Open Source Computer Vision Library https://opencv.org/
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/*M///////////////////////////////////////////////////////////////////////////////////////
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// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
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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