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Commit 0093eb47 authored by Alexander Alekhin's avatar Alexander Alekhin
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cuda: drop samples for low-level CUDA API 

Also these samples require TBB, so they are not tested during default OpenCV builds
parent f93c1b94
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samples/gpu/CMakeLists.txt
View file @ 0093eb47
......@@ -50,9 +50,6 @@ endif()
foreach(sample_filename ${all_samples})
ocv_define_sample(tgt ${sample_filename} gpu)
ocv_target_link_libraries(${tgt} ${OPENCV_LINKER_LIBS} ${OPENCV_CUDA_SAMPLES_REQUIRED_DEPS})
if(HAVE_CUDA AND NOT ANDROID)
ocv_target_link_libraries(${tgt} ${CUDA_CUDA_LIBRARY})
endif()
if(HAVE_opencv_xfeatures2d)
ocv_target_link_libraries(${tgt} opencv_xfeatures2d)
endif()
......
samples/gpu/driver_api_multi.cpp deleted 100644 → 0
View file @ f93c1b94
/* This sample demonstrates the way you can perform independent tasks
on the different GPUs */
// Disable some warnings which are caused with CUDA headers
#if defined(_MSC_VER)
#pragma warning(disable: 4201 4408 4100)
#endif
#include <iostream>
#include "opencv2/cvconfig.h"
#include "opencv2/core.hpp"
#include "opencv2/cudaarithm.hpp"
#ifdef HAVE_TBB
# include "tbb/tbb.h"
# include "tbb/task.h"
# undef min
# undef max
#endif
#if !defined(HAVE_CUDA) || !defined(HAVE_TBB) || defined(__arm__)
int main()
{
#if !defined(HAVE_CUDA)
std::cout << "CUDA support is required (CMake key 'WITH_CUDA' must be true).\n";
#endif
#if !defined(HAVE_TBB)
std::cout << "TBB support is required (CMake key 'WITH_TBB' must be true).\n";
#endif
#if defined(__arm__)
std::cout << "Unsupported for ARM CUDA library." << std::endl;
#endif
return 0;
}
#else
#include <cuda.h>
#include <cuda_runtime.h>
using namespace std;
using namespace cv;
using namespace cv::cuda;
struct Worker { void operator()(int device_id) const; };
void destroyContexts();
#define safeCall(expr) safeCall_(expr, #expr, __FILE__, __LINE__)
inline void safeCall_(int code, const char* expr, const char* file, int line)
{
if (code != CUDA_SUCCESS)
{
std::cout << "CUDA driver API error: code " << code << ", expr " << expr
<< ", file " << file << ", line " << line << endl;
destroyContexts();
exit(-1);
}
}
// Each GPU is associated with its own context
CUcontext contexts[2];
int main()
{
int num_devices = getCudaEnabledDeviceCount();
if (num_devices < 2)
{
std::cout << "Two or more GPUs are required\n";
return -1;
}
for (int i = 0; i < num_devices; ++i)
{
cv::cuda::printShortCudaDeviceInfo(i);
DeviceInfo dev_info(i);
if (!dev_info.isCompatible())
{
std::cout << "CUDA module isn't built for GPU #" << i << " ("
<< dev_info.name() << ", CC " << dev_info.majorVersion()
<< dev_info.minorVersion() << "\n";
return -1;
}
}
// Init CUDA Driver API
safeCall(cuInit(0));
// Create context for GPU #0
CUdevice device;
safeCall(cuDeviceGet(&device, 0));
safeCall(cuCtxCreate(&contexts[0], 0, device));
CUcontext prev_context;
safeCall(cuCtxPopCurrent(&prev_context));
// Create context for GPU #1
safeCall(cuDeviceGet(&device, 1));
safeCall(cuCtxCreate(&contexts[1], 0, device));
safeCall(cuCtxPopCurrent(&prev_context));
// Execute calculation in two threads using two GPUs
int devices[] = {0, 1};
tbb::parallel_do(devices, devices + 2, Worker());
destroyContexts();
return 0;
}
void Worker::operator()(int device_id) const
{
// Set the proper context
safeCall(cuCtxPushCurrent(contexts[device_id]));
Mat src(1000, 1000, CV_32F);
Mat dst;
RNG rng(0);
rng.fill(src, RNG::UNIFORM, 0, 1);
// CPU works
cv::transpose(src, dst);
// GPU works
GpuMat d_src(src);
GpuMat d_dst;
cuda::transpose(d_src, d_dst);
// Check results
bool passed = cv::norm(dst - Mat(d_dst), NORM_INF) < 1e-3;
std::cout << "GPU #" << device_id << " (" << DeviceInfo().name() << "): "
<< (passed ? "passed" : "FAILED") << endl;
// Deallocate data here, otherwise deallocation will be performed
// after context is extracted from the stack
d_src.release();
d_dst.release();
CUcontext prev_context;
safeCall(cuCtxPopCurrent(&prev_context));
}
void destroyContexts()
{
safeCall(cuCtxDestroy(contexts[0]));
safeCall(cuCtxDestroy(contexts[1]));
}
#endif
samples/gpu/driver_api_stereo_multi.cpp deleted 100644 → 0
View file @ f93c1b94
/* This sample demonstrates working on one piece of data using two GPUs.
It splits input into two parts and processes them separately on different
GPUs. */
// Disable some warnings which are caused with CUDA headers
#if defined(_MSC_VER)
#pragma warning(disable: 4201 4408 4100)
#endif
#include <iostream>
#include "opencv2/cvconfig.h"
#include "opencv2/core.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/cudastereo.hpp"
#ifdef HAVE_TBB
# include "tbb/tbb.h"
# include "tbb/task.h"
# undef min
# undef max
#endif
#if !defined(HAVE_CUDA) || !defined(HAVE_TBB) || defined(__arm__)
int main()
{
#if !defined(HAVE_CUDA)
std::cout << "CUDA support is required (CMake key 'WITH_CUDA' must be true).\n";
#endif
#if !defined(HAVE_TBB)
std::cout << "TBB support is required (CMake key 'WITH_TBB' must be true).\n";
#endif
#if defined(__arm__)
std::cout << "Unsupported for ARM CUDA library." << std::endl;
#endif
return 0;
}
#else
#include <cuda.h>
#include <cuda_runtime.h>
using namespace std;
using namespace cv;
using namespace cv::cuda;
struct Worker { void operator()(int device_id) const; };
void destroyContexts();
#define safeCall(expr) safeCall_(expr, #expr, __FILE__, __LINE__)
inline void safeCall_(int code, const char* expr, const char* file, int line)
{
if (code != CUDA_SUCCESS)
{
std::cout << "CUDA driver API error: code " << code << ", expr " << expr
<< ", file " << file << ", line " << line << endl;
destroyContexts();
exit(-1);
}
}
// Each GPU is associated with its own context
CUcontext contexts[2];
void inline contextOn(int id)
{
safeCall(cuCtxPushCurrent(contexts[id]));
}
void inline contextOff()
{
CUcontext prev_context;
safeCall(cuCtxPopCurrent(&prev_context));
}
// GPUs data
GpuMat d_left[2];
GpuMat d_right[2];
Ptr<cuda::StereoBM> bm[2];
GpuMat d_result[2];
static void printHelp()
{
std::cout << "Usage: driver_api_stereo_multi --left <left_image> --right <right_image>\n";
}
int main(int argc, char** argv)
{
if (argc < 5)
{
printHelp();
return -1;
}
int num_devices = getCudaEnabledDeviceCount();
if (num_devices < 2)
{
std::cout << "Two or more GPUs are required\n";
return -1;
}
for (int i = 0; i < num_devices; ++i)
{
cv::cuda::printShortCudaDeviceInfo(i);
DeviceInfo dev_info(i);
if (!dev_info.isCompatible())
{
std::cout << "GPU module isn't built for GPU #" << i << " ("
<< dev_info.name() << ", CC " << dev_info.majorVersion()
<< dev_info.minorVersion() << "\n";
return -1;
}
}
// Load input data
Mat left, right;
for (int i = 1; i < argc; ++i)
{
if (string(argv[i]) == "--left")
{
left = imread(argv[++i], cv::IMREAD_GRAYSCALE);
CV_Assert(!left.empty());
}
else if (string(argv[i]) == "--right")
{
right = imread(argv[++i], cv::IMREAD_GRAYSCALE);
CV_Assert(!right.empty());
}
else if (string(argv[i]) == "--help")
{
printHelp();
return -1;
}
}
// Init CUDA Driver API
safeCall(cuInit(0));
// Create context for GPU #0
CUdevice device;
safeCall(cuDeviceGet(&device, 0));
safeCall(cuCtxCreate(&contexts[0], 0, device));
contextOff();
// Create context for GPU #1
safeCall(cuDeviceGet(&device, 1));
safeCall(cuCtxCreate(&contexts[1], 0, device));
contextOff();
// Split source images for processing on GPU #0
contextOn(0);
d_left[0].upload(left.rowRange(0, left.rows / 2));
d_right[0].upload(right.rowRange(0, right.rows / 2));
bm[0] = cuda::createStereoBM();
contextOff();
// Split source images for processing on the GPU #1
contextOn(1);
d_left[1].upload(left.rowRange(left.rows / 2, left.rows));
d_right[1].upload(right.rowRange(right.rows / 2, right.rows));
bm[1] = cuda::createStereoBM();
contextOff();
// Execute calculation in two threads using two GPUs
int devices[] = {0, 1};
tbb::parallel_do(devices, devices + 2, Worker());
// Release the first GPU resources
contextOn(0);
imshow("GPU #0 result", Mat(d_result[0]));
d_left[0].release();
d_right[0].release();
d_result[0].release();
bm[0].release();
contextOff();
// Release the second GPU resources
contextOn(1);
imshow("GPU #1 result", Mat(d_result[1]));
d_left[1].release();
d_right[1].release();
d_result[1].release();
bm[1].release();
contextOff();
waitKey();
destroyContexts();
return 0;
}
void Worker::operator()(int device_id) const
{
contextOn(device_id);
bm[device_id]->compute(d_left[device_id], d_right[device_id], d_result[device_id]);
std::cout << "GPU #" << device_id << " (" << DeviceInfo().name()
<< "): finished\n";
contextOff();
}
void destroyContexts()
{
safeCall(cuCtxDestroy(contexts[0]));
safeCall(cuCtxDestroy(contexts[1]));
}
#endif
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