问题描述
众所周知,OpenCV 3.0支持新课程如果可以的话,它提供透明API(TAPI)以自动使用OpenCL:
As known, OpenCV 3.0 supports new class cv::Umat
which provides Transparent API (TAPI) to use OpenCL automaticaly if it can: http://code.opencv.org/projects/opencv/wiki/Opencv3#tapi
cv :: Umat
和TAPI有两个简介:
There are two indtroductions to the cv::Umat
and TAPI:
- 英特尔:
- AMD:
- Intel: https://software.intel.com/en-us/articles/opencv-30-architecture-guide-for-intel-inde-opencv
- AMD: http://developer.amd.com/community/blog/2014/10/15/opencv-3-0-transparent-api-opencl-acceleration/
但是如果我有:
- Intel CPU Core i5(Haswell)4xCores(OpenCL )
- 英特尔集成高清显卡
- 第一款nVidia GPU GeForce GTX 970(Maxwell)
和CUDA - 第二届nVidia GPU GeForce GTX 970 ......
- Intel CPU Core i5 (Haswell) 4xCores (OpenCL Intel CPUs with SSE 4.1, SSE 4.2 or AVX support)
- Intel Integrated HD Graphics which supports OpenCL 1.2
- 1st nVidia GPU GeForce GTX 970 (Maxwell) which supports OpenCL 1.2and CUDA
- 2nd nVidia GPU GeForce GTX 970 ...
如果我在OpenCV中启用OpenCL,那么我该怎么办?在第一个nVidia GPU或第二个nVidia GPU上,在8个CPU核心,集成高清显卡上更改设备?
If I turn on OpenCL in OpenCV, then how can I change the device on wich OpenCL-code will be executed: on 8 Cores of CPU, on Integrated HD Graphics, on 1st nVidia GPU or 2nd nVidia GPU?
我该怎么办?选择这4个设备中的每一个,使用OpenCL进行并行执行算法 cv :: Umat
?
How can I select one of each of these 4 devices to use OpenCL for parallel execution algorithms with cv::Umat
?
例如,我如何在4xCore的CPU Core-i5上使用OpenCL加速 cv :: Umat
?
For example, how can I use OpenCL acceleration on 4xCores of CPU Core-i5 with cv::Umat
?
推荐答案
我使用类似的东西检查用于OpenCL支持的版本和硬件。
I use something like this to check versions and hardware being used for OpenCL support.
ocl::setUseOpenCL(true);
if (!ocl::haveOpenCL())
{
cout << "OpenCL is not available..." << endl;
//return;
}
cv::ocl::Context context;
if (!context.create(cv::ocl::Device::TYPE_GPU))
{
cout << "Failed creating the context..." << endl;
//return;
}
cout << context.ndevices() << " GPU devices are detected." << endl; //This bit provides an overview of the OpenCL devices you have in your computer
for (int i = 0; i < context.ndevices(); i++)
{
cv::ocl::Device device = context.device(i);
cout << "name: " << device.name() << endl;
cout << "available: " << device.available() << endl;
cout << "imageSupport: " << device.imageSupport() << endl;
cout << "OpenCL_C_Version: " << device.OpenCL_C_Version() << endl;
cout << endl;
}
然后您可以使用此设置首选硬件
Then you can set your preferred hardware to use, using this
cv::ocl::Device(context.device(1));
希望这可以帮到你。
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