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added host code for gpu::matchTemplate (as NPP_staging was integrated)

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pull/13383/head
Alexey Spizhevoy 14 years ago
parent e62bf3a2ae
commit 6891a60149
2 changed files with 505 additions and 143 deletions
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  1. 488
      modules/gpu/src/match_template.cpp
  2. 160
      tests/gpu/src/match_template.cpp

488
modules/gpu/src/match_template.cpp
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@ -41,14 +41,11 @@
//M*/
#include "precomp.hpp"
#include <iostream>
#include <utility>
using namespace cv;
using namespace cv::gpu;
#define BLOCK_VERSION
#if !defined (HAVE_CUDA)
void cv::gpu::matchTemplate(const GpuMat&, const GpuMat&, GpuMat&, int) { throw_nogpu(); }
@ -56,12 +53,19 @@ void cv::gpu::matchTemplate(const GpuMat&, const GpuMat&, GpuMat&, int) { throw_
#else
#include <cufft.h>
#include <NPP_staging.h>
namespace cv { namespace gpu { namespace imgproc
{
namespace cv { namespace gpu { namespace imgproc
{
void multiplyAndNormalizeSpects(int n, float scale, const cufftComplex* a,
const cufftComplex* b, cufftComplex* c);
void matchTemplateNaive_CCORR_8U(
const DevMem2D image, const DevMem2D templ, DevMem2Df result, int cn);
void matchTemplateNaive_CCORR_32F(
const DevMem2D image, const DevMem2D templ, DevMem2Df result, int cn);
void matchTemplateNaive_SQDIFF_8U(
const DevMem2D image, const DevMem2D templ, DevMem2Df result, int cn);
@ -69,46 +73,193 @@ namespace cv { namespace gpu { namespace imgproc
const DevMem2D image, const DevMem2D templ, DevMem2Df result, int cn);
void matchTemplatePrepared_SQDIFF_8U(
int w, int h, const DevMem2Df image_sumsq, float templ_sumsq,
int w, int h, const DevMem2D_<unsigned long long> image_sqsum,
unsigned int templ_sqsum, DevMem2Df result, int cn);
void matchTemplatePrepared_SQDIFF_NORMED_8U(
int w, int h, const DevMem2D_<unsigned long long> image_sqsum,
unsigned int templ_sqsum, DevMem2Df result, int cn);
void matchTemplatePrepared_CCOFF_8U(
int w, int h, const DevMem2D_<unsigned int> image_sum,
unsigned int templ_sum, DevMem2Df result);
void matchTemplatePrepared_CCOFF_8UC2(
int w, int h,
const DevMem2D_<unsigned int> image_sum_r,
const DevMem2D_<unsigned int> image_sum_g,
unsigned int templ_sum_r, unsigned int templ_sum_g,
DevMem2Df result);
void matchTemplatePrepared_CCOFF_8UC3(
int w, int h,
const DevMem2D_<unsigned int> image_sum_r,
const DevMem2D_<unsigned int> image_sum_g,
const DevMem2D_<unsigned int> image_sum_b,
unsigned int templ_sum_r,
unsigned int templ_sum_g,
unsigned int templ_sum_b,
DevMem2Df result);
void matchTemplatePrepared_CCOFF_8UC4(
int w, int h,
const DevMem2D_<unsigned int> image_sum_r,
const DevMem2D_<unsigned int> image_sum_g,
const DevMem2D_<unsigned int> image_sum_b,
const DevMem2D_<unsigned int> image_sum_a,
unsigned int templ_sum_r,
unsigned int templ_sum_g,
unsigned int templ_sum_b,
unsigned int templ_sum_a,
DevMem2Df result);
void matchTemplatePrepared_CCOFF_NORMED_8U(
int w, int h, const DevMem2D_<unsigned int> image_sum,
const DevMem2D_<unsigned long long> image_sqsum,
unsigned int templ_sum, unsigned int templ_sqsum,
DevMem2Df result);
void matchTemplatePrepared_CCOFF_NORMED_8UC2(
int w, int h,
const DevMem2D_<unsigned int> image_sum_r, const DevMem2D_<unsigned long long> image_sqsum_r,
const DevMem2D_<unsigned int> image_sum_g, const DevMem2D_<unsigned long long> image_sqsum_g,
unsigned int templ_sum_r, unsigned int templ_sqsum_r,
unsigned int templ_sum_g, unsigned int templ_sqsum_g,
DevMem2Df result);
void matchTemplatePrepared_CCOFF_NORMED_8UC3(
int w, int h,
const DevMem2D_<unsigned int> image_sum_r, const DevMem2D_<unsigned long long> image_sqsum_r,
const DevMem2D_<unsigned int> image_sum_g, const DevMem2D_<unsigned long long> image_sqsum_g,
const DevMem2D_<unsigned int> image_sum_b, const DevMem2D_<unsigned long long> image_sqsum_b,
unsigned int templ_sum_r, unsigned int templ_sqsum_r,
unsigned int templ_sum_g, unsigned int templ_sqsum_g,
unsigned int templ_sum_b, unsigned int templ_sqsum_b,
DevMem2Df result);
void matchTemplatePrepared_CCOFF_NORMED_8UC4(
int w, int h,
const DevMem2D_<unsigned int> image_sum_r, const DevMem2D_<unsigned long long> image_sqsum_r,
const DevMem2D_<unsigned int> image_sum_g, const DevMem2D_<unsigned long long> image_sqsum_g,
const DevMem2D_<unsigned int> image_sum_b, const DevMem2D_<unsigned long long> image_sqsum_b,
const DevMem2D_<unsigned int> image_sum_a, const DevMem2D_<unsigned long long> image_sqsum_a,
unsigned int templ_sum_r, unsigned int templ_sqsum_r,
unsigned int templ_sum_g, unsigned int templ_sqsum_g,
unsigned int templ_sum_b, unsigned int templ_sqsum_b,
unsigned int templ_sum_a, unsigned int templ_sqsum_a,
DevMem2Df result);
void normalize_8U(int w, int h, const DevMem2D_<unsigned long long> image_sqsum,
unsigned int templ_sqsum, DevMem2Df result, int cn);
void extractFirstChannel_32F(const DevMem2D image, DevMem2Df result, int cn);
}}}
namespace
namespace
{
void matchTemplate_32F_SQDIFF(const GpuMat&, const GpuMat&, GpuMat&);
void matchTemplate_32F_CCORR(const GpuMat&, const GpuMat&, GpuMat&);
void matchTemplate_8U_SQDIFF(const GpuMat&, const GpuMat&, GpuMat&);
void matchTemplate_8U_CCORR(const GpuMat&, const GpuMat&, GpuMat&);
// Computes integral image. Result matrix will have data type 32S,
// while actuall data type is 32U
void integral_8U_32U(const GpuMat& src, GpuMat& sum);
// Computes squared integral image. Result matrix will have data type 64F,
// while actual data type is 64U
void sqrIntegral_8U_64U(const GpuMat& src, GpuMat& sqsum);
// Estimates optimal blocks size for FFT method
void estimateBlockSize(int w, int h, int tw, int th, int& bw, int& bh);
// Performs FFT-based cross-correlation
void crossCorr_32F(const GpuMat& image, const GpuMat& templ, GpuMat& result);
// Evaluates optimal template's area threshold. If
// template's area is less than the threshold, we use naive match
// template version, otherwise FFT-based (if available)
int getTemplateThreshold(int method, int depth);
void matchTemplate_CCORR_32F(const GpuMat& image, const GpuMat& templ, GpuMat& result);
void matchTemplate_CCORR_8U(const GpuMat& image, const GpuMat& templ, GpuMat& result);
void matchTemplate_CCORR_NORMED_8U(const GpuMat& image, const GpuMat& templ, GpuMat& result);
void matchTemplate_SQDIFF_32F(const GpuMat& image, const GpuMat& templ, GpuMat& result);
void matchTemplate_SQDIFF_8U(const GpuMat& image, const GpuMat& templ, GpuMat& result);
void matchTemplate_SQDIFF_NORMED_8U(const GpuMat& image, const GpuMat& templ, GpuMat& result);
void matchTemplate_CCOFF_8U(const GpuMat& image, const GpuMat& templ, GpuMat& result);
void matchTemplate_CCOFF_NORMED_8U(const GpuMat& image, const GpuMat& templ, GpuMat& result);
void integral_8U_32U(const GpuMat& src, GpuMat& sum)
{
CV_Assert(src.type() == CV_8U);
NppStSize32u roiSize;
roiSize.width = src.cols;
roiSize.height = src.rows;
NppSt32u bufSize;
nppSafeCall(nppiStIntegralGetSize_8u32u(roiSize, &bufSize));
GpuMat buf(1, bufSize, CV_8U);
sum.create(src.rows + 1, src.cols + 1, CV_32S);
nppSafeCall(nppiStIntegral_8u32u_C1R(
const_cast<NppSt8u*>(src.ptr<NppSt8u>(0)), src.step,
sum.ptr<NppSt32u>(0), sum.step, roiSize,
buf.ptr<NppSt8u>(0), bufSize));
}
void sqrIntegral_8U_64U(const GpuMat& src, GpuMat& sqsum)
{
CV_Assert(src.type() == CV_8U);
NppStSize32u roiSize;
roiSize.width = src.cols;
roiSize.height = src.rows;
NppSt32u bufSize;
nppSafeCall(nppiStSqrIntegralGetSize_8u64u(roiSize, &bufSize));
GpuMat buf(1, bufSize, CV_8U);
sqsum.create(src.rows + 1, src.cols + 1, CV_64F);
nppSafeCall(nppiStSqrIntegral_8u64u_C1R(
const_cast<NppSt8u*>(src.ptr<NppSt8u>(0)), src.step,
sqsum.ptr<NppSt64u>(0), sqsum.step, roiSize,
buf.ptr<NppSt8u>(0), bufSize));
}
#ifdef BLOCK_VERSION
void estimateBlockSize(int w, int h, int tw, int th, int& bw, int& bh)
{
const int scale = 40;
const int bh_min = 1024;
const int bw_min = 1024;
int major, minor;
getComputeCapability(getDevice(), major, minor);
int scale = 40;
int bh_min = 1024;
int bw_min = 1024;
if (major >= 2) // Fermi generation or newer
{
bh_min = 2048;
bw_min = 2048;
}
bw = std::max(tw * scale, bw_min);
bh = std::max(th * scale, bh_min);
bw = std::min(bw, w);
bh = std::min(bh, h);
}
#endif
void matchTemplate_32F_SQDIFF(const GpuMat& image, const GpuMat& templ, GpuMat& result)
{
result.create(image.rows - templ.rows + 1, image.cols - templ.cols + 1, CV_32F);
imgproc::matchTemplateNaive_SQDIFF_32F(image, templ, result, 1);
}
#ifdef BLOCK_VERSION
void matchTemplate_32F_CCORR(const GpuMat& image, const GpuMat& templ, GpuMat& result)
void crossCorr_32F(const GpuMat& image, const GpuMat& templ, GpuMat& result)
{
CV_Assert(image.type() == CV_32F);
CV_Assert(templ.type() == CV_32F);
result.create(image.rows - templ.rows + 1, image.cols - templ.cols + 1, CV_32F);
Size block_size;
estimateBlockSize(result.cols, result.rows, templ.cols, templ.rows,
estimateBlockSize(result.cols, result.rows, templ.cols, templ.rows,
block_size.width, block_size.height);
Size dft_size;
@ -139,7 +290,7 @@ namespace
GpuMat templ_roi(templ.size(), CV_32S, templ.data, templ.step);
GpuMat templ_block(dft_size, CV_32S, templ_data, dft_size.width * sizeof(cufftReal));
copyMakeBorder(templ_roi, templ_block, 0, templ_block.rows - templ_roi.rows, 0,
copyMakeBorder(templ_roi, templ_block, 0, templ_block.rows - templ_roi.rows, 0,
templ_block.cols - templ_roi.cols, 0);
CV_Assert(cufftExecR2C(planR2C, templ_data, templ_spect) == CUFFT_SUCCESS);
@ -148,16 +299,16 @@ namespace
for (int y = 0; y < result.rows; y += block_size.height)
{
for (int x = 0; x < result.cols; x += block_size.width)
{
{
Size image_roi_size;
image_roi_size.width = min(x + dft_size.width, image.cols) - x;
image_roi_size.height = min(y + dft_size.height, image.rows) - y;
GpuMat image_roi(image_roi_size, CV_32S, (void*)(image.ptr<float>(y) + x), image.step);
copyMakeBorder(image_roi, image_block, 0, image_block.rows - image_roi.rows, 0,
copyMakeBorder(image_roi, image_block, 0, image_block.rows - image_roi.rows, 0,
image_block.cols - image_roi.cols, 0);
CV_Assert(cufftExecR2C(planR2C, image_data, image_spect) == CUFFT_SUCCESS);
imgproc::multiplyAndNormalizeSpects(spect_len, 1.f / dft_size.area(),
imgproc::multiplyAndNormalizeSpects(spect_len, 1.f / dft_size.area(),
image_spect, templ_spect, result_spect);
CV_Assert(cufftExecC2R(planC2R, result_spect, result_data) == CUFFT_SUCCESS);
@ -180,79 +331,236 @@ namespace
cudaFree(templ_data);
cudaFree(result_data);
}
#else
void matchTemplate_32F_CCORR(const GpuMat& image, const GpuMat& templ, GpuMat& result)
int getTemplateThreshold(int method, int depth)
{
Size opt_size;
opt_size.width = getOptimalDFTSize(image.cols);
opt_size.height = getOptimalDFTSize(image.rows);
switch (method)
{
case CV_TM_CCORR:
if (depth == CV_32F) return 250;
if (depth == CV_8U) return 300;
break;
case CV_TM_SQDIFF:
if (depth == CV_8U) return 500;
break;
}
CV_Error(CV_StsBadArg, "getTemplateThreshold: unsupported match template mode");
return 0;
}
cufftReal* image_data;
cufftReal* templ_data;
cufftReal* result_data;
cudaMalloc((void**)&image_data, sizeof(cufftReal) * opt_size.area());
cudaMalloc((void**)&templ_data, sizeof(cufftReal) * opt_size.area());
cudaMalloc((void**)&result_data, sizeof(cufftReal) * opt_size.area());
void matchTemplate_CCORR_32F(const GpuMat& image, const GpuMat& templ, GpuMat& result)
{
result.create(image.rows - templ.rows + 1, image.cols - templ.cols + 1, CV_32F);
if (templ.size().area() < getTemplateThreshold(CV_TM_CCORR, CV_32F))
{
imgproc::matchTemplateNaive_CCORR_32F(image, templ, result, image.channels());
return;
}
int spect_len = opt_size.height * (opt_size.width / 2 + 1);
cufftComplex* image_spect;
cufftComplex* templ_spect;
cufftComplex* result_spect;
cudaMalloc((void**)&image_spect, sizeof(cufftComplex) * spect_len);
cudaMalloc((void**)&templ_spect, sizeof(cufftComplex) * spect_len);
cudaMalloc((void**)&result_spect, sizeof(cufftComplex) * spect_len);
GpuMat result_;
crossCorr_32F(image.reshape(1), templ.reshape(1), result_);
imgproc::extractFirstChannel_32F(result_, result, image.channels());
}
GpuMat image_(image.size(), CV_32S, image.data, image.step);
GpuMat image_cont(opt_size, CV_32S, image_data, opt_size.width * sizeof(cufftReal));
copyMakeBorder(image_, image_cont, 0, image_cont.rows - image.rows, 0,
image_cont.cols - image.cols, 0);
GpuMat templ_(templ.size(), CV_32S, templ.data, templ.step);
GpuMat templ_cont(opt_size, CV_32S, templ_data, opt_size.width * sizeof(cufftReal));
copyMakeBorder(templ_, templ_cont, 0, templ_cont.rows - templ.rows, 0,
templ_cont.cols - templ.cols, 0);
void matchTemplate_CCORR_8U(const GpuMat& image, const GpuMat& templ, GpuMat& result)
{
if (templ.size().area() < getTemplateThreshold(CV_TM_CCORR, CV_8U))
{
result.create(image.rows - templ.rows + 1, image.cols - templ.cols + 1, CV_32F);
imgproc::matchTemplateNaive_CCORR_8U(image, templ, result, image.channels());
return;
}
cufftHandle planR2C, planC2R;
CV_Assert(cufftPlan2d(&planC2R, opt_size.height, opt_size.width, CUFFT_C2R) == CUFFT_SUCCESS);
CV_Assert(cufftPlan2d(&planR2C, opt_size.height, opt_size.width, CUFFT_R2C) == CUFFT_SUCCESS);
GpuMat imagef, templf;
image.convertTo(imagef, CV_32F);
templ.convertTo(templf, CV_32F);
matchTemplate_CCORR_32F(imagef, templf, result);
}
CV_Assert(cufftExecR2C(planR2C, image_data, image_spect) == CUFFT_SUCCESS);
CV_Assert(cufftExecR2C(planR2C, templ_data, templ_spect) == CUFFT_SUCCESS);
imgproc::multiplyAndNormalizeSpects(spect_len, 1.f / opt_size.area(),
image_spect, templ_spect, result_spect);
CV_Assert(cufftExecC2R(planC2R, result_spect, result_data) == CUFFT_SUCCESS);
void matchTemplate_CCORR_NORMED_8U(const GpuMat& image, const GpuMat& templ,
GpuMat& result)
{
matchTemplate_CCORR_8U(image, templ, result);
cufftDestroy(planR2C);
cufftDestroy(planC2R);
GpuMat img_sqsum;
sqrIntegral_8U_64U(image.reshape(1), img_sqsum);
GpuMat result_cont(image.rows - templ.rows + 1, image.cols - templ.cols + 1, CV_32F,
result_data, opt_size.width * sizeof(cufftReal));
result_cont.copyTo(result);
unsigned int templ_sqsum = (unsigned int)sqrSum(templ.reshape(1))[0];
imgproc::normalize_8U(templ.cols, templ.rows, img_sqsum, templ_sqsum,
result, image.channels());
}
cudaFree(image_spect);
cudaFree(templ_spect);
cudaFree(result_spect);
cudaFree(image_data);
cudaFree(templ_data);
cudaFree(result_data);
void matchTemplate_SQDIFF_32F(const GpuMat& image, const GpuMat& templ, GpuMat& result)
{
result.create(image.rows - templ.rows + 1, image.cols - templ.cols + 1, CV_32F);
imgproc::matchTemplateNaive_SQDIFF_32F(image, templ, result, image.channels());
}
#endif
void matchTemplate_8U_SQDIFF(const GpuMat& image, const GpuMat& templ, GpuMat& result)
void matchTemplate_SQDIFF_8U(const GpuMat& image, const GpuMat& templ, GpuMat& result)
{
result.create(image.rows - templ.rows + 1, image.cols - templ.cols + 1, CV_32F);
imgproc::matchTemplateNaive_SQDIFF_8U(image, templ, result, 1);
if (templ.size().area() < getTemplateThreshold(CV_TM_SQDIFF, CV_8U))
{
result.create(image.rows - templ.rows + 1, image.cols - templ.cols + 1, CV_32F);
imgproc::matchTemplateNaive_SQDIFF_8U(image, templ, result, image.channels());
return;
}
GpuMat img_sqsum;
sqrIntegral_8U_64U(image.reshape(1), img_sqsum);
unsigned int templ_sqsum = (unsigned int)sqrSum(templ.reshape(1))[0];
matchTemplate_CCORR_8U(image, templ, result);
imgproc::matchTemplatePrepared_SQDIFF_8U(
templ.cols, templ.rows, img_sqsum, templ_sqsum, result, image.channels());
}
void matchTemplate_SQDIFF_NORMED_8U(const GpuMat& image, const GpuMat& templ, GpuMat& result)
{
GpuMat img_sqsum;
sqrIntegral_8U_64U(image.reshape(1), img_sqsum);
unsigned int templ_sqsum = (unsigned int)sqrSum(templ.reshape(1))[0];
matchTemplate_CCORR_8U(image, templ, result);
imgproc::matchTemplatePrepared_SQDIFF_NORMED_8U(
templ.cols, templ.rows, img_sqsum, templ_sqsum, result, image.channels());
}
void matchTemplate_CCOFF_8U(const GpuMat& image, const GpuMat& templ, GpuMat& result)
{
matchTemplate_CCORR_8U(image, templ, result);
if (image.channels() == 1)
{
GpuMat image_sum;
integral_8U_32U(image, image_sum);
unsigned int templ_sum = (unsigned int)sum(templ)[0];
imgproc::matchTemplatePrepared_CCOFF_8U(templ.cols, templ.rows,
image_sum, templ_sum, result);
}
else
{
std::vector<GpuMat> images;
std::vector<GpuMat> image_sums(image.channels());
split(image, images);
for (int i = 0; i < image.channels(); ++i)
integral_8U_32U(images[i], image_sums[i]);
Scalar templ_sum = sum(templ);
switch (image.channels())
{
case 2:
imgproc::matchTemplatePrepared_CCOFF_8UC2(
templ.cols, templ.rows, image_sums[0], image_sums[1],
(unsigned int)templ_sum[0], (unsigned int)templ_sum[1],
result);
break;
case 3:
imgproc::matchTemplatePrepared_CCOFF_8UC3(
templ.cols, templ.rows, image_sums[0], image_sums[1], image_sums[2],
(unsigned int)templ_sum[0], (unsigned int)templ_sum[1], (unsigned int)templ_sum[2],
result);
break;
case 4:
imgproc::matchTemplatePrepared_CCOFF_8UC4(
templ.cols, templ.rows, image_sums[0], image_sums[1], image_sums[2], image_sums[3],
(unsigned int)templ_sum[0], (unsigned int)templ_sum[1], (unsigned int)templ_sum[2],
(unsigned int)templ_sum[3], result);
break;
default:
CV_Error(CV_StsBadArg, "matchTemplate: unsupported number of channels");
}
}
}
void matchTemplate_8U_CCORR(const GpuMat& image, const GpuMat& templ, GpuMat& result)
void matchTemplate_CCOFF_NORMED_8U(const GpuMat& image, const GpuMat& templ, GpuMat& result)
{
GpuMat imagef, templf;
image.convertTo(imagef, CV_32F);
templ.convertTo(templf, CV_32F);
matchTemplate_32F_CCORR(imagef, templf, result);
matchTemplate_CCORR_32F(imagef, templf, result);
if (image.channels() == 1)
{
GpuMat image_sum, image_sqsum;
integral_8U_32U(image, image_sum);
sqrIntegral_8U_64U(image, image_sqsum);
unsigned int templ_sum = (unsigned int)sum(templ)[0];
unsigned int templ_sqsum = (unsigned int)sqrSum(templ)[0];
imgproc::matchTemplatePrepared_CCOFF_NORMED_8U(
templ.cols, templ.rows, image_sum, image_sqsum,
templ_sum, templ_sqsum, result);
}
else
{
std::vector<GpuMat> images;
std::vector<GpuMat> image_sums(image.channels());
std::vector<GpuMat> image_sqsums(image.channels());
split(image, images);
for (int i = 0; i < image.channels(); ++i)
{
integral_8U_32U(images[i], image_sums[i]);
sqrIntegral_8U_64U(images[i], image_sqsums[i]);
}
Scalar templ_sum = sum(templ);
Scalar templ_sqsum = sqrSum(templ);
switch (image.channels())
{
case 2:
imgproc::matchTemplatePrepared_CCOFF_NORMED_8UC2(
templ.cols, templ.rows,
image_sums[0], image_sqsums[0],
image_sums[1], image_sqsums[1],
(unsigned int)templ_sum[0], (unsigned int)templ_sqsum[0],
(unsigned int)templ_sum[1], (unsigned int)templ_sqsum[1],
result);
break;
case 3:
imgproc::matchTemplatePrepared_CCOFF_NORMED_8UC3(
templ.cols, templ.rows,
image_sums[0], image_sqsums[0],
image_sums[1], image_sqsums[1],
image_sums[2], image_sqsums[2],
(unsigned int)templ_sum[0], (unsigned int)templ_sqsum[0],
(unsigned int)templ_sum[1], (unsigned int)templ_sqsum[1],
(unsigned int)templ_sum[2], (unsigned int)templ_sqsum[2],
result);
break;
case 4:
imgproc::matchTemplatePrepared_CCOFF_NORMED_8UC4(
templ.cols, templ.rows,
image_sums[0], image_sqsums[0],
image_sums[1], image_sqsums[1],
image_sums[2], image_sqsums[2],
image_sums[3], image_sqsums[3],
(unsigned int)templ_sum[0], (unsigned int)templ_sqsum[0],
(unsigned int)templ_sum[1], (unsigned int)templ_sqsum[1],
(unsigned int)templ_sum[2], (unsigned int)templ_sqsum[2],
(unsigned int)templ_sum[3], (unsigned int)templ_sqsum[3],
result);
break;
default:
CV_Error(CV_StsBadArg, "matchTemplate: unsupported number of channels");
}
}
}
}
@ -264,17 +572,18 @@ void cv::gpu::matchTemplate(const GpuMat& image, const GpuMat& templ, GpuMat& re
typedef void (*Caller)(const GpuMat&, const GpuMat&, GpuMat&);
static const Caller callers8U[] = { ::matchTemplate_8U_SQDIFF, 0,
::matchTemplate_8U_CCORR, 0, 0, 0 };
static const Caller callers32F[] = { ::matchTemplate_32F_SQDIFF, 0,
::matchTemplate_32F_CCORR, 0, 0, 0 };
static const Caller callers8U[] = { ::matchTemplate_SQDIFF_8U, ::matchTemplate_SQDIFF_NORMED_8U,
::matchTemplate_CCORR_8U, ::matchTemplate_CCORR_NORMED_8U,
::matchTemplate_CCOFF_8U, ::matchTemplate_CCOFF_NORMED_8U };
static const Caller callers32F[] = { ::matchTemplate_SQDIFF_32F, 0,
::matchTemplate_CCORR_32F, 0, 0, 0 };
const Caller* callers = 0;
switch (image.type())
const Caller* callers;
switch (image.depth())
{
case CV_8U: callers = callers8U; break;
case CV_32F: callers = callers32F; break;
default: CV_Error(CV_StsBadArg, "matchTemplate: unsupported data type");
case CV_8U: callers = callers8U; break;
case CV_32F: callers = callers32F; break;
default: CV_Error(CV_StsBadArg, "matchTemplate: unsupported data type");
}
Caller caller = callers[method];
@ -284,3 +593,4 @@ void cv::gpu::matchTemplate(const GpuMat& image, const GpuMat& templ, GpuMat& re
#endif

160
tests/gpu/src/match_template.cpp
Unescape View File

@ -48,7 +48,7 @@
#ifdef SHOW_TIME
#include <ctime>
#define F(x)
#define F(x) x
#else
#define F(x)
#endif
@ -70,54 +70,106 @@ struct CV_GpuMatchTemplateTest: CvTest
int n, m, h, w;
F(clock_t t;)
for (int i = 0; i < 3; ++i)
for (int cn = 1; cn <= 4; ++cn)
{
n = 1 + rand() % 2000;
m = 1 + rand() % 1000;
do h = 1 + rand() % 30; while (h > n);
do w = 1 + rand() % 30; while (w > m);
//cout << "w: " << w << " h: " << h << endl;
gen(image, n, m, CV_8U);
gen(templ, h, w, CV_8U);
F(t = clock();)
matchTemplate(image, templ, dst_gold, CV_TM_SQDIFF);
F(cout << "cpu:" << clock() - t << endl;)
F(t = clock();)
gpu::matchTemplate(gpu::GpuMat(image), gpu::GpuMat(templ), dst, CV_TM_SQDIFF);
F(cout << "gpu_block: " << clock() - t << endl;)
if (!check(dst_gold, Mat(dst), 5 * h * w * 1e-5f)) return;
gen(image, n, m, CV_8U);
gen(templ, h, w, CV_8U);
F(t = clock();)
matchTemplate(image, templ, dst_gold, CV_TM_CCORR);
F(cout << "cpu:" << clock() - t << endl;)
F(t = clock();)
gpu::matchTemplate(gpu::GpuMat(image), gpu::GpuMat(templ), dst, CV_TM_CCORR);
F(cout << "gpu_block: " << clock() - t << endl;)
if (!check(dst_gold, Mat(dst), 5 * h * w * 1e-5f)) return;
gen(image, n, m, CV_32F);
gen(templ, h, w, CV_32F);
F(t = clock();)
matchTemplate(image, templ, dst_gold, CV_TM_SQDIFF);
F(cout << "cpu:" << clock() - t << endl;)
F(t = clock();)
gpu::matchTemplate(gpu::GpuMat(image), gpu::GpuMat(templ), dst, CV_TM_SQDIFF);
F(cout << "gpu_block: " << clock() - t << endl;)
if (!check(dst_gold, Mat(dst), 0.25f * h * w * 1e-5f)) return;
gen(image, n, m, CV_32F);
gen(templ, h, w, CV_32F);
F(t = clock();)
matchTemplate(image, templ, dst_gold, CV_TM_CCORR);
F(cout << "cpu:" << clock() - t << endl;)
F(t = clock();)
gpu::matchTemplate(gpu::GpuMat(image), gpu::GpuMat(templ), dst, CV_TM_CCORR);
F(cout << "gpu_block: " << clock() - t << endl;)
if (!check(dst_gold, Mat(dst), 0.25f * h * w * 1e-5f)) return;
F(ts->printf(CvTS::CONSOLE, "cn: %d\n", cn);)
for (int i = 0; i <= 0; ++i)
{
n = 1 + rand() % 1000;
m = 1 + rand() % 1000;
do h = 1 + rand() % 100; while (h > n);
do w = 1 + rand() % 100; while (w > m);
//cout << "w: " << w << " h: " << h << endl;
gen(image, n, m, CV_8U, cn);
gen(templ, h, w, CV_8U, cn);
F(t = clock();)
matchTemplate(image, templ, dst_gold, CV_TM_SQDIFF);
F(cout << "depth: 8U cn: " << cn << " n: " << n << " m: " << m << " w: " << w << " h: " << h << endl;)
F(cout << "cpu:" << clock() - t << endl;)
F(t = clock();)
gpu::matchTemplate(gpu::GpuMat(image), gpu::GpuMat(templ), dst, CV_TM_SQDIFF);
F(cout << "gpu_block: " << clock() - t << endl;)
if (!check(dst_gold, Mat(dst), 5 * h * w * 1e-4f)) return;
gen(image, n, m, CV_8U, cn);
gen(templ, h, w, CV_8U, cn);
F(t = clock();)
matchTemplate(image, templ, dst_gold, CV_TM_SQDIFF_NORMED);
F(cout << "depth: 8U cn: " << cn << " n: " << n << " m: " << m << " w: " << w << " h: " << h << endl;)
F(cout << "cpu:" << clock() - t << endl;)
F(t = clock();)
gpu::matchTemplate(gpu::GpuMat(image), gpu::GpuMat(templ), dst, CV_TM_SQDIFF_NORMED);
F(cout << "gpu_block: " << clock() - t << endl;)
if (!check(dst_gold, Mat(dst), h * w * 1e-5f)) return;
gen(image, n, m, CV_8U, cn);
gen(templ, h, w, CV_8U, cn);
F(t = clock();)
matchTemplate(image, templ, dst_gold, CV_TM_CCORR);
F(cout << "depth: 8U cn: " << cn << " n: " << n << " m: " << m << " w: " << w << " h: " << h << endl;)
F(cout << "cpu:" << clock() - t << endl;)
F(t = clock();)
gpu::matchTemplate(gpu::GpuMat(image), gpu::GpuMat(templ), dst, CV_TM_CCORR);
F(cout << "gpu_block: " << clock() - t << endl;)
if (!check(dst_gold, Mat(dst), 5 * h * w * cn * cn * 1e-5f)) return;
gen(image, n, m, CV_8U, cn);
gen(templ, h, w, CV_8U, cn);
F(t = clock();)
matchTemplate(image, templ, dst_gold, CV_TM_CCORR_NORMED);
F(cout << "depth: 8U cn: " << cn << " n: " << n << " m: " << m << " w: " << w << " h: " << h << endl;)
F(cout << "cpu:" << clock() - t << endl;)
F(t = clock();)
gpu::matchTemplate(gpu::GpuMat(image), gpu::GpuMat(templ), dst, CV_TM_CCORR_NORMED);
F(cout << "gpu_block: " << clock() - t << endl;)
if (!check(dst_gold, Mat(dst), h * w * 1e-5f)) return;
gen(image, n, m, CV_8U, cn);
gen(templ, h, w, CV_8U, cn);
F(t = clock();)
matchTemplate(image, templ, dst_gold, CV_TM_CCOEFF);
F(cout << "depth: 8U cn: " << cn << " n: " << n << " m: " << m << " w: " << w << " h: " << h << endl;)
F(cout << "cpu:" << clock() - t << endl;)
F(t = clock();)
gpu::matchTemplate(gpu::GpuMat(image), gpu::GpuMat(templ), dst, CV_TM_CCOEFF);
F(cout << "gpu_block: " << clock() - t << endl;)
if (!check(dst_gold, Mat(dst), 5 * h * w * cn * cn * 1e-5f)) return;
gen(image, n, m, CV_8U, cn);
gen(templ, h, w, CV_8U, cn);
F(t = clock();)
matchTemplate(image, templ, dst_gold, CV_TM_CCOEFF_NORMED);
F(cout << "depth: 8U cn: " << cn << " n: " << n << " m: " << m << " w: " << w << " h: " << h << endl;)
F(cout << "cpu:" << clock() - t << endl;)
F(t = clock();)
gpu::matchTemplate(gpu::GpuMat(image), gpu::GpuMat(templ), dst, CV_TM_CCOEFF_NORMED);
F(cout << "gpu_block: " << clock() - t << endl;)
if (!check(dst_gold, Mat(dst), h * w * 1e-6f)) return;
gen(image, n, m, CV_32F, cn);
gen(templ, h, w, CV_32F, cn);
F(t = clock();)
matchTemplate(image, templ, dst_gold, CV_TM_SQDIFF);
F(cout << "depth: 32F cn: " << cn << " n: " << n << " m: " << m << " w: " << w << " h: " << h << endl;)
F(cout << "cpu:" << clock() - t << endl;)
F(t = clock();)
gpu::matchTemplate(gpu::GpuMat(image), gpu::GpuMat(templ), dst, CV_TM_SQDIFF);
F(cout << "gpu_block: " << clock() - t << endl;)
if (!check(dst_gold, Mat(dst), 0.25f * h * w * 1e-5f)) return;
gen(image, n, m, CV_32F, cn);
gen(templ, h, w, CV_32F, cn);
F(t = clock();)
matchTemplate(image, templ, dst_gold, CV_TM_CCORR);
F(cout << "depth: 32F cn: " << cn << " n: " << n << " m: " << m << " w: " << w << " h: " << h << endl;)
F(cout << "cpu:" << clock() - t << endl;)
F(t = clock();)
gpu::matchTemplate(gpu::GpuMat(image), gpu::GpuMat(templ), dst, CV_TM_CCORR);
F(cout << "gpu_block: " << clock() - t << endl;)
if (!check(dst_gold, Mat(dst), 0.25f * h * w * 1e-5f)) return;
}
}
}
catch (const Exception& e)
@ -128,14 +180,14 @@ struct CV_GpuMatchTemplateTest: CvTest
}
}
void gen(Mat& a, int rows, int cols, int type)
void gen(Mat& a, int rows, int cols, int depth, int cn)
{
RNG rng;
a.create(rows, cols, type);
if (type == CV_8U)
rng.fill(a, RNG::UNIFORM, Scalar(0), Scalar(10));
else if (type == CV_32F)
rng.fill(a, RNG::UNIFORM, Scalar(0.f), Scalar(1.f));
a.create(rows, cols, CV_MAKETYPE(depth, cn));
if (depth == CV_8U)
rng.fill(a, RNG::UNIFORM, Scalar::all(1), Scalar::all(10));
else if (depth == CV_32F)
rng.fill(a, RNG::UNIFORM, Scalar::all(0.001f), Scalar::all(1.f));
}
bool check(const Mat& a, const Mat& b, float max_err)

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