Open Source Computer Vision Library https://opencv.org/
You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
 
 
 
 
 
 

176 lines
6.8 KiB

/*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, Multicoreware, Inc., all rights reserved.
// Copyright (C) 2010-2012, Advanced Micro Devices, Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// @Authors
// Nathan, liujun@multicorewareinc.com
//
// 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 the copyright holders 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 "test_precomp.hpp"
#include <iomanip>
using namespace cv;
using namespace cv::ocl;
using namespace testing;
using namespace std;
template <typename T>
static void blendLinearGold(const Mat &img1, const Mat &img2,
const Mat &weights1, const Mat &weights2,
Mat &result_gold)
{
CV_Assert(img1.size() == img2.size() && img1.type() == img2.type());
CV_Assert(weights1.size() == weights2.size() && weights1.size() == img1.size() &&
weights1.type() == CV_32FC1 && weights2.type() == CV_32FC1);
result_gold.create(img1.size(), img1.type());
int cn = img1.channels();
int step1 = img1.cols * img1.channels();
for (int y = 0; y < img1.rows; ++y)
{
const float * const weights1_row = weights1.ptr<float>(y);
const float * const weights2_row = weights2.ptr<float>(y);
const T * const img1_row = img1.ptr<T>(y);
const T * const img2_row = img2.ptr<T>(y);
T * const result_gold_row = result_gold.ptr<T>(y);
for (int x = 0; x < step1; ++x)
{
int x1 = x / cn;
float w1 = weights1_row[x1], w2 = weights2_row[x1];
result_gold_row[x] = saturate_cast<T>(((float)img1_row[x] * w1
+ (float)img2_row[x] * w2) / (w1 + w2 + 1e-5f));
}
}
}
PARAM_TEST_CASE(Blend, MatDepth, int, bool)
{
int depth, channels;
bool useRoi;
Mat src1, src2, weights1, weights2, dst;
Mat src1_roi, src2_roi, weights1_roi, weights2_roi, dst_roi;
oclMat gsrc1, gsrc2, gweights1, gweights2, gdst, gst;
oclMat gsrc1_roi, gsrc2_roi, gweights1_roi, gweights2_roi, gdst_roi;
virtual void SetUp()
{
depth = GET_PARAM(0);
channels = GET_PARAM(1);
useRoi = GET_PARAM(2);
}
void random_roi()
{
const int type = CV_MAKE_TYPE(depth, channels);
const double upValue = 256;
const double sumMinValue = 0.01; // we don't want to divide by "zero"
Size roiSize = randomSize(1, 20);
Border src1Border = randomBorder(0, useRoi ? MAX_VALUE : 0);
randomSubMat(src1, src1_roi, roiSize, src1Border, type, -upValue, upValue);
Border src2Border = randomBorder(0, useRoi ? MAX_VALUE : 0);
randomSubMat(src2, src2_roi, roiSize, src2Border, type, -upValue, upValue);
Border weights1Border = randomBorder(0, useRoi ? MAX_VALUE : 0);
randomSubMat(weights1, weights1_roi, roiSize, weights1Border, CV_32FC1, -upValue, upValue);
Border weights2Border = randomBorder(0, useRoi ? MAX_VALUE : 0);
randomSubMat(weights2, weights2_roi, roiSize, weights2Border, CV_32FC1, sumMinValue, upValue); // fill it as a (w1 + w12)
weights2_roi = weights2_roi - weights1_roi;
// check that weights2_roi is still a part of weights2 (not a new matrix)
CV_Assert(checkNorm(weights2_roi,
weights2(Rect(weights2Border.lef, weights2Border.top, roiSize.width, roiSize.height))) < 1e-6);
Border dstBorder = randomBorder(0, useRoi ? MAX_VALUE : 0);
randomSubMat(dst, dst_roi, roiSize, dstBorder, type, 5, 16);
generateOclMat(gsrc1, gsrc1_roi, src1, roiSize, src1Border);
generateOclMat(gsrc2, gsrc2_roi, src2, roiSize, src2Border);
generateOclMat(gweights1, gweights1_roi, weights1, roiSize, weights1Border);
generateOclMat(gweights2, gweights2_roi, weights2, roiSize, weights2Border);
generateOclMat(gdst, gdst_roi, dst, roiSize, dstBorder);
}
void Near(double eps = 0.0)
{
Mat whole, roi;
gdst.download(whole);
gdst_roi.download(roi);
EXPECT_MAT_NEAR(dst, whole, eps);
EXPECT_MAT_NEAR(dst_roi, roi, eps);
}
};
typedef void (*blendLinearFunc)(const cv::Mat &img1, const cv::Mat &img2, const cv::Mat &weights1, const cv::Mat &weights2, cv::Mat &result_gold);
OCL_TEST_P(Blend, Accuracy)
{
for (int i = 0; i < LOOP_TIMES; ++i)
{
random_roi();
cv::ocl::blendLinear(gsrc1_roi, gsrc2_roi, gweights1_roi, gweights2_roi, gdst_roi);
static blendLinearFunc funcs[] = {
blendLinearGold<uchar>,
blendLinearGold<schar>,
blendLinearGold<ushort>,
blendLinearGold<short>,
blendLinearGold<int>,
blendLinearGold<float>,
};
blendLinearFunc func = funcs[depth];
func(src1_roi, src2_roi, weights1_roi, weights2_roi, dst_roi);
Near(depth <= CV_32S ? 1.0 : 0.2);
}
}
INSTANTIATE_TEST_CASE_P(OCL_ImgProc, Blend,
Combine(testing::Values(CV_8U, CV_8S, CV_16U, CV_16S, CV_32S, CV_32F),
testing::Range(1, 5), Bool()));