opencv/modules/ocl/test/test_warp.cpp

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/*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.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2010-2012, Institute Of Software Chinese Academy Of Science, all rights reserved.
// Copyright (C) 2010-2012, Advanced Micro Devices, Inc., all rights reserved.
// Copyright (C) 2010-2012, Multicoreware, Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// @Authors
// Niko Li, newlife20080214@gmail.com
// Jia Haipeng, jiahaipeng95@gmail.com
// Shengen Yan, yanshengen@gmail.com
// Jiang Liyuan, lyuan001.good@163.com
// Rock Li, Rock.Li@amd.com
// Wu Zailong, bullet@yeah.net
// Xu Pang, pangxu010@163.com
// Sen Liu, swjtuls1987@126.com
//
// Redistribution and use in source and binary forms, with or without modification,
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// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
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// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
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// 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
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// 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;
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// and on any theory of liability, whether in contract, strict liability,
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//M*/
#include "test_precomp.hpp"
#ifdef HAVE_OPENCL
using namespace cv;
using namespace testing;
using namespace std;
static MatType noType = -1;
/////////////////////////////////////////////////////////////////////////////////////////////////
// warpAffine & warpPerspective
PARAM_TEST_CASE(WarpTestBase, MatType, Interpolation, bool, bool)
{
int type, interpolation;
Size dsize;
bool useRoi, mapInverse;
Mat src, dst_whole, src_roi, dst_roi;
ocl::oclMat gsrc_whole, gsrc_roi, gdst_whole, gdst_roi;
virtual void SetUp()
{
type = GET_PARAM(0);
interpolation = GET_PARAM(1);
mapInverse = GET_PARAM(2);
useRoi = GET_PARAM(3);
if (mapInverse)
interpolation |= WARP_INVERSE_MAP;
}
void random_roi()
{
dsize = randomSize(1, MAX_VALUE);
Size roiSize = randomSize(1, MAX_VALUE);
Border srcBorder = randomBorder(0, useRoi ? MAX_VALUE : 0);
randomSubMat(src, src_roi, roiSize, srcBorder, type, -MAX_VALUE, MAX_VALUE);
Border dstBorder = randomBorder(0, useRoi ? MAX_VALUE : 0);
randomSubMat(dst_whole, dst_roi, dsize, dstBorder, type, -MAX_VALUE, MAX_VALUE);
generateOclMat(gsrc_whole, gsrc_roi, src, roiSize, srcBorder);
generateOclMat(gdst_whole, gdst_roi, dst_whole, dsize, dstBorder);
}
void Near(double threshold = 0.0)
{
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Mat whole, roi;
gdst_whole.download(whole);
gdst_roi.download(roi);
EXPECT_MAT_NEAR(dst_whole, whole, threshold);
EXPECT_MAT_NEAR(dst_roi, roi, threshold);
}
};
/////warpAffine
typedef WarpTestBase WarpAffine;
OCL_TEST_P(WarpAffine, Mat)
{
for (int j = 0; j < LOOP_TIMES; j++)
{
random_roi();
Mat M = getRotationMatrix2D(Point2f(src_roi.cols / 2.0f, src_roi.rows / 2.0f),
rng.uniform(-180.f, 180.f), rng.uniform(0.4f, 2.0f));
warpAffine(src_roi, dst_roi, M, dsize, interpolation);
ocl::warpAffine(gsrc_roi, gdst_roi, M, dsize, interpolation);
Near(1.0);
}
}
// warpPerspective
typedef WarpTestBase WarpPerspective;
OCL_TEST_P(WarpPerspective, Mat)
{
for (int j = 0; j < LOOP_TIMES; j++)
{
random_roi();
float cols = static_cast<float>(src_roi.cols), rows = static_cast<float>(src_roi.rows);
float cols2 = cols / 2.0f, rows2 = rows / 2.0f;
Point2f sp[] = { Point2f(0.0f, 0.0f), Point2f(cols, 0.0f), Point2f(0.0f, rows), Point2f(cols, rows) };
Point2f dp[] = { Point2f(rng.uniform(0.0f, cols2), rng.uniform(0.0f, rows2)),
Point2f(rng.uniform(cols2, cols), rng.uniform(0.0f, rows2)),
Point2f(rng.uniform(0.0f, cols2), rng.uniform(rows2, rows)),
Point2f(rng.uniform(cols2, cols), rng.uniform(rows2, rows)) };
Mat M = getPerspectiveTransform(sp, dp);
warpPerspective(src_roi, dst_roi, M, dsize, interpolation);
ocl::warpPerspective(gsrc_roi, gdst_roi, M, dsize, interpolation);
Near(1.0);
}
}
// buildWarpPerspectiveMaps
PARAM_TEST_CASE(BuildWarpPerspectiveMaps, bool, bool)
{
bool useRoi, mapInverse;
Size dsize;
Mat xmap_whole, ymap_whole, xmap_roi, ymap_roi;
ocl::oclMat gxmap_whole, gymap_whole, gxmap_roi, gymap_roi;
void SetUp()
{
mapInverse = GET_PARAM(0);
useRoi = GET_PARAM(1);
}
void random_roi()
{
dsize = randomSize(1, MAX_VALUE);
Border xmapBorder = randomBorder(0, useRoi ? MAX_VALUE : 0);
randomSubMat(xmap_whole, xmap_roi, dsize, xmapBorder, CV_32FC1, -MAX_VALUE, MAX_VALUE);
Border ymapBorder = randomBorder(0, useRoi ? MAX_VALUE : 0);
randomSubMat(ymap_whole, ymap_roi, dsize, ymapBorder, CV_32FC1, -MAX_VALUE, MAX_VALUE);
generateOclMat(gxmap_whole, gxmap_roi, xmap_whole, dsize, xmapBorder);
generateOclMat(gymap_whole, gymap_roi, ymap_whole, dsize, ymapBorder);
}
void Near(double threshold = 0.0)
{
Mat whole, roi;
gxmap_whole.download(whole);
gxmap_roi.download(roi);
EXPECT_MAT_NEAR(xmap_whole, whole, threshold);
EXPECT_MAT_NEAR(xmap_roi, roi, threshold);
}
void Near1(double threshold = 0.0)
{
Mat whole, roi;
gymap_whole.download(whole);
gymap_roi.download(roi);
EXPECT_MAT_NEAR(ymap_whole, whole, threshold);
EXPECT_MAT_NEAR(ymap_roi, roi, threshold);
}
};
static void buildWarpPerspectiveMaps(const Mat &M, bool inverse, Size dsize, Mat &xmap, Mat &ymap)
{
CV_Assert(M.rows == 3 && M.cols == 3);
CV_Assert(dsize.area() > 0);
xmap.create(dsize, CV_32FC1);
ymap.create(dsize, CV_32FC1);
float coeffs[3 * 3];
Mat coeffsMat(3, 3, CV_32F, (void *)coeffs);
if (inverse)
M.convertTo(coeffsMat, coeffsMat.type());
else
{
cv::Mat iM;
invert(M, iM);
iM.convertTo(coeffsMat, coeffsMat.type());
}
for (int y = 0; y < dsize.height; ++y)
{
float * const xmap_ptr = xmap.ptr<float>(y);
float * const ymap_ptr = ymap.ptr<float>(y);
for (int x = 0; x < dsize.width; ++x)
{
float coeff = 1.0f / (x * coeffs[6] + y * coeffs[7] + coeffs[8]);
xmap_ptr[x] = (x * coeffs[0] + y * coeffs[1] + coeffs[2]) * coeff;
ymap_ptr[x] = (x * coeffs[3] + y * coeffs[4] + coeffs[5]) * coeff;
}
}
}
OCL_TEST_P(BuildWarpPerspectiveMaps, Mat)
{
for (int j = 0; j < LOOP_TIMES; j++)
{
random_roi();
float cols = static_cast<float>(MAX_VALUE), rows = static_cast<float>(MAX_VALUE);
float cols2 = cols / 2.0f, rows2 = rows / 2.0f;
Point2f sp[] = { Point2f(0.0f, 0.0f), Point2f(cols, 0.0f), Point2f(0.0f, rows), Point2f(cols, rows) };
Point2f dp[] = { Point2f(rng.uniform(0.0f, cols2), rng.uniform(0.0f, rows2)),
Point2f(rng.uniform(cols2, cols), rng.uniform(0.0f, rows2)),
Point2f(rng.uniform(0.0f, cols2), rng.uniform(rows2, rows)),
Point2f(rng.uniform(cols2, cols), rng.uniform(rows2, rows)) };
Mat M = getPerspectiveTransform(sp, dp);
buildWarpPerspectiveMaps(M, mapInverse, dsize, xmap_roi, ymap_roi);
ocl::buildWarpPerspectiveMaps(M, mapInverse, dsize, gxmap_roi, gymap_roi);
Near(5e-3);
Near1(5e-3);
}
}
/////////////////////////////////////////////////////////////////////////////////////////////////
// remap
PARAM_TEST_CASE(Remap, MatDepth, Channels, pair<MatType, MatType>, Border, bool)
{
int srcType, map1Type, map2Type;
int borderType;
bool useRoi;
Scalar val;
Mat src, src_roi;
Mat dst, dst_roi;
Mat map1, map1_roi;
Mat map2, map2_roi;
// ocl mat with roi
ocl::oclMat gsrc, gsrc_roi;
ocl::oclMat gdst, gdst_roi;
ocl::oclMat gmap1, gmap1_roi;
ocl::oclMat gmap2, gmap2_roi;
virtual void SetUp()
{
srcType = CV_MAKE_TYPE(GET_PARAM(0), GET_PARAM(1));
map1Type = GET_PARAM(2).first;
map2Type = GET_PARAM(2).second;
borderType = GET_PARAM(3);
useRoi = GET_PARAM(4);
}
void random_roi()
{
val = randomScalar(-MAX_VALUE, MAX_VALUE);
Size srcROISize = randomSize(1, MAX_VALUE);
Size dstROISize = randomSize(1, MAX_VALUE);
Border srcBorder = randomBorder(0, useRoi ? MAX_VALUE : 0);
randomSubMat(src, src_roi, srcROISize, srcBorder, srcType, 5, 256);
Border dstBorder = randomBorder(0, useRoi ? MAX_VALUE : 0);
randomSubMat(dst, dst_roi, dstROISize, dstBorder, srcType, -MAX_VALUE, MAX_VALUE);
int mapMaxValue = MAX_VALUE << 2;
Border map1Border = randomBorder(0, useRoi ? MAX_VALUE : 0);
randomSubMat(map1, map1_roi, dstROISize, map1Border, map1Type, -mapMaxValue, mapMaxValue);
Border map2Border = randomBorder(0, useRoi ? MAX_VALUE : 0);
if (map2Type != noType)
{
int mapMinValue = -mapMaxValue;
if (map2Type == CV_16UC1 || map2Type == CV_16SC1)
mapMinValue = 0, mapMaxValue = INTER_TAB_SIZE2;
randomSubMat(map2, map2_roi, dstROISize, map2Border, map2Type, mapMinValue, mapMaxValue);
}
generateOclMat(gsrc, gsrc_roi, src, srcROISize, srcBorder);
generateOclMat(gdst, gdst_roi, dst, dstROISize, dstBorder);
generateOclMat(gmap1, gmap1_roi, map1, dstROISize, map1Border);
if (noType != map2Type)
generateOclMat(gmap2, gmap2_roi, map2, dstROISize, map2Border);
}
void Near(double threshold = 0.0)
{
Mat whole, roi;
gdst.download(whole);
gdst_roi.download(roi);
EXPECT_MAT_NEAR(dst, whole, threshold);
EXPECT_MAT_NEAR(dst_roi, roi, threshold);
}
};
typedef Remap Remap_INTER_NEAREST;
OCL_TEST_P(Remap_INTER_NEAREST, Mat)
{
for (int j = 0; j < LOOP_TIMES; j++)
{
random_roi();
remap(src_roi, dst_roi, map1_roi, map2_roi, INTER_NEAREST, borderType, val);
ocl::remap(gsrc_roi, gdst_roi, gmap1_roi, gmap2_roi, INTER_NEAREST, borderType, val);
Near(1.0);
}
}
typedef Remap Remap_INTER_LINEAR;
OCL_TEST_P(Remap_INTER_LINEAR, Mat)
{
for (int j = 0; j < LOOP_TIMES; j++)
{
random_roi();
cv::remap(src_roi, dst_roi, map1_roi, map2_roi, INTER_LINEAR, borderType, val);
ocl::remap(gsrc_roi, gdst_roi, gmap1_roi, gmap2_roi, INTER_LINEAR, borderType, val);
Near(2.0);
}
}
/////////////////////////////////////////////////////////////////////////////////////////////////
// resize
PARAM_TEST_CASE(Resize, MatType, double, double, Interpolation, bool)
{
int type, interpolation;
double fx, fy;
bool useRoi;
Mat src, dst_whole, src_roi, dst_roi;
ocl::oclMat gsrc_whole, gsrc_roi, gdst_whole, gdst_roi;
virtual void SetUp()
{
type = GET_PARAM(0);
fx = GET_PARAM(1);
fy = GET_PARAM(2);
interpolation = GET_PARAM(3);
useRoi = GET_PARAM(4);
}
void random_roi()
{
CV_Assert(fx > 0 && fy > 0);
Size srcRoiSize = randomSize(1, MAX_VALUE), dstRoiSize;
dstRoiSize.width = cvRound(srcRoiSize.width * fx);
dstRoiSize.height = cvRound(srcRoiSize.height * fy);
if (dstRoiSize.area() == 0)
{
random_roi();
return;
}
Border srcBorder = randomBorder(0, useRoi ? MAX_VALUE : 0);
randomSubMat(src, src_roi, srcRoiSize, srcBorder, type, -MAX_VALUE, MAX_VALUE);
Border dstBorder = randomBorder(0, useRoi ? MAX_VALUE : 0);
randomSubMat(dst_whole, dst_roi, dstRoiSize, dstBorder, type, -MAX_VALUE, MAX_VALUE);
generateOclMat(gsrc_whole, gsrc_roi, src, srcRoiSize, srcBorder);
generateOclMat(gdst_whole, gdst_roi, dst_whole, dstRoiSize, dstBorder);
}
void Near(double threshold = 0.0)
{
Mat whole, roi;
gdst_whole.download(whole);
gdst_roi.download(roi);
EXPECT_MAT_NEAR(dst_whole, whole, threshold);
EXPECT_MAT_NEAR(dst_roi, roi, threshold);
}
};
OCL_TEST_P(Resize, Mat)
{
for (int j = 0; j < LOOP_TIMES; j++)
{
random_roi();
cv::resize(src_roi, dst_roi, Size(), fx, fy, interpolation);
ocl::resize(gsrc_roi, gdst_roi, Size(), fx, fy, interpolation);
Near(1.0);
}
}
/////////////////////////////////////////////////////////////////////////////////////
INSTANTIATE_TEST_CASE_P(ImgprocWarp, WarpAffine, Combine(
Values(CV_8UC1, CV_8UC3, CV_8UC4, CV_32FC1, CV_32FC3, CV_32FC4),
Values((Interpolation)INTER_NEAREST, (Interpolation)INTER_LINEAR, (Interpolation)INTER_CUBIC),
Bool(),
Bool()));
INSTANTIATE_TEST_CASE_P(ImgprocWarp, WarpPerspective, Combine(
Values(CV_8UC1, CV_8UC3, CV_8UC4, CV_32FC1, CV_32FC3, CV_32FC4),
Values((Interpolation)INTER_NEAREST, (Interpolation)INTER_LINEAR, (Interpolation)INTER_CUBIC),
Bool(),
Bool()));
INSTANTIATE_TEST_CASE_P(ImgprocWarp, BuildWarpPerspectiveMaps, Combine(Bool(), Bool()));
INSTANTIATE_TEST_CASE_P(ImgprocWarp, Remap_INTER_LINEAR, Combine(
Values(CV_8U, CV_16U, CV_16S, CV_32F, CV_64F),
Values(1, 2, 3, 4),
Values(pair<MatType, MatType>((MatType)CV_32FC1, (MatType)CV_32FC1),
pair<MatType, MatType>((MatType)CV_16SC2, (MatType)CV_16UC1),
pair<MatType, MatType>((MatType)CV_32FC2, noType)),
Values((Border)BORDER_CONSTANT,
(Border)BORDER_REPLICATE,
(Border)BORDER_WRAP,
(Border)BORDER_REFLECT,
(Border)BORDER_REFLECT_101),
Bool()));
INSTANTIATE_TEST_CASE_P(ImgprocWarp, Remap_INTER_NEAREST, Combine(
Values(CV_8U, CV_16U, CV_16S, CV_32F, CV_64F),
Values(1, 2, 3, 4),
Values(pair<MatType, MatType>((MatType)CV_32FC1, (MatType)CV_32FC1),
pair<MatType, MatType>((MatType)CV_32FC2, noType),
pair<MatType, MatType>((MatType)CV_16SC2, (MatType)CV_16UC1),
pair<MatType, MatType>((MatType)CV_16SC2, noType)),
Values((Border)BORDER_CONSTANT,
(Border)BORDER_REPLICATE,
(Border)BORDER_WRAP,
(Border)BORDER_REFLECT,
(Border)BORDER_REFLECT_101),
Bool()));
INSTANTIATE_TEST_CASE_P(ImgprocWarp, Resize, Combine(
Values(CV_8UC1, CV_8UC3, CV_8UC4, CV_32FC1, CV_32FC3, CV_32FC4),
Values(0.5, 1.5, 2.0),
Values(0.5, 1.5, 2.0),
Values((Interpolation)INTER_NEAREST, (Interpolation)INTER_LINEAR),
Bool()));
#endif // HAVE_OPENCL