/*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) 2000-2008, Intel Corporation, all rights reserved. // Copyright (C) 2009, Willow Garage Inc., all rights reserved. // Third party copyrights are property of their respective owners. // // 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 #include using namespace std; using namespace cv; class CV_GrabcutTest : public cvtest::BaseTest { public: CV_GrabcutTest(); ~CV_GrabcutTest(); protected: bool verify(const Mat& mask, const Mat& exp); void run(int); }; CV_GrabcutTest::CV_GrabcutTest() {} CV_GrabcutTest::~CV_GrabcutTest() {} bool CV_GrabcutTest::verify(const Mat& mask, const Mat& exp) { const float maxDiffRatio = 0.005f; int expArea = countNonZero( exp ); int nonIntersectArea = countNonZero( mask != exp ); float curRatio = (float)nonIntersectArea / (float)expArea; ts->printf( cvtest::TS::LOG, "nonIntersectArea/expArea = %f\n", curRatio ); return curRatio < maxDiffRatio; } void CV_GrabcutTest::run( int /* start_from */) { cvtest::DefaultRngAuto defRng; Mat img = imread(string(ts->get_data_path()) + "shared/airplane.png"); Mat mask_prob = imread(string(ts->get_data_path()) + "grabcut/mask_prob.png", 0); Mat exp_mask1 = imread(string(ts->get_data_path()) + "grabcut/exp_mask1.png", 0); Mat exp_mask2 = imread(string(ts->get_data_path()) + "grabcut/exp_mask2.png", 0); if (img.empty() || (!mask_prob.empty() && img.size() != mask_prob.size()) || (!exp_mask1.empty() && img.size() != exp_mask1.size()) || (!exp_mask2.empty() && img.size() != exp_mask2.size()) ) { ts->set_failed_test_info(cvtest::TS::FAIL_MISSING_TEST_DATA); return; } Rect rect(Point(24, 126), Point(483, 294)); Mat exp_bgdModel, exp_fgdModel; Mat mask; mask = Scalar(0); Mat bgdModel, fgdModel; grabCut( img, mask, rect, bgdModel, fgdModel, 0, GC_INIT_WITH_RECT ); grabCut( img, mask, rect, bgdModel, fgdModel, 2, GC_EVAL ); // Multiply images by 255 for more visuality of test data. if( mask_prob.empty() ) { mask.copyTo( mask_prob ); imwrite(string(ts->get_data_path()) + "grabcut/mask_prob.png", mask_prob); } if( exp_mask1.empty() ) { exp_mask1 = (mask & 1) * 255; imwrite(string(ts->get_data_path()) + "grabcut/exp_mask1.png", exp_mask1); } if (!verify((mask & 1) * 255, exp_mask1)) { ts->set_failed_test_info(cvtest::TS::FAIL_MISMATCH); return; } mask = mask_prob; bgdModel.release(); fgdModel.release(); rect = Rect(); grabCut( img, mask, rect, bgdModel, fgdModel, 0, GC_INIT_WITH_MASK ); grabCut( img, mask, rect, bgdModel, fgdModel, 1, GC_EVAL ); if( exp_mask2.empty() ) { exp_mask2 = (mask & 1) * 255; imwrite(string(ts->get_data_path()) + "grabcut/exp_mask2.png", exp_mask2); } if (!verify((mask & 1) * 255, exp_mask2)) { ts->set_failed_test_info(cvtest::TS::FAIL_MISMATCH); return; } ts->set_failed_test_info(cvtest::TS::OK); } TEST(Imgproc_GrabCut, regression) { CV_GrabcutTest test; test.safe_run(); } TEST(Imgproc_GrabCut, repeatability) { cvtest::TS& ts = *cvtest::TS::ptr(); Mat image_1 = imread(string(ts.get_data_path()) + "grabcut/image1652.ppm", CV_LOAD_IMAGE_COLOR); Mat mask_1 = imread(string(ts.get_data_path()) + "grabcut/mask1652.ppm", CV_LOAD_IMAGE_GRAYSCALE); Rect roi_1(0, 0, 150, 150); Mat image_2 = image_1.clone(); Mat mask_2 = mask_1.clone(); Rect roi_2 = roi_1; Mat image_3 = image_1.clone(); Mat mask_3 = mask_1.clone(); Rect roi_3 = roi_1; Mat bgdModel_1, fgdModel_1; Mat bgdModel_2, fgdModel_2; Mat bgdModel_3, fgdModel_3; theRNG().state = 12378213; grabCut(image_1, mask_1, roi_1, bgdModel_1, fgdModel_1, 1, GC_INIT_WITH_MASK); theRNG().state = 12378213; grabCut(image_2, mask_2, roi_2, bgdModel_2, fgdModel_2, 1, GC_INIT_WITH_MASK); theRNG().state = 12378213; grabCut(image_3, mask_3, roi_3, bgdModel_3, fgdModel_3, 1, GC_INIT_WITH_MASK); EXPECT_EQ(0, countNonZero(mask_1 != mask_2)); EXPECT_EQ(0, countNonZero(mask_1 != mask_3)); EXPECT_EQ(0, countNonZero(mask_2 != mask_3)); }