I'm trying to figure out if http://www.solid-run.com/products/hummingboard/ will be able to run OpenCV with OpenCL accelerations. Attempting to do this on the Raspberry Pi was fruitless.
The Ocl library for OpenCl acceleration for OpenCV requires OpenCL with FULL PROFILE. Vivate GPU in Freescale iMX6q only supports Embedded Profile(EP).
You cannot use OpenCL acceleration in OpenCV in this case.
Related
I am trying to estimate pose of a Aruco Marker using opencv library.
But the performance of the above Library is a bit slow since it runs on CPU.Is there a way so that I can run the above Library on GPU?
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I tried researching in OpenCV's documentation, it has some cuda enabled functions but for aruco functions it is not available
long time tormented by this question, I ask your advice in what direction to move. Objective - to develop universal application with yolo on windows, which can use computing power of AMD/Nvidia/Intel GPU, AMD/Intel CPU (one of the devices will be used). As far as I know, the OpenCV DNN module is leading in CPU computation; a DNN + Cuda bundle is planned for Nvidia graphics cards and a DNN + OpenCL bundle is planned for Intel GPUs. But testing AMD GPU rx580 with DNN + OpenCL, I ran into the following problem: https://github.com/opencv/opencv/issues/17656. Does this module not support AMD GPU computing at all? If so, could you please let me know what platform this is possible on and, preferably, as efficiently as possible. A possible solution might be Tencent's ncnn, but I'm not sure of the performance on the desktop. By output I mean the coordinates of detected objects and their names (in opencv dnn module I got them with cv::dnn::Net::forward()). Also, correct me if I'm wrong somewhere. Any feedback would be appreciated.
I tried the OpenCV DNN + OpenCL module and expected high performance, but this combination does not work.
I believe OpenCV doesn't support AMD for GPU optimization. If you're interested in running DL models on non-Nvidia GPUs, I suggest reading PlaidML, YOLO-OpenCL, DeepCL
Do you know what is different between Mali OpenCL SDK and OpenCL in OpenCV library? I see that in Mali OpenCL SDK has some detail sample code about how to create Memory buffer, get input data, setup argument... But in OpenCL inside OpenCV library, I only need change from Mat to UMAT to have OpenCL code run on GPU? and it seems OpenCL code hidden under API? How can I change OpenCL code by my application?
These are not the same things.
Your question is like asking what the difference between a for-Loop and a random method doForLoopthat contains a for-Loop is.
OpenCV can use OpenCL to accelerate certain tasks.
The Mali OpenCL SDK is a SDK to program OpenCL directly. You can use this SDK to develop programs that should run on the Mail mobile graphics GPU.
As said here, OpenCV uses IPP which uses GPU:
It turned out that OpenCV was using IPP and IPP itself can use GPU
nowadays.
just in case someone else googles for "opencv gpu slower" and didnt
know about the IPP GPU support ;)
Also, I found this:
Optimizing an Augmented Reality Pipeline using Intel® IPP Asynchronous
Using Intel® GPUs to Optimize the Performance and Power Consumption of
Total Immersion's D'Fusion* Augmented Reality Pipeline
And there is no one keyword: OpenCL, OpenACC, CUDA, nVidia, ...
There is only one relative to GPU keyword: OpenGL
Does this mean that the Intel IPP supports only Intel GPU? Or Intel IPP support any GPU (nVidia GeForce, AMD Radeon) which supports OpenGL?
Intel IPP doesn't support GPUs. It was kind of "preview" product - Intel 8.0 Preview, which was discontinued.
Intel integrated graphics is supported only by OpenCL. Intel IPP is focused on CPUs only.
Regards!
I was the one of your linked posting...
I didnt try to find out IPP capabilities because it wasnt my project but one of a colleague...
googling talks about "IPP Asynchronous" library and config stuff like
HPP_ACCEL_TYPE_GPU_VIA_DX9 looks like there are options to use OpenCL and DX9 but no warranties from my side that they are supported or that this list is complete...
I am working on raspberry pi in image processing project using opencv
But i found that it was inefficient with raspberry pi as it works on CPU and don't use powerful GPU and i must switch to openCL
Are there any method to convert from openCV to openCL
Or how can i able GPU for opencv ?
Or how i can i use opencv with acceptable fast response processing on raspberry pi ?
OpenCL modules are included in OpenCV. http://docs.opencv.org/modules/ocl/doc/introduction.html
use it.