1 /*M///////////////////////////////////////////////////////////////////////////////////////
2 //
3 //  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
4 //
5 //  By downloading, copying, installing or using the software you agree to this license.
6 //  If you do not agree to this license, do not download, install,
7 //  copy or use the software.
8 //
9 //
10 //                           License Agreement
11 //                For Open Source Computer Vision Library
12 //
13 // Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
14 // Copyright (C) 2009, Willow Garage Inc., all rights reserved.
15 // Third party copyrights are property of their respective owners.
16 //
17 // Redistribution and use in source and binary forms, with or without modification,
18 // are permitted provided that the following conditions are met:
19 //
20 //   * Redistribution's of source code must retain the above copyright notice,
21 //     this list of conditions and the following disclaimer.
22 //
23 //   * Redistribution's in binary form must reproduce the above copyright notice,
24 //     this list of conditions and the following disclaimer in the documentation
25 //     and/or other materials provided with the distribution.
26 //
27 //   * The name of the copyright holders may not be used to endorse or promote products
28 //     derived from this software without specific prior written permission.
29 //
30 // This software is provided by the copyright holders and contributors "as is" and
31 // any express or implied warranties, including, but not limited to, the implied
32 // warranties of merchantability and fitness for a particular purpose are disclaimed.
33 // In no event shall the Intel Corporation or contributors be liable for any direct,
34 // indirect, incidental, special, exemplary, or consequential damages
35 // (including, but not limited to, procurement of substitute goods or services;
36 // loss of use, data, or profits; or business interruption) however caused
37 // and on any theory of liability, whether in contract, strict liability,
38 // or tort (including negligence or otherwise) arising in any way out of
39 // the use of this software, even if advised of the possibility of such damage.
40 //
41 //M*/
42 
43 #include "perf_precomp.hpp"
44 
45 namespace opencv_test { namespace {
46 
47 DEF_PARAM_TEST_1(Image, string);
48 
49 struct GreedyLabeling
50 {
51     struct dot
52     {
53         int x;
54         int y;
55 
makeopencv_test::__anon7316d0e30111::GreedyLabeling::dot56         static dot make(int i, int j)
57         {
58             dot d; d.x = i; d.y = j;
59             return d;
60         }
61     };
62 
63     struct InInterval
64     {
InIntervalopencv_test::__anon7316d0e30111::GreedyLabeling::InInterval65         InInterval(const int& _lo, const int& _hi) : lo(-_lo), hi(_hi) {}
66         const int lo, hi;
67 
operator ()opencv_test::__anon7316d0e30111::GreedyLabeling::InInterval68         bool operator() (const unsigned char a, const unsigned char b) const
69         {
70             int d = a - b;
71             return lo <= d && d <= hi;
72         }
73 
74     private:
75         InInterval& operator=(const InInterval&);
76 
77 
78     };
79 
GreedyLabelingopencv_test::__anon7316d0e30111::GreedyLabeling80     GreedyLabeling(cv::Mat img)
81     : image(img), _labels(image.size(), CV_32SC1, cv::Scalar::all(-1)) {stack = new dot[image.cols * image.rows];}
82 
~GreedyLabelingopencv_test::__anon7316d0e30111::GreedyLabeling83     ~GreedyLabeling(){delete[] stack;}
84 
operator ()opencv_test::__anon7316d0e30111::GreedyLabeling85     void operator() (cv::Mat labels) const
86     {
87         labels.setTo(cv::Scalar::all(-1));
88         InInterval inInt(0, 2);
89         int cc = -1;
90 
91         int* dist_labels = (int*)labels.data;
92         int pitch = static_cast<int>(labels.step1());
93 
94         unsigned char* source = (unsigned char*)image.data;
95         int width = image.cols;
96         int height = image.rows;
97 
98         for (int j = 0; j < image.rows; ++j)
99             for (int i = 0; i < image.cols; ++i)
100             {
101                 if (dist_labels[j * pitch + i] != -1) continue;
102 
103                 dot* top = stack;
104                 dot p = dot::make(i, j);
105                 cc++;
106 
107                 dist_labels[j * pitch + i] = cc;
108 
109                 while (top >= stack)
110                 {
111                     int*  dl = &dist_labels[p.y * pitch + p.x];
112                     unsigned char* sp = &source[p.y * image.step1() + p.x];
113 
114                     dl[0] = cc;
115 
116                     //right
117                     if( p.x < (width - 1) && dl[ +1] == -1 && inInt(sp[0], sp[+1]))
118                         *top++ = dot::make(p.x + 1, p.y);
119 
120                     //left
121                     if( p.x > 0 && dl[-1] == -1 && inInt(sp[0], sp[-1]))
122                         *top++ = dot::make(p.x - 1, p.y);
123 
124                     //bottom
125                     if( p.y < (height - 1) && dl[+pitch] == -1 && inInt(sp[0], sp[+image.step1()]))
126                         *top++ = dot::make(p.x, p.y + 1);
127 
128                     //top
129                     if( p.y > 0 && dl[-pitch] == -1 && inInt(sp[0], sp[-static_cast<int>(image.step1())]))
130                         *top++ = dot::make(p.x, p.y - 1);
131 
132                     p = *--top;
133                 }
134             }
135     }
136 
137     cv::Mat image;
138     cv::Mat _labels;
139     dot* stack;
140 };
141 
142 PERF_TEST_P(Image, DISABLED_Labeling_ConnectivityMask,
143             Values<string>("gpu/labeling/aloe-disp.png"))
144 {
145     declare.time(1.0);
146 
147     const cv::Mat image = readImage(GetParam(), cv::IMREAD_GRAYSCALE);
148     ASSERT_FALSE(image.empty());
149 
150     if (PERF_RUN_CUDA())
151     {
152         cv::cuda::GpuMat d_image(image);
153         cv::cuda::GpuMat mask;
154 
155         TEST_CYCLE() cv::cuda::connectivityMask(d_image, mask, cv::Scalar::all(0), cv::Scalar::all(2));
156 
157         CUDA_SANITY_CHECK(mask);
158     }
159     else
160     {
161         FAIL_NO_CPU();
162     }
163 }
164 
165 PERF_TEST_P(Image, DISABLED_Labeling_ConnectedComponents,
166             Values<string>("gpu/labeling/aloe-disp.png"))
167 {
168     declare.time(1.0);
169 
170     const cv::Mat image = readImage(GetParam(), cv::IMREAD_GRAYSCALE);
171     ASSERT_FALSE(image.empty());
172 
173     if (PERF_RUN_CUDA())
174     {
175         cv::cuda::GpuMat d_mask;
176         cv::cuda::connectivityMask(cv::cuda::GpuMat(image), d_mask, cv::Scalar::all(0), cv::Scalar::all(2));
177 
178         cv::cuda::GpuMat components;
179 
180         TEST_CYCLE() cv::cuda::labelComponents(d_mask, components);
181 
182         CUDA_SANITY_CHECK(components);
183     }
184     else
185     {
186         GreedyLabeling host(image);
187 
188         TEST_CYCLE() host(host._labels);
189 
190         cv::Mat components = host._labels;
191         CPU_SANITY_CHECK(components);
192     }
193 }
194 
195 }} // namespace
196