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Open Source Computer Vision Library
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222 lines
5.2 KiB
222 lines
5.2 KiB
/* This sample demonstrates working on one piece of data using two GPUs. |
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It splits input into two parts and processes them separately on different |
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GPUs. */ |
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// Disable some warnings which are caused with CUDA headers |
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#if defined(_MSC_VER) |
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#pragma warning(disable: 4201 4408 4100) |
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#endif |
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#include <iostream> |
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#include "cvconfig.h" |
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#include "opencv2/core/core.hpp" |
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#include "opencv2/highgui/highgui.hpp" |
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#include "opencv2/cudastereo.hpp" |
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#ifdef HAVE_TBB |
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# include "tbb/tbb_stddef.h" |
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# if TBB_VERSION_MAJOR*100 + TBB_VERSION_MINOR >= 202 |
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# include "tbb/tbb.h" |
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# include "tbb/task.h" |
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# undef min |
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# undef max |
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# else |
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# undef HAVE_TBB |
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# endif |
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#endif |
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#if !defined(HAVE_CUDA) || !defined(HAVE_TBB) || defined(__arm__) |
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int main() |
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{ |
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#if !defined(HAVE_CUDA) |
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std::cout << "CUDA support is required (CMake key 'WITH_CUDA' must be true).\n"; |
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#endif |
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#if !defined(HAVE_TBB) |
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std::cout << "TBB support is required (CMake key 'WITH_TBB' must be true).\n"; |
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#endif |
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#if defined(__arm__) |
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std::cout << "Unsupported for ARM CUDA library." << std::endl; |
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#endif |
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return 0; |
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} |
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#else |
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#include <cuda.h> |
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#include <cuda_runtime.h> |
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using namespace std; |
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using namespace cv; |
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using namespace cv::cuda; |
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struct Worker { void operator()(int device_id) const; }; |
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void destroyContexts(); |
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#define safeCall(expr) safeCall_(expr, #expr, __FILE__, __LINE__) |
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inline void safeCall_(int code, const char* expr, const char* file, int line) |
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{ |
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if (code != CUDA_SUCCESS) |
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{ |
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std::cout << "CUDA driver API error: code " << code << ", expr " << expr |
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<< ", file " << file << ", line " << line << endl; |
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destroyContexts(); |
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exit(-1); |
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} |
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} |
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// Each GPU is associated with its own context |
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CUcontext contexts[2]; |
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void inline contextOn(int id) |
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{ |
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safeCall(cuCtxPushCurrent(contexts[id])); |
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} |
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void inline contextOff() |
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{ |
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CUcontext prev_context; |
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safeCall(cuCtxPopCurrent(&prev_context)); |
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} |
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// GPUs data |
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GpuMat d_left[2]; |
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GpuMat d_right[2]; |
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Ptr<cuda::StereoBM> bm[2]; |
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GpuMat d_result[2]; |
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static void printHelp() |
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{ |
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std::cout << "Usage: driver_api_stereo_multi_gpu --left <left_image> --right <right_image>\n"; |
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} |
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int main(int argc, char** argv) |
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{ |
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if (argc < 5) |
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{ |
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printHelp(); |
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return -1; |
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} |
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int num_devices = getCudaEnabledDeviceCount(); |
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if (num_devices < 2) |
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{ |
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std::cout << "Two or more GPUs are required\n"; |
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return -1; |
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} |
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for (int i = 0; i < num_devices; ++i) |
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{ |
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cv::cuda::printShortCudaDeviceInfo(i); |
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DeviceInfo dev_info(i); |
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if (!dev_info.isCompatible()) |
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{ |
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std::cout << "GPU module isn't built for GPU #" << i << " (" |
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<< dev_info.name() << ", CC " << dev_info.majorVersion() |
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<< dev_info.minorVersion() << "\n"; |
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return -1; |
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} |
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} |
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// Load input data |
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Mat left, right; |
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for (int i = 1; i < argc; ++i) |
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{ |
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if (string(argv[i]) == "--left") |
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{ |
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left = imread(argv[++i], cv::IMREAD_GRAYSCALE); |
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CV_Assert(!left.empty()); |
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} |
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else if (string(argv[i]) == "--right") |
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{ |
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right = imread(argv[++i], cv::IMREAD_GRAYSCALE); |
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CV_Assert(!right.empty()); |
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} |
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else if (string(argv[i]) == "--help") |
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{ |
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printHelp(); |
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return -1; |
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} |
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} |
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// Init CUDA Driver API |
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safeCall(cuInit(0)); |
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// Create context for GPU #0 |
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CUdevice device; |
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safeCall(cuDeviceGet(&device, 0)); |
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safeCall(cuCtxCreate(&contexts[0], 0, device)); |
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contextOff(); |
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// Create context for GPU #1 |
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safeCall(cuDeviceGet(&device, 1)); |
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safeCall(cuCtxCreate(&contexts[1], 0, device)); |
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contextOff(); |
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// Split source images for processing on GPU #0 |
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contextOn(0); |
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d_left[0].upload(left.rowRange(0, left.rows / 2)); |
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d_right[0].upload(right.rowRange(0, right.rows / 2)); |
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bm[0] = cuda::createStereoBM(); |
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contextOff(); |
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// Split source images for processing on the GPU #1 |
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contextOn(1); |
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d_left[1].upload(left.rowRange(left.rows / 2, left.rows)); |
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d_right[1].upload(right.rowRange(right.rows / 2, right.rows)); |
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bm[1] = cuda::createStereoBM(); |
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contextOff(); |
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// Execute calculation in two threads using two GPUs |
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int devices[] = {0, 1}; |
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tbb::parallel_do(devices, devices + 2, Worker()); |
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// Release the first GPU resources |
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contextOn(0); |
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imshow("GPU #0 result", Mat(d_result[0])); |
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d_left[0].release(); |
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d_right[0].release(); |
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d_result[0].release(); |
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bm[0].release(); |
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contextOff(); |
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// Release the second GPU resources |
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contextOn(1); |
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imshow("GPU #1 result", Mat(d_result[1])); |
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d_left[1].release(); |
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d_right[1].release(); |
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d_result[1].release(); |
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bm[1].release(); |
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contextOff(); |
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waitKey(); |
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destroyContexts(); |
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return 0; |
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} |
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void Worker::operator()(int device_id) const |
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{ |
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contextOn(device_id); |
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bm[device_id]->compute(d_left[device_id], d_right[device_id], d_result[device_id]); |
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std::cout << "GPU #" << device_id << " (" << DeviceInfo().name() |
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<< "): finished\n"; |
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contextOff(); |
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} |
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void destroyContexts() |
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{ |
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safeCall(cuCtxDestroy(contexts[0])); |
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safeCall(cuCtxDestroy(contexts[1])); |
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} |
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#endif
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