OpenCV_4.2.0/opencv-4.2.0/modules/photo/test/test_inpaint.cpp

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#include "test_precomp.hpp"

namespace opencv_test { namespace {

class CV_InpaintTest : public cvtest::BaseTest
{
public:
    CV_InpaintTest();
    ~CV_InpaintTest();
protected:
    void run(int);
};

CV_InpaintTest::CV_InpaintTest()
{
}
CV_InpaintTest::~CV_InpaintTest() {}

void CV_InpaintTest::run( int )
{
    string folder = string(ts->get_data_path()) + "inpaint/";
    Mat orig = imread(folder + "orig.png");
    Mat exp1 = imread(folder + "exp1.png");
    Mat exp2 = imread(folder + "exp2.png");
    Mat mask = imread(folder + "mask.png");

    if (orig.empty() || exp1.empty() || exp2.empty() || mask.empty())
    {
        ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_TEST_DATA );
        return;
    }

    Mat inv_mask;
    mask.convertTo(inv_mask, CV_8UC3, -1.0, 255.0);

    Mat mask1ch;
    cv::cvtColor(mask, mask1ch, COLOR_BGR2GRAY);

    Mat test = orig.clone();
    test.setTo(Scalar::all(255), mask1ch);

    Mat res1, res2;
    inpaint( test, mask1ch, res1, 5, INPAINT_NS );
    inpaint( test, mask1ch, res2, 5, INPAINT_TELEA );

    Mat diff1, diff2;
    absdiff( orig, res1, diff1 );
    absdiff( orig, res2, diff2 );

    double n1 = cvtest::norm(diff1.reshape(1), NORM_INF, inv_mask.reshape(1));
    double n2 = cvtest::norm(diff2.reshape(1), NORM_INF, inv_mask.reshape(1));

    if (n1 != 0 || n2 != 0)
    {
        ts->set_failed_test_info( cvtest::TS::FAIL_MISMATCH );
        return;
    }

    absdiff( exp1, res1, diff1 );
    absdiff( exp2, res2, diff2 );

    n1 = cvtest::norm(diff1.reshape(1), NORM_INF, mask.reshape(1));
    n2 = cvtest::norm(diff2.reshape(1), NORM_INF, mask.reshape(1));

    const int jpeg_thres = 3;
    if (n1 > jpeg_thres || n2 > jpeg_thres)
    {
        ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
        return;
    }

    ts->set_failed_test_info(cvtest::TS::OK);
}

TEST(Photo_Inpaint, regression) { CV_InpaintTest test; test.safe_run(); }

typedef testing::TestWithParam<tuple<int> > formats;

TEST_P(formats, 1c)
{
    const int type = get<0>(GetParam());
    Mat src(100, 100, type);
    src.setTo(Scalar::all(128));
    Mat ref = src.clone();
    Mat dst, mask = Mat::zeros(src.size(), CV_8U);

    circle(src, Point(50, 50), 5, Scalar(200), 6);
    circle(mask, Point(50, 50), 5, Scalar(200), 6);
    inpaint(src, mask, dst, 10, INPAINT_NS);

    Mat dst2;
    inpaint(src, mask, dst2, 10, INPAINT_TELEA);

    ASSERT_LE(cv::norm(dst, ref, NORM_INF), 3.);
    ASSERT_LE(cv::norm(dst2, ref, NORM_INF), 3.);
}

INSTANTIATE_TEST_CASE_P(Photo_Inpaint, formats, testing::Values(CV_32F, CV_16U, CV_8U));

TEST(Photo_InpaintBorders, regression)
{
    Mat img(64, 64, CV_8U);
    img = 128;
    img(Rect(0, 0, 16, 64)) = 0;

    Mat mask(64, 64, CV_8U);
    mask = 0;
    mask(Rect(0, 0, 16, 64)) = 255;

    Mat inpainted;
    inpaint(img, mask, inpainted, 1, INPAINT_TELEA);

    Mat diff;
    cv::absdiff(inpainted, 128*Mat::ones(inpainted.size(), inpainted.type()), diff);
    ASSERT_TRUE(countNonZero(diff) == 0);
}

}} // namespace