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 // Copyright (C) 2013, OpenCV Foundation, all rights reserved. 16 // Third party copyrights are property of their respective owners. 17 // 18 // Redistribution and use in source and binary forms, with or without modification, 19 // are permitted provided that the following conditions are met: 20 // 21 // * Redistribution's of source code must retain the above copyright notice, 22 // this list of conditions and the following disclaimer. 23 // 24 // * Redistribution's in binary form must reproduce the above copyright notice, 25 // this list of conditions and the following disclaimer in the documentation 26 // and/or other materials provided with the distribution. 27 // 28 // * The name of the copyright holders may not be used to endorse or promote products 29 // derived from this software without specific prior written permission. 30 // 31 // This software is provided by the copyright holders and contributors "as is" and 32 // any express or implied warranties, including, but not limited to, the implied 33 // warranties of merchantability and fitness for a particular purpose are disclaimed. 34 // In no event shall the Intel Corporation or contributors be liable for any direct, 35 // indirect, incidental, special, exemplary, or consequential damages 36 // (including, but not limited to, procurement of substitute goods or services; 37 // loss of use, data, or profits; or business interruption) however caused 38 // and on any theory of liability, whether in contract, strict liability, 39 // or tort (including negligence or otherwise) arising in any way out of 40 // the use of this software, even if advised of the possibility of such damage. 41 // 42 //M*/ 43 44 #include "test_precomp.hpp" 45 46 using namespace cv; 47 using namespace cv::cuda; 48 using namespace cv::cudev; 49 using namespace cvtest; 50 51 TEST(Sum, GpuMat) 52 { 53 const Size size = randomSize(100, 400); 54 55 Mat src = randomMat(size, CV_8UC1); 56 57 GpuMat_<uchar> d_src(src); 58 59 GpuMat_<float> dst = sum_(d_src); 60 float res; 61 dst.download(_OutputArray(&res, 1)); 62 63 Scalar dst_gold = cv::sum(src); 64 65 ASSERT_FLOAT_EQ(static_cast<float>(dst_gold[0]), res); 66 } 67 68 TEST(Sum, Expr) 69 { 70 const Size size = randomSize(100, 400); 71 72 Mat src1 = randomMat(size, CV_32FC1, 0, 1); 73 Mat src2 = randomMat(size, CV_32FC1, 0, 1); 74 75 GpuMat_<float> d_src1(src1), d_src2(src2); 76 77 GpuMat_<float> dst = sum_(abs_(d_src1 - d_src2)); 78 float res; 79 dst.download(_OutputArray(&res, 1)); 80 81 Scalar dst_gold = cv::norm(src1, src2, NORM_L1); 82 83 ASSERT_FLOAT_EQ(static_cast<float>(dst_gold[0]), res); 84 } 85 86 TEST(MinVal, GpuMat) 87 { 88 const Size size = randomSize(100, 400); 89 90 Mat src = randomMat(size, CV_8UC1); 91 92 GpuMat_<uchar> d_src(src); 93 94 GpuMat_<float> dst = minVal_(d_src); 95 float res; 96 dst.download(_OutputArray(&res, 1)); 97 98 double res_gold; 99 cv::minMaxLoc(src, &res_gold, 0); 100 101 ASSERT_FLOAT_EQ(static_cast<float>(res_gold), res); 102 } 103 104 TEST(MaxVal, Expr) 105 { 106 const Size size = randomSize(100, 400); 107 108 Mat src1 = randomMat(size, CV_32SC1); 109 Mat src2 = randomMat(size, CV_32SC1); 110 111 GpuMat_<int> d_src1(src1), d_src2(src2); 112 113 GpuMat_<float> dst = maxVal_(abs_(d_src1 - d_src2)); 114 float res; 115 dst.download(_OutputArray(&res, 1)); 116 117 double res_gold = cv::norm(src1, src2, NORM_INF); 118 119 ASSERT_FLOAT_EQ(static_cast<float>(res_gold), res); 120 } 121 122 TEST(MinMaxVal, GpuMat) 123 { 124 const Size size = randomSize(100, 400); 125 126 Mat src = randomMat(size, CV_8UC1); 127 128 GpuMat_<uchar> d_src(src); 129 130 GpuMat_<float> dst = minMaxVal_(d_src); 131 float res[2]; 132 dst.download(Mat(1, 2, CV_32FC1, res)); 133 134 double res_gold[2]; 135 cv::minMaxLoc(src, &res_gold[0], &res_gold[1]); 136 137 ASSERT_FLOAT_EQ(static_cast<float>(res_gold[0]), res[0]); 138 ASSERT_FLOAT_EQ(static_cast<float>(res_gold[1]), res[1]); 139 } 140 141 TEST(NonZeroCount, Accuracy) 142 { 143 const Size size = randomSize(100, 400); 144 145 Mat src = randomMat(size, CV_8UC1, 0, 5); 146 147 GpuMat_<uchar> d_src(src); 148 149 GpuMat_<int> dst1 = countNonZero_(d_src); 150 GpuMat_<int> dst2 = sum_(cvt_<int>(d_src) != 0); 151 152 EXPECT_MAT_NEAR(dst1, dst2, 0.0); 153 } 154 155 TEST(ReduceToRow, Sum) 156 { 157 const Size size = randomSize(100, 400); 158 159 Mat src = randomMat(size, CV_8UC1); 160 161 GpuMat_<uchar> d_src(src); 162 163 GpuMat_<int> dst = reduceToRow_<Sum<int> >(d_src); 164 165 Mat dst_gold; 166 cv::reduce(src, dst_gold, 0, REDUCE_SUM, CV_32S); 167 168 EXPECT_MAT_NEAR(dst_gold, dst, 0.0); 169 } 170 171 TEST(ReduceToRow, Avg) 172 { 173 const Size size = randomSize(100, 400); 174 175 Mat src = randomMat(size, CV_8UC1); 176 177 GpuMat_<uchar> d_src(src); 178 179 GpuMat_<float> dst = reduceToRow_<Avg<float> >(d_src); 180 181 Mat dst_gold; 182 cv::reduce(src, dst_gold, 0, REDUCE_AVG, CV_32F); 183 184 EXPECT_MAT_NEAR(dst_gold, dst, 1e-4); 185 } 186 187 TEST(ReduceToRow, Min) 188 { 189 const Size size = randomSize(100, 400); 190 191 Mat src = randomMat(size, CV_8UC1); 192 193 GpuMat_<uchar> d_src(src); 194 195 GpuMat_<uchar> dst = reduceToRow_<Min<uchar> >(d_src); 196 197 Mat dst_gold; 198 cv::reduce(src, dst_gold, 0, REDUCE_MIN); 199 200 EXPECT_MAT_NEAR(dst_gold, dst, 0.0); 201 } 202 203 TEST(ReduceToRow, Max) 204 { 205 const Size size = randomSize(100, 400); 206 207 Mat src = randomMat(size, CV_8UC1); 208 209 GpuMat_<uchar> d_src(src); 210 211 GpuMat_<uchar> dst = reduceToRow_<Max<uchar> >(d_src); 212 213 Mat dst_gold; 214 cv::reduce(src, dst_gold, 0, REDUCE_MAX); 215 216 EXPECT_MAT_NEAR(dst_gold, dst, 0.0); 217 } 218 219 TEST(ReduceToColumn, Sum) 220 { 221 const Size size = randomSize(100, 400); 222 223 Mat src = randomMat(size, CV_8UC1); 224 225 GpuMat_<uchar> d_src(src); 226 227 GpuMat_<int> dst = reduceToColumn_<Sum<int> >(d_src); 228 229 Mat dst_gold; 230 cv::reduce(src, dst_gold, 1, REDUCE_SUM, CV_32S); 231 dst_gold.cols = dst_gold.rows; 232 dst_gold.rows = 1; 233 dst_gold.step = dst_gold.cols * dst_gold.elemSize(); 234 235 EXPECT_MAT_NEAR(dst_gold, dst, 0.0); 236 } 237 238 TEST(ReduceToColumn, Avg) 239 { 240 const Size size = randomSize(100, 400); 241 242 Mat src = randomMat(size, CV_8UC1); 243 244 GpuMat_<uchar> d_src(src); 245 246 GpuMat_<float> dst = reduceToColumn_<Avg<float> >(d_src); 247 248 Mat dst_gold; 249 cv::reduce(src, dst_gold, 1, REDUCE_AVG, CV_32F); 250 dst_gold.cols = dst_gold.rows; 251 dst_gold.rows = 1; 252 dst_gold.step = dst_gold.cols * dst_gold.elemSize(); 253 254 EXPECT_MAT_NEAR(dst_gold, dst, 1e-4); 255 } 256 257 TEST(ReduceToColumn, Min) 258 { 259 const Size size = randomSize(100, 400); 260 261 Mat src = randomMat(size, CV_8UC1); 262 263 GpuMat_<uchar> d_src(src); 264 265 GpuMat_<uchar> dst = reduceToColumn_<Min<uchar> >(d_src); 266 267 Mat dst_gold; 268 cv::reduce(src, dst_gold, 1, REDUCE_MIN); 269 dst_gold.cols = dst_gold.rows; 270 dst_gold.rows = 1; 271 dst_gold.step = dst_gold.cols * dst_gold.elemSize(); 272 273 EXPECT_MAT_NEAR(dst_gold, dst, 0.0); 274 } 275 276 TEST(ReduceToColumn, Max) 277 { 278 const Size size = randomSize(100, 400); 279 280 Mat src = randomMat(size, CV_8UC1); 281 282 GpuMat_<uchar> d_src(src); 283 284 GpuMat_<uchar> dst = reduceToColumn_<Max<uchar> >(d_src); 285 286 Mat dst_gold; 287 cv::reduce(src, dst_gold, 1, REDUCE_MAX); 288 dst_gold.cols = dst_gold.rows; 289 dst_gold.rows = 1; 290 dst_gold.step = dst_gold.cols * dst_gold.elemSize(); 291 292 EXPECT_MAT_NEAR(dst_gold, dst, 0.0); 293 } 294 295 static void calcHistGold(const cv::Mat& src, cv::Mat& hist) 296 { 297 hist.create(1, 256, CV_32SC1); 298 hist.setTo(cv::Scalar::all(0)); 299 300 int* hist_row = hist.ptr<int>(); 301 for (int y = 0; y < src.rows; ++y) 302 { 303 const uchar* src_row = src.ptr(y); 304 305 for (int x = 0; x < src.cols; ++x) 306 ++hist_row[src_row[x]]; 307 } 308 } 309 310 TEST(Histogram, GpuMat) 311 { 312 const Size size = randomSize(100, 400); 313 314 Mat src = randomMat(size, CV_8UC1); 315 316 GpuMat_<uchar> d_src(src); 317 318 GpuMat_<int> dst = histogram_<256>(d_src); 319 320 Mat dst_gold; 321 calcHistGold(src, dst_gold); 322 323 EXPECT_MAT_NEAR(dst_gold, dst, 0.0); 324 } 325
