1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
/*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()));