Open Source Computer Vision Library https://opencv.org/
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/*M///////////////////////////////////////////////////////////////////////////////////////
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// License Agreement
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//
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#include "test_precomp.hpp"
#include "opencv2/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 <= 4; num_channels++)
{
if (num_channels == 2) continue;
if (num_channels == 4 && ext!=3 /*TIFF*/) continue;
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), std::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, IMREAD_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());
CV_Assert(num_channels == img_test.channels());
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), std::min((img_r * k), (img_c * k)) / 4 , Scalar::all(255));
string filename = cv::tempfile(".jpg");
imwrite(filename, img);
img = imread(filename, IMREAD_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, IMREAD_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), std::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, IMREAD_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(IMWRITE_PNG_COMPRESSION);
param.push_back(3); //default(3) 0-9.
cv::imencode(".png" ,im ,buff, param);
// hangs
Mat im2 = imdecode(buff,IMREAD_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);
}
//Test OpenCV issue 3075 is solved
class CV_GrfmtReadPNGColorPaletteWithAlphaTest : public cvtest::BaseTest
{
public:
void run(int)
{
try
{
// First Test : Read PNG with alpha, imread flag -1
Mat img = imread(string(ts->get_data_path()) + "readwrite/color_palette_alpha.png",-1);
if (img.empty()) ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_TEST_DATA);
ASSERT_TRUE(img.channels() == 4);
unsigned char* img_data = (unsigned char*)img.data;
// Verification first pixel is red in BGRA
ASSERT_TRUE(img_data[0] == 0x00);
ASSERT_TRUE(img_data[1] == 0x00);
ASSERT_TRUE(img_data[2] == 0xFF);
ASSERT_TRUE(img_data[3] == 0xFF);
// Verification second pixel is red in BGRA
ASSERT_TRUE(img_data[4] == 0x00);
ASSERT_TRUE(img_data[5] == 0x00);
ASSERT_TRUE(img_data[6] == 0xFF);
ASSERT_TRUE(img_data[7] == 0xFF);
// Second Test : Read PNG without alpha, imread flag -1
img = imread(string(ts->get_data_path()) + "readwrite/color_palette_no_alpha.png",-1);
if (img.empty()) ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_TEST_DATA);
ASSERT_TRUE(img.channels() == 3);
img_data = (unsigned char*)img.data;
// Verification first pixel is red in BGR
ASSERT_TRUE(img_data[0] == 0x00);
ASSERT_TRUE(img_data[1] == 0x00);
ASSERT_TRUE(img_data[2] == 0xFF);
// Verification second pixel is red in BGR
ASSERT_TRUE(img_data[3] == 0x00);
ASSERT_TRUE(img_data[4] == 0x00);
ASSERT_TRUE(img_data[5] == 0xFF);
// Third Test : Read PNG with alpha, imread flag 1
img = imread(string(ts->get_data_path()) + "readwrite/color_palette_alpha.png",1);
if (img.empty()) ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_TEST_DATA);
ASSERT_TRUE(img.channels() == 3);
img_data = (unsigned char*)img.data;
// Verification first pixel is red in BGR
ASSERT_TRUE(img_data[0] == 0x00);
ASSERT_TRUE(img_data[1] == 0x00);
ASSERT_TRUE(img_data[2] == 0xFF);
// Verification second pixel is red in BGR
ASSERT_TRUE(img_data[3] == 0x00);
ASSERT_TRUE(img_data[4] == 0x00);
ASSERT_TRUE(img_data[5] == 0xFF);
// Fourth Test : Read PNG without alpha, imread flag 1
img = imread(string(ts->get_data_path()) + "readwrite/color_palette_no_alpha.png",1);
if (img.empty()) ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_TEST_DATA);
ASSERT_TRUE(img.channels() == 3);
img_data = (unsigned char*)img.data;
// Verification first pixel is red in BGR
ASSERT_TRUE(img_data[0] == 0x00);
ASSERT_TRUE(img_data[1] == 0x00);
ASSERT_TRUE(img_data[2] == 0xFF);
// Verification second pixel is red in BGR
ASSERT_TRUE(img_data[3] == 0x00);
ASSERT_TRUE(img_data[4] == 0x00);
ASSERT_TRUE(img_data[5] == 0xFF);
}
catch(...)
{
ts->set_failed_test_info(cvtest::TS::FAIL_EXCEPTION);
}
ts->set_failed_test_info(cvtest::TS::OK);
}
};
TEST(Highgui_Image, read_png_color_palette_with_alpha) { CV_GrfmtReadPNGColorPaletteWithAlphaTest test; test.safe_run(); }
#endif
#ifdef HAVE_JPEG
TEST(Highgui_Jpeg, encode_empty)
{
cv::Mat img;
std::vector<uchar> jpegImg;
ASSERT_THROW(cv::imencode(".jpg", img, jpegImg), cv::Exception);
}
#endif
#ifdef HAVE_TIFF
// these defines are used to resolve conflict between tiff.h and opencv2/core/types_c.h
#define uint64 uint64_hack_
#define int64 int64_hack_
#include "tiff.h"
TEST(Highgui_Tiff, decode_tile16384x16384)
{
// see issue #2161
cv::Mat big(16384, 16384, CV_8UC1, cv::Scalar::all(0));
string file3 = cv::tempfile(".tiff");
string file4 = cv::tempfile(".tiff");
std::vector<int> params;
params.push_back(TIFFTAG_ROWSPERSTRIP);
params.push_back(big.rows);
cv::imwrite(file4, big, params);
cv::imwrite(file3, big.colRange(0, big.cols - 1), params);
big.release();
try
{
cv::imread(file3, IMREAD_UNCHANGED);
EXPECT_NO_THROW(cv::imread(file4, IMREAD_UNCHANGED));
}
catch(const std::bad_alloc&)
{
// have no enough memory
}
remove(file3.c_str());
remove(file4.c_str());
}
TEST(Highgui_Tiff, write_read_16bit_big_little_endian)
{
// see issue #2601 "16-bit Grayscale TIFF Load Failures Due to Buffer Underflow and Endianness"
// Setup data for two minimal 16-bit grayscale TIFF files in both endian formats
uchar tiff_sample_data[2][86] = { {
// Little endian
0x49, 0x49, 0x2a, 0x00, 0x0c, 0x00, 0x00, 0x00, 0xad, 0xde, 0xef, 0xbe, 0x06, 0x00, 0x00, 0x01,
0x03, 0x00, 0x01, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x01, 0x01, 0x03, 0x00, 0x01, 0x00,
0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x02, 0x01, 0x03, 0x00, 0x01, 0x00, 0x00, 0x00, 0x10, 0x00,
0x00, 0x00, 0x06, 0x01, 0x03, 0x00, 0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x11, 0x01,
0x04, 0x00, 0x01, 0x00, 0x00, 0x00, 0x08, 0x00, 0x00, 0x00, 0x17, 0x01, 0x04, 0x00, 0x01, 0x00,
0x00, 0x00, 0x04, 0x00, 0x00, 0x00 }, {
// Big endian
0x4d, 0x4d, 0x00, 0x2a, 0x00, 0x00, 0x00, 0x0c, 0xde, 0xad, 0xbe, 0xef, 0x00, 0x06, 0x01, 0x00,
0x00, 0x03, 0x00, 0x00, 0x00, 0x01, 0x00, 0x02, 0x00, 0x00, 0x01, 0x01, 0x00, 0x03, 0x00, 0x00,
0x00, 0x01, 0x00, 0x01, 0x00, 0x00, 0x01, 0x02, 0x00, 0x03, 0x00, 0x00, 0x00, 0x01, 0x00, 0x10,
0x00, 0x00, 0x01, 0x06, 0x00, 0x03, 0x00, 0x00, 0x00, 0x01, 0x00, 0x01, 0x00, 0x00, 0x01, 0x11,
0x00, 0x04, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x08, 0x01, 0x17, 0x00, 0x04, 0x00, 0x00,
0x00, 0x01, 0x00, 0x00, 0x00, 0x04 }
};
// Test imread() for both a little endian TIFF and big endian TIFF
for (int i = 0; i < 2; i++)
{
string filename = cv::tempfile(".tiff");
// Write sample TIFF file
FILE* fp = fopen(filename.c_str(), "wb");
ASSERT_TRUE(fp != NULL);
ASSERT_EQ((size_t)1, fwrite(tiff_sample_data, 86, 1, fp));
fclose(fp);
Mat img = imread(filename, IMREAD_UNCHANGED);
EXPECT_EQ(1, img.rows);
EXPECT_EQ(2, img.cols);
EXPECT_EQ(CV_16U, img.type());
EXPECT_EQ(sizeof(ushort), img.elemSize());
EXPECT_EQ(1, img.channels());
EXPECT_EQ(0xDEAD, img.at<ushort>(0,0));
EXPECT_EQ(0xBEEF, img.at<ushort>(0,1));
remove(filename.c_str());
}
}
#endif
#ifdef HAVE_WEBP
TEST(Highgui_WebP, encode_decode_lossless_webp)
{
cvtest::TS& ts = *cvtest::TS::ptr();
string input = string(ts.get_data_path()) + "../cv/shared/lena.png";
cv::Mat img = cv::imread(input);
ASSERT_FALSE(img.empty());
string output = cv::tempfile(".webp");
EXPECT_NO_THROW(cv::imwrite(output, img)); // lossless
cv::Mat img_webp = cv::imread(output);
std::vector<unsigned char> buf;
FILE * wfile = NULL;
wfile = fopen(output.c_str(), "rb");
if (wfile != NULL)
{
fseek(wfile, 0, SEEK_END);
size_t wfile_size = ftell(wfile);
fseek(wfile, 0, SEEK_SET);
buf.resize(wfile_size);
size_t data_size = fread(&buf[0], 1, wfile_size, wfile);
if(wfile)
{
fclose(wfile);
}
if (data_size != wfile_size)
{
EXPECT_TRUE(false);
}
}
remove(output.c_str());
cv::Mat decode = cv::imdecode(buf, IMREAD_COLOR);
ASSERT_FALSE(decode.empty());
EXPECT_TRUE(cv::norm(decode, img_webp, NORM_INF) == 0);
ASSERT_FALSE(img_webp.empty());
EXPECT_TRUE(cv::norm(img, img_webp, NORM_INF) == 0);
}
TEST(Highgui_WebP, encode_decode_lossy_webp)
{
cvtest::TS& ts = *cvtest::TS::ptr();
std::string input = std::string(ts.get_data_path()) + "../cv/shared/lena.png";
cv::Mat img = cv::imread(input);
ASSERT_FALSE(img.empty());
for(int q = 100; q>=0; q-=20)
{
std::vector<int> params;
params.push_back(IMWRITE_WEBP_QUALITY);
params.push_back(q);
string output = cv::tempfile(".webp");
EXPECT_NO_THROW(cv::imwrite(output, img, params));
cv::Mat img_webp = cv::imread(output);
remove(output.c_str());
EXPECT_FALSE(img_webp.empty());
EXPECT_EQ(3, img_webp.channels());
EXPECT_EQ(512, img_webp.cols);
EXPECT_EQ(512, img_webp.rows);
}
}
TEST(Highgui_WebP, encode_decode_with_alpha_webp)
{
cvtest::TS& ts = *cvtest::TS::ptr();
std::string input = std::string(ts.get_data_path()) + "../cv/shared/lena.png";
cv::Mat img = cv::imread(input);
ASSERT_FALSE(img.empty());
std::vector<cv::Mat> imgs;
cv::split(img, imgs);
imgs.push_back(cv::Mat(imgs[0]));
imgs[imgs.size() - 1] = cv::Scalar::all(128);
cv::merge(imgs, img);
string output = cv::tempfile(".webp");
EXPECT_NO_THROW(cv::imwrite(output, img));
cv::Mat img_webp = cv::imread(output);
remove(output.c_str());
EXPECT_FALSE(img_webp.empty());
EXPECT_EQ(4, img_webp.channels());
EXPECT_EQ(512, img_webp.cols);
EXPECT_EQ(512, img_webp.rows);
}
#endif
TEST(Highgui_Hdr, regression)
{
string folder = string(cvtest::TS::ptr()->get_data_path()) + "/readwrite/";
string name_rle = folder + "rle.hdr";
string name_no_rle = folder + "no_rle.hdr";
Mat img_rle = imread(name_rle, -1);
ASSERT_FALSE(img_rle.empty()) << "Could not open " << name_rle;
Mat img_no_rle = imread(name_no_rle, -1);
ASSERT_FALSE(img_no_rle.empty()) << "Could not open " << name_no_rle;
double min = 0.0, max = 1.0;
minMaxLoc(abs(img_rle - img_no_rle), &min, &max);
ASSERT_FALSE(max > DBL_EPSILON);
string tmp_file_name = tempfile(".hdr");
vector<int>param(1);
for(int i = 0; i < 2; i++) {
param[0] = i;
imwrite(tmp_file_name, img_rle, param);
Mat written_img = imread(tmp_file_name, -1);
ASSERT_FALSE(written_img.empty()) << "Could not open " << tmp_file_name;
minMaxLoc(abs(img_rle - written_img), &min, &max);
ASSERT_FALSE(max > DBL_EPSILON);
}
}