1.1)
The online guides I found apparently don't work, and I even went as far as to build openCV myself to see if it would work, but it did not.
Every version I try throws a procedure entry point could not be located in dynamic link library imgcodecs452.dll error, and I could not find anything online.
Has anyone ran into this issue?
Note that I'm running a very old CPU, pre-AVX x5690, but I did compile for without AVX yet it still failed.
I'm trying to get the Dart SDK on a Pi Zero W.
When I download the SDK archive, extract it, and put it in the /usr/lib folder manually, I get segmentation faults when I try to run any of the command line tools. I reflashed the memory card (32GB, so plenty large) from scratch from an x64 machine and pre-loaded the SDK as well to help ensure that there wasn't any funky Pi file corruption and got the same result.
Though I was sure it wouldn't work, I loaded the ARM7 version of the SDK, and got executable file format incompatibility errors that were not surprising.
I downloaded the .deb package, and got a warning that the file was not meant for my Pi and that I might break things, so I didn't try to install it.
I used the apt-get instructions from the Dart website and that failed with the error "E: Unable to locate package dart" which seems to indicate that I had the incorrect name for the package (note: I copied and pasted it directly from the Dart website). I tried to look through the repository contents, and assuming that I looked at the correct file, there were not any Dart entries in it, so the error is not surprising.
My Linux competence is suspect, so I could use any ideas. I'd prefer not to build the SDK from scratch as, in my experience, open source build instructions almost always assume that the user needs to know/do something that is not explicitly listed in the instructions, so that tends to be a 2-hour effort that ultimately fails (pretty sure I'm not the only one who's had that experience).
Thoughts, anyone?
That is not going to work. Your problem is that "Pi Zero W" is a "1GHz single-core ARMv6 CPU (BCM2835)" CPU which means it can only execute programs for the ARMv6 architecture or lower.
Dart does have a minimum requirement for ARMv7 since they removed support for ARMv6 early this year: https://github.com/dart-lang/sdk/issues/42069
The support was never that great for ARMv6 (I did have an old Raspberry Pi) and programs was running really slow with missing support for FFI. So my recommendation is to get a board which supports ARMv7 or ARMv8 (ARM64) which works really great.
Having an issue with trying to build any opencv version with code::blocks.
I've have built opencv successfully before and have no idea what the issue is.
I've tried following many different tutorials on building opencv using mingw 4.9.2 and CMake. I have also tried using mingw32 and mingw64.
But I continue to receive the errors shown in the image above.
My question is; What is the issue? How can I fix this? And, lastly, what am I doing wrong?
Found that the version of OpenCV I was using had issues with MinGW. Tested a whole bunch of OpenCV versions (3.3, 3.2, 3.1, 2.4.13, 2.4.13.3).
I found that OpenCV version 2.4.9 with the latest version of CMake and MinGW worked.
Thought I'd leave this here to help anyone else having issues with creating OpenCV to work with MinGW/Code::Blocks
I'm trying (with no success) to cross-compile OpenCV on a embedded board.
I followed this: http://docs.opencv.org/doc/tutorials/introduction/crosscompilation/arm_crosscompile_with_cmake.html.
To summarize I installed the cross compilation tools for ARM, the I ran the cmake (providing the proper toolchain file), the make and the make install commands.
I next copied the lib/ include and bin/ directories with the opencv installation in the embedded board.
However, when I try to compile a simple hello world with opencv I get undefined reference to __gnu_thumb1_case_uqi and other similar symbols.
Does anybody faced this problem and know how to solve it?
Alternative approach
Just take some embedded distro like Buildroot, OpenEmbedded or Debian. They all provide OpenCV.
As I'm mostly experienced in Buildroot, I'd like to point to the newly introduced feature to keep your project separate from BR: http://nightly.buildroot.org/manual.html#outside-br-custom. This will give you a main idea on how to compile your software against BR's OpenCV.
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/