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meanShiftFiltering_GPU output parameters changed to CV_8UC4. This is a start for moving from 3 channel to C4 images within GPU module.

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This commit is contained in:
Kirill Kornyakov 2010-09-03 14:32:12 +00:00
parent 2154a0ce63
commit ec7e937481
5 changed files with 137 additions and 103 deletions
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3
modules/gpu/include/opencv2/gpu/gpu.hpp
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@ -347,7 +347,8 @@ namespace cv
CV_EXPORTS void remap(const GpuMat& src, const GpuMat& xmap, const GpuMat& ymap, GpuMat& dst);
// Does mean shift filtering on GPU.
CV_EXPORTS void meanShiftFiltering_GPU(const GpuMat& src, GpuMat& dst, int sp, int sr, TermCriteria criteria = TermCriteria(TermCriteria::MAX_ITER + TermCriteria::EPS, 5, 1));
CV_EXPORTS void meanShiftFiltering_GPU(const GpuMat& src, GpuMat& dst, int sp, int sr,
TermCriteria criteria = TermCriteria(TermCriteria::MAX_ITER + TermCriteria::EPS, 5, 1));
// Does coloring of disparity image: [0..ndisp) -> [0..240, 1, 1] in HSV.
// Supported types of input disparity: CV_8U, CV_16S.

11
modules/gpu/src/cuda/imgproc.cu
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@ -163,7 +163,8 @@ namespace imgproc
{
texture<uchar4, 2> tex_meanshift;
extern "C" __global__ void meanshift_kernel( unsigned char* out, int out_step, int cols, int rows, int sp, int sr, int maxIter, float eps )
extern "C" __global__ void meanshift_kernel( unsigned char* out, int out_step, int cols, int rows,
int sp, int sr, int maxIter, float eps )
{
int x0 = blockIdx.x * blockDim.x + threadIdx.x;
int y0 = blockIdx.y * blockDim.y + threadIdx.y;
@ -224,10 +225,8 @@ namespace imgproc
break;
}
int base = (blockIdx.y * blockDim.y + threadIdx.y) * out_step + (blockIdx.x * blockDim.x + threadIdx.x) * 3 * sizeof(uchar);
out[base+0] = c.x;
out[base+1] = c.y;
out[base+2] = c.z;
int base = (blockIdx.y * blockDim.y + threadIdx.y) * out_step + (blockIdx.x * blockDim.x + threadIdx.x) * 4 * sizeof(uchar);
*(uchar4*)(out + base) = c;
}
}
}
@ -236,7 +235,7 @@ namespace cv { namespace gpu { namespace impl
{
extern "C" void meanShiftFiltering_gpu(const DevMem2D& src, DevMem2D dst, int sp, int sr, int maxIter, float eps)
{
dim3 grid(1, 1, 1);
dim3 grid(1, 1, 1);
dim3 threads(32, 16, 1);
grid.x = divUp(src.cols, threads.x);
grid.y = divUp(src.rows, threads.y);

6
modules/gpu/src/imgproc_gpu.cpp
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@ -119,18 +119,18 @@ void cv::gpu::meanShiftFiltering_GPU(const GpuMat& src, GpuMat& dst, int sp, int
if( src.depth() != CV_8U || src.channels() != 4 )
CV_Error( CV_StsUnsupportedFormat, "Only 8-bit, 4-channel images are supported" );
dst.create( src.size(), CV_8UC3 );
dst.create( src.size(), CV_8UC4 );
float eps;
if( !(criteria.type & TermCriteria::MAX_ITER) )
criteria.maxCount = 5;
int maxIter = std::min(std::max(criteria.maxCount, 1), 100);
float eps;
if( !(criteria.type & TermCriteria::EPS) )
eps = 1.f;
eps = (float)std::max(criteria.epsilon, 0.0);
impl::meanShiftFiltering_gpu(src, dst, sp, sr, maxIter, eps);
}

192
tests/gpu/src/meanshift.cpp
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@ -1,82 +1,110 @@
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// Intel License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000, Intel Corporation, all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of Intel Corporation may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#include "gputest.hpp"
#include <iostream>
#include <string>
#include <opencv2/opencv.hpp>
#include <opencv2/gpu/gpu.hpp>
class CV_GpuMeanShift : public CvTest
{
public:
CV_GpuMeanShift();
protected:
void run(int);
};
CV_GpuMeanShift::CV_GpuMeanShift(): CvTest( "GPU-MeanShift", "MeanShift" ){}
void CV_GpuMeanShift::run(int )
{
int spatialRad = 30;
int colorRad = 30;
cv::Mat img = cv::imread(std::string(ts->get_data_path()) + "meanshift/cones.png");
cv::Mat img_template = cv::imread(std::string(ts->get_data_path()) + "meanshift/con_result.png");
cv::Mat rgba;
cvtColor(img, rgba, CV_BGR2BGRA);
cv::gpu::GpuMat res;
cv::gpu::meanShiftFiltering_GPU( cv::gpu::GpuMat(rgba), res, spatialRad, colorRad );
res.convertTo(res, img_template.type());
double norm = cv::norm(res, img_template, cv::NORM_INF);
if (norm >= 0.5) std::cout << "MeanShift norm = " << norm << std::endl;
ts->set_failed_test_info((norm < 0.5) ? CvTS::OK : CvTS::FAIL_GENERIC);
}
CV_GpuMeanShift CV_GpuMeanShift_test;
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// Intel License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000, Intel Corporation, all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of Intel Corporation may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#include "gputest.hpp"
#include <iostream>
#include <string>
#include <opencv2/opencv.hpp>
#include <opencv2/gpu/gpu.hpp>
class CV_GpuMeanShift : public CvTest
{
public:
CV_GpuMeanShift();
protected:
void run(int);
};
CV_GpuMeanShift::CV_GpuMeanShift(): CvTest( "GPU-MeanShift", "MeanShift" ){}
void CV_GpuMeanShift::run(int)
{
int spatialRad = 30;
int colorRad = 30;
cv::Mat img = cv::imread(std::string(ts->get_data_path()) + "meanshift/cones.png");
cv::Mat img_template = cv::imread(std::string(ts->get_data_path()) + "meanshift/con_result.png");
if (img.empty() || img_template.empty())
{
ts->set_failed_test_info(CvTS::FAIL_MISSING_TEST_DATA);
return;
}
cv::Mat rgba;
cvtColor(img, rgba, CV_BGR2BGRA);
cv::gpu::GpuMat res;
cv::gpu::meanShiftFiltering_GPU( cv::gpu::GpuMat(rgba), res, spatialRad, colorRad );
if (res.type() != CV_8UC4)
{
ts->set_failed_test_info(CvTS::FAIL_INVALID_OUTPUT);
return;
}
cv::Mat result;
res.download(result);
uchar maxDiff = 0;
for (int j = 0; j < result.rows; ++j)
{
const uchar* res_line = result.ptr<uchar>(j);
const uchar* ref_line = img_template.ptr<uchar>(j);
for (int i = 0; i < result.cols; ++i)
{
for (int k = 0; k < 3; ++k)
{
const uchar& ch1 = res_line[result.channels()*i + k];
const uchar& ch2 = ref_line[img_template.channels()*i + k];
uchar diff = abs(ch1 - ch2);
if (maxDiff < diff)
maxDiff = diff;
}
}
}
if (maxDiff > 0)
ts->printf(CvTS::CONSOLE, "\nMeanShift maxDiff = %d\n", maxDiff);
ts->set_failed_test_info((maxDiff == 0) ? CvTS::OK : CvTS::FAIL_GENERIC);
}
CV_GpuMeanShift CV_GpuMeanShift_test;

28
tests/gpu/src/stereo_bp.cpp
View File

@ -58,22 +58,28 @@ CV_GpuStereoBP::CV_GpuStereoBP(): CvTest( "GPU-StereoBP", "StereoBP" ){}
void CV_GpuStereoBP::run(int )
{
cv::Mat img_l = cv::imread(std::string(ts->get_data_path()) + "stereobp/aloe-L.png");
cv::Mat img_r = cv::imread(std::string(ts->get_data_path()) + "stereobp/aloe-R.png");
cv::Mat img_template = cv::imread(std::string(ts->get_data_path()) + "stereobp/aloe-disp.png", 0);
cv::Mat img_l = cv::imread(std::string(ts->get_data_path()) + "stereobp/aloe-L.png");
cv::Mat img_r = cv::imread(std::string(ts->get_data_path()) + "stereobp/aloe-R.png");
cv::Mat img_template = cv::imread(std::string(ts->get_data_path()) + "stereobp/aloe-disp.png", 0);
cv::gpu::GpuMat disp;
cv::gpu::StereoBeliefPropagation bpm(64, 8, 2, 25, 0.1f, 15, 1, CV_16S);
if (img_l.empty() || img_r.empty() || img_template.empty())
{
ts->set_failed_test_info(CvTS::FAIL_MISSING_TEST_DATA);
return;
}
bpm(cv::gpu::GpuMat(img_l), cv::gpu::GpuMat(img_r), disp);
cv::gpu::GpuMat disp;
cv::gpu::StereoBeliefPropagation bpm(64, 8, 2, 25, 0.1f, 15, 1, CV_16S);
//cv::imwrite(std::string(ts->get_data_path()) + "stereobp/aloe-disp.png", disp);
bpm(cv::gpu::GpuMat(img_l), cv::gpu::GpuMat(img_r), disp);
disp.convertTo(disp, img_template.type());
//cv::imwrite(std::string(ts->get_data_path()) + "stereobp/aloe-disp.png", disp);
double norm = cv::norm(disp, img_template, cv::NORM_INF);
if (norm >= 0.5) std::cout << "StereoBP norm = " << norm << std::endl;
ts->set_failed_test_info((norm < 0.5) ? CvTS::OK : CvTS::FAIL_GENERIC);
disp.convertTo(disp, img_template.type());
double norm = cv::norm(disp, img_template, cv::NORM_INF);
if (norm >= 0.5) std::cout << "StereoBP norm = " << norm << std::endl;
ts->set_failed_test_info((norm < 0.5) ? CvTS::OK : CvTS::FAIL_GENERIC);
}