Open Source Computer Vision Library https://opencv.org/
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/*M///////////////////////////////////////////////////////////////////////////////////////
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#include "test_precomp.hpp"
namespace opencv_test { namespace {
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", IMREAD_COLOR);
Mat mask_1 = imread(string(ts.get_data_path()) + "grabcut/mask1652.ppm", IMREAD_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));
}
}} // namespace