142 lines
5.1 KiB
C++
142 lines
5.1 KiB
C++
/*M///////////////////////////////////////////////////////////////////////////////////////
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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//
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// By downloading, copying, installing or using the software you agree to this license.
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// If you do not agree to this license, do not download, install,
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// copy or use the software.
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//
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//
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// License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
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// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
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// Third party copyrights are property of their respective owners.
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//
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// Redistribution and use in source and binary forms, with or without modification,
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// are permitted provided that the following conditions are met:
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//
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// * Redistribution's of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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//
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// * Redistribution's in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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//
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// * The name of the copyright holders may not be used to endorse or promote products
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// derived from this software without specific prior written permission.
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//
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// This software is provided by the copyright holders and contributors "as is" and
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// any express or implied warranties, including, but not limited to, the implied
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// warranties of merchantability and fitness for a particular purpose are disclaimed.
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// In no event shall the Intel Corporation or contributors be liable for any direct,
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// indirect, incidental, special, exemplary, or consequential damages
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// (including, but not limited to, procurement of substitute goods or services;
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// loss of use, data, or profits; or business interruption) however caused
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// and on any theory of liability, whether in contract, strict liability,
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// or tort (including negligence or otherwise) arising in any way out of
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// the use of this software, even if advised of the possibility of such damage.
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//
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//M*/
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#include "test_precomp.hpp"
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#include <string>
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#include <iostream>
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using namespace std;
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using namespace cv;
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class CV_GrabcutTest : public cvtest::BaseTest
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{
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public:
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CV_GrabcutTest();
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~CV_GrabcutTest();
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protected:
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bool verify(const Mat& mask, const Mat& exp);
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void run(int);
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};
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CV_GrabcutTest::CV_GrabcutTest() {}
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CV_GrabcutTest::~CV_GrabcutTest() {}
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bool CV_GrabcutTest::verify(const Mat& mask, const Mat& exp)
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{
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const float maxDiffRatio = 0.005f;
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int expArea = countNonZero( exp );
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int nonIntersectArea = countNonZero( mask != exp );
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float curRatio = (float)nonIntersectArea / (float)expArea;
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ts->printf( cvtest::TS::LOG, "nonIntersectArea/expArea = %f\n", curRatio );
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return curRatio < maxDiffRatio;
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}
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void CV_GrabcutTest::run( int /* start_from */)
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{
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cvtest::DefaultRngAuto defRng;
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Mat img = imread(string(ts->get_data_path()) + "shared/airplane.jpg");
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Mat mask_prob = imread(string(ts->get_data_path()) + "grabcut/mask_prob.png", 0);
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Mat exp_mask1 = imread(string(ts->get_data_path()) + "grabcut/exp_mask1.png", 0);
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Mat exp_mask2 = imread(string(ts->get_data_path()) + "grabcut/exp_mask2.png", 0);
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if (img.empty() || (!mask_prob.empty() && img.size() != mask_prob.size()) ||
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(!exp_mask1.empty() && img.size() != exp_mask1.size()) ||
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(!exp_mask2.empty() && img.size() != exp_mask2.size()) )
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{
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ts->set_failed_test_info(cvtest::TS::FAIL_MISSING_TEST_DATA);
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return;
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}
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Rect rect(Point(24, 126), Point(483, 294));
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Mat exp_bgdModel, exp_fgdModel;
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Mat mask;
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mask = Scalar(0);
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Mat bgdModel, fgdModel;
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grabCut( img, mask, rect, bgdModel, fgdModel, 0, GC_INIT_WITH_RECT );
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grabCut( img, mask, rect, bgdModel, fgdModel, 2, GC_EVAL );
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// Multiply images by 255 for more visuality of test data.
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if( mask_prob.empty() )
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{
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mask.copyTo( mask_prob );
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imwrite(string(ts->get_data_path()) + "grabcut/mask_prob.png", mask_prob);
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}
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if( exp_mask1.empty() )
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{
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exp_mask1 = (mask & 1) * 255;
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imwrite(string(ts->get_data_path()) + "grabcut/exp_mask1.png", exp_mask1);
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}
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if (!verify((mask & 1) * 255, exp_mask1))
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{
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ts->set_failed_test_info(cvtest::TS::FAIL_MISMATCH);
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return;
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}
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mask = mask_prob;
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bgdModel.release();
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fgdModel.release();
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rect = Rect();
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grabCut( img, mask, rect, bgdModel, fgdModel, 0, GC_INIT_WITH_MASK );
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grabCut( img, mask, rect, bgdModel, fgdModel, 1, GC_EVAL );
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if( exp_mask2.empty() )
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{
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exp_mask2 = (mask & 1) * 255;
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imwrite(string(ts->get_data_path()) + "grabcut/exp_mask2.png", exp_mask2);
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}
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if (!verify((mask & 1) * 255, exp_mask2))
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{
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ts->set_failed_test_info(cvtest::TS::FAIL_MISMATCH);
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return;
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}
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ts->set_failed_test_info(cvtest::TS::OK);
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}
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TEST(Imgproc_GrabCut, regression) { CV_GrabcutTest test; test.safe_run(); }
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