use perf test replace performance sample

This commit is contained in:
yao
2013-03-27 12:04:48 +08:00
parent 55c9a7c87d
commit 5539e85a11
26 changed files with 3791 additions and 14305 deletions

View File

@@ -44,79 +44,77 @@
//M*/
#include "precomp.hpp"
#include <iomanip>
#ifdef HAVE_OPENCL
using namespace cv;
using namespace cv::ocl;
using namespace cvtest;
using namespace testing;
using namespace std;
PARAM_TEST_CASE(Blend, MatType, int)
///////////// blend ////////////////////////
template <typename T>
void blendLinearGold(const cv::Mat &img1, const cv::Mat &img2, const cv::Mat &weights1, const cv::Mat &weights2, cv::Mat &result_gold)
{
int type;
int channels;
std::vector<cv::ocl::Info> oclinfo;
result_gold.create(img1.size(), img1.type());
virtual void SetUp()
int cn = img1.channels();
for (int y = 0; y < img1.rows; ++y)
{
const float *weights1_row = weights1.ptr<float>(y);
const float *weights2_row = weights2.ptr<float>(y);
const T *img1_row = img1.ptr<T>(y);
const T *img2_row = img2.ptr<T>(y);
T *result_gold_row = result_gold.ptr<T>(y);
type = GET_PARAM(0);
channels = GET_PARAM(1);
//int devnums = getDevice(oclinfo);
//CV_Assert(devnums > 0);
//cv::ocl::setBinpath(CLBINPATH);
}
};
TEST_P(Blend, Performance)
{
cv::Size size(MWIDTH, MHEIGHT);
cv::Mat img1_host = randomMat(size, CV_MAKETYPE(type, channels), 0, type == CV_8U ? 255.0 : 1.0);
cv::Mat img2_host = randomMat(size, CV_MAKETYPE(type, channels), 0, type == CV_8U ? 255.0 : 1.0);
cv::Mat weights1 = randomMat(size, CV_32F, 0, 1);
cv::Mat weights2 = randomMat(size, CV_32F, 0, 1);
cv::ocl::oclMat gimg1(size, CV_MAKETYPE(type, channels)), gimg2(size, CV_MAKETYPE(type, channels)), gweights1(size, CV_32F), gweights2(size, CV_32F);
cv::ocl::oclMat gdst(size, CV_MAKETYPE(type, channels));
double totalgputick_all = 0;
double totalgputick_kernel = 0;
double t1 = 0;
double t2 = 0;
for (int j = 0; j < LOOP_TIMES + 1; j ++) //LOOP_TIMES=100
{
t1 = (double)cvGetTickCount();
cv::ocl::oclMat gimg1 = cv::ocl::oclMat(img1_host);
cv::ocl::oclMat gimg2 = cv::ocl::oclMat(img2_host);
cv::ocl::oclMat gweights1 = cv::ocl::oclMat(weights1);
cv::ocl::oclMat gweights2 = cv::ocl::oclMat(weights1);
t2 = (double)cvGetTickCount();
cv::ocl::blendLinear(gimg1, gimg2, gweights1, gweights2, gdst);
t2 = (double)cvGetTickCount() - t2;
cv::Mat m;
gdst.download(m);
t1 = (double)cvGetTickCount() - t1;
if (j == 0)
for (int x = 0; x < img1.cols * cn; ++x)
{
continue;
float w1 = weights1_row[x / cn];
float w2 = weights2_row[x / cn];
result_gold_row[x] = static_cast<T>((img1_row[x] * w1 + img2_row[x] * w2) / (w1 + w2 + 1e-5f));
}
totalgputick_all = t1 + totalgputick_all;
totalgputick_kernel = t2 + totalgputick_kernel;
};
cout << "average gpu total runtime is " << totalgputick_all / ((double)cvGetTickFrequency()* LOOP_TIMES * 1000.) << "ms" << endl;
cout << "average gpu runtime without data transfering is " << totalgputick_kernel / ((double)cvGetTickFrequency()* LOOP_TIMES * 1000.) << "ms" << endl;
}
}
TEST(blend)
{
Mat src1, src2, weights1, weights2, dst;
ocl::oclMat d_src1, d_src2, d_weights1, d_weights2, d_dst;
INSTANTIATE_TEST_CASE_P(GPU_ImgProc, Blend, Combine(
Values(CV_8U, CV_32F), Values(1, 4)));
#endif
int all_type[] = {CV_8UC1, CV_8UC4};
std::string type_name[] = {"CV_8UC1", "CV_8UC4"};
for (int size = Min_Size; size <= Max_Size; size *= Multiple)
{
for (size_t j = 0; j < sizeof(all_type) / sizeof(int); j++)
{
SUBTEST << size << 'x' << size << "; " << type_name[j] << " and CV_32FC1";
gen(src1, size, size, all_type[j], 0, 256);
gen(src2, size, size, all_type[j], 0, 256);
gen(weights1, size, size, CV_32FC1, 0, 1);
gen(weights2, size, size, CV_32FC1, 0, 1);
blendLinearGold<uchar>(src1, src2, weights1, weights2, dst);
CPU_ON;
blendLinearGold<uchar>(src1, src2, weights1, weights2, dst);
CPU_OFF;
d_src1.upload(src1);
d_src2.upload(src2);
d_weights1.upload(weights1);
d_weights2.upload(weights2);
WARMUP_ON;
ocl::blendLinear(d_src1, d_src2, d_weights1, d_weights2, d_dst);
WARMUP_OFF;
GPU_ON;
ocl::blendLinear(d_src1, d_src2, d_weights1, d_weights2, d_dst);
;
GPU_OFF;
GPU_FULL_ON;
d_src1.upload(src1);
d_src2.upload(src2);
d_weights1.upload(weights1);
d_weights2.upload(weights2);
ocl::blendLinear(d_src1, d_src2, d_weights1, d_weights2, d_dst);
d_dst.download(dst);
GPU_FULL_OFF;
}
}
}