opencv/modules/highgui/test/test_grfmt.cpp

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#include "test_precomp.hpp"
#include "opencv2/highgui/highgui.hpp"

using namespace cv;
using namespace std;


class CV_GrfmtWriteBigImageTest : public cvtest::BaseTest
{
public:
    void run(int)
    {
        try
        {
            ts->printf(cvtest::TS::LOG, "start  reading big image\n");
            Mat img = imread(string(ts->get_data_path()) + "readwrite/read.png");
            ts->printf(cvtest::TS::LOG, "finish reading big image\n");
            if (img.empty()) ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_TEST_DATA);
            ts->printf(cvtest::TS::LOG, "start  writing big image\n");
            imwrite(cv::tempfile(".png"), img);
            ts->printf(cvtest::TS::LOG, "finish writing big image\n");
        }
        catch(...)
        {
            ts->set_failed_test_info(cvtest::TS::FAIL_EXCEPTION);
        }
        ts->set_failed_test_info(cvtest::TS::OK);
    }
};

string ext_from_int(int ext)
{
#ifdef HAVE_PNG
    if (ext == 0) return ".png";
#endif
    if (ext == 1) return ".bmp";
    if (ext == 2) return ".pgm";
#ifdef HAVE_TIFF
    if (ext == 3) return ".tiff";
#endif
    return "";
}

class CV_GrfmtWriteSequenceImageTest : public cvtest::BaseTest
{
public:
    void run(int)
    {
        try
        {
            const int img_r = 640;
            const int img_c = 480;

            for (int k = 1; k <= 5; ++k)
            {
                for (int ext = 0; ext < 4; ++ext) // 0 - png, 1 - bmp, 2 - pgm, 3 - tiff
                {
                    if(ext_from_int(ext).empty())
                        continue;
                    for (int num_channels = 1; num_channels <= 3; num_channels+=2)
                    {
                        ts->printf(ts->LOG, "image type depth:%d   channels:%d   ext: %s\n", CV_8U, num_channels, ext_from_int(ext).c_str());
                        Mat img(img_r * k, img_c * k, CV_MAKETYPE(CV_8U, num_channels), Scalar::all(0));
                        circle(img, Point2i((img_c * k) / 2, (img_r * k) / 2), cv::min((img_r * k), (img_c * k)) / 4 , Scalar::all(255));

                        string img_path = cv::tempfile(ext_from_int(ext).c_str());
                        ts->printf(ts->LOG, "writing      image : %s\n", img_path.c_str());
                        imwrite(img_path, img);

                        ts->printf(ts->LOG, "reading test image : %s\n", img_path.c_str());
                        Mat img_test = imread(img_path, CV_LOAD_IMAGE_UNCHANGED);

                        if (img_test.empty()) ts->set_failed_test_info(ts->FAIL_MISMATCH);

                        CV_Assert(img.size() == img_test.size());
                        CV_Assert(img.type() == img_test.type());

                        double n = norm(img, img_test);
                        if ( n > 1.0)
                        {
                            ts->printf(ts->LOG, "norm = %f \n", n);
                            ts->set_failed_test_info(ts->FAIL_MISMATCH);
                        }
                    }
                }

#ifdef HAVE_JPEG
                for (int num_channels = 1; num_channels <= 3; num_channels+=2)
                {
                    // jpeg
                    ts->printf(ts->LOG, "image type depth:%d   channels:%d   ext: %s\n", CV_8U, num_channels, ".jpg");
                    Mat img(img_r * k, img_c * k, CV_MAKETYPE(CV_8U, num_channels), Scalar::all(0));
                    circle(img, Point2i((img_c * k) / 2, (img_r * k) / 2), cv::min((img_r * k), (img_c * k)) / 4 , Scalar::all(255));

                    string filename = cv::tempfile(".jpg");
                    imwrite(filename, img);
                    img = imread(filename, CV_LOAD_IMAGE_UNCHANGED);

                    filename = string(ts->get_data_path() + "readwrite/test_" + char(k + 48) + "_c" + char(num_channels + 48) + ".jpg");
                    ts->printf(ts->LOG, "reading test image : %s\n", filename.c_str());
                    Mat img_test = imread(filename, CV_LOAD_IMAGE_UNCHANGED);

                    if (img_test.empty()) ts->set_failed_test_info(ts->FAIL_MISMATCH);

                    CV_Assert(img.size() == img_test.size());
                    CV_Assert(img.type() == img_test.type());

                    double n = norm(img, img_test);
                    if ( n > 1.0)
                    {
                        ts->printf(ts->LOG, "norm = %f \n", n);
                        ts->set_failed_test_info(ts->FAIL_MISMATCH);
                    }
                }
#endif

#ifdef HAVE_TIFF
                for (int num_channels = 1; num_channels <= 3; num_channels+=2)
                {
                    // tiff
                    ts->printf(ts->LOG, "image type depth:%d   channels:%d   ext: %s\n", CV_16U, num_channels, ".tiff");
                    Mat img(img_r * k, img_c * k, CV_MAKETYPE(CV_16U, num_channels), Scalar::all(0));
                    circle(img, Point2i((img_c * k) / 2, (img_r * k) / 2), cv::min((img_r * k), (img_c * k)) / 4 , Scalar::all(255));

                    string filename = cv::tempfile(".tiff");
                    imwrite(filename, img);
                    ts->printf(ts->LOG, "reading test image : %s\n", filename.c_str());
                    Mat img_test = imread(filename, CV_LOAD_IMAGE_UNCHANGED);

                    if (img_test.empty()) ts->set_failed_test_info(ts->FAIL_MISMATCH);

                    CV_Assert(img.size() == img_test.size());

                    ts->printf(ts->LOG, "img      : %d ; %d \n", img.channels(), img.depth());
                    ts->printf(ts->LOG, "img_test : %d ; %d \n", img_test.channels(), img_test.depth());

                    CV_Assert(img.type() == img_test.type());


                    double n = norm(img, img_test);
                    if ( n > 1.0)
                    {
                        ts->printf(ts->LOG, "norm = %f \n", n);
                        ts->set_failed_test_info(ts->FAIL_MISMATCH);
                    }
                }
#endif
            }
        }
        catch(const cv::Exception & e)
        {
            ts->printf(ts->LOG, "Exception: %s\n" , e.what());
            ts->set_failed_test_info(ts->FAIL_MISMATCH);
        }
    }
};

class CV_GrfmtReadBMPRLE8Test : public cvtest::BaseTest
{
public:
    void run(int)
    {
        try
        {
            Mat rle = imread(string(ts->get_data_path()) + "readwrite/rle8.bmp");
            Mat bmp = imread(string(ts->get_data_path()) + "readwrite/ordinary.bmp");
            if (norm(rle-bmp)>1.e-10)
                ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
        }
        catch(...)
        {
            ts->set_failed_test_info(cvtest::TS::FAIL_EXCEPTION);
        }
        ts->set_failed_test_info(cvtest::TS::OK);
    }
};


#ifdef HAVE_PNG
TEST(Highgui_Image, write_big) { CV_GrfmtWriteBigImageTest test; test.safe_run(); }
#endif

TEST(Highgui_Image, write_imageseq) { CV_GrfmtWriteSequenceImageTest test; test.safe_run(); }

TEST(Highgui_Image, read_bmp_rle8) { CV_GrfmtReadBMPRLE8Test test; test.safe_run(); }

#ifdef HAVE_PNG
class CV_GrfmtPNGEncodeTest : public cvtest::BaseTest
{
public:
    void run(int)
    {
        try
        {
            vector<uchar> buff;
            Mat im = Mat::zeros(1000,1000, CV_8U);
            //randu(im, 0, 256);
            vector<int> param;
            param.push_back(CV_IMWRITE_PNG_COMPRESSION);
            param.push_back(3); //default(3) 0-9.
            cv::imencode(".png" ,im ,buff, param);

            // hangs
            Mat im2 = imdecode(buff,CV_LOAD_IMAGE_ANYDEPTH);
        }
        catch(...)
        {
            ts->set_failed_test_info(cvtest::TS::FAIL_EXCEPTION);
        }
        ts->set_failed_test_info(cvtest::TS::OK);
    }
};

TEST(Highgui_Image, encode_png) { CV_GrfmtPNGEncodeTest test; test.safe_run(); }

TEST(Highgui_ImreadVSCvtColor, regression)
{
    cvtest::TS& ts = *cvtest::TS::ptr();

    const int MAX_MEAN_DIFF = 1;
    const int MAX_ABS_DIFF = 10;

    string imgName = string(ts.get_data_path()) + "/../cv/shared/lena.png";
    Mat original_image = imread(imgName);
    Mat gray_by_codec = imread(imgName, 0);
    Mat gray_by_cvt;

    cvtColor(original_image, gray_by_cvt, CV_BGR2GRAY);

    Mat diff;
    absdiff(gray_by_codec, gray_by_cvt, diff);

    double actual_avg_diff = (double)mean(diff)[0];
    double actual_maxval, actual_minval;
    minMaxLoc(diff, &actual_minval, &actual_maxval);
    //printf("actual avg = %g, actual maxdiff = %g, npixels = %d\n", actual_avg_diff, actual_maxval, (int)diff.total());

    EXPECT_LT(actual_avg_diff, MAX_MEAN_DIFF);
    EXPECT_LT(actual_maxval, MAX_ABS_DIFF);
}
#endif