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Open Source Computer Vision Library
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219 lines
8.3 KiB
219 lines
8.3 KiB
#include "test_precomp.hpp" |
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using namespace cv; |
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using namespace std; |
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using namespace std::tr1; |
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#ifdef HAVE_TIFF |
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// these defines are used to resolve conflict between tiff.h and opencv2/core/types_c.h |
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#define uint64 uint64_hack_ |
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#define int64 int64_hack_ |
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#include "tiff.h" |
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#ifdef __ANDROID__ |
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// Test disabled as it uses a lot of memory. |
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// It is killed with SIGKILL by out of memory killer. |
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TEST(Imgcodecs_Tiff, DISABLED_decode_tile16384x16384) |
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#else |
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TEST(Imgcodecs_Tiff, decode_tile16384x16384) |
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#endif |
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{ |
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// see issue #2161 |
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cv::Mat big(16384, 16384, CV_8UC1, cv::Scalar::all(0)); |
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string file3 = cv::tempfile(".tiff"); |
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string file4 = cv::tempfile(".tiff"); |
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std::vector<int> params; |
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params.push_back(TIFFTAG_ROWSPERSTRIP); |
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params.push_back(big.rows); |
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EXPECT_NO_THROW(cv::imwrite(file4, big, params)); |
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EXPECT_NO_THROW(cv::imwrite(file3, big.colRange(0, big.cols - 1), params)); |
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big.release(); |
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try |
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{ |
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cv::imread(file3, IMREAD_UNCHANGED); |
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EXPECT_NO_THROW(cv::imread(file4, IMREAD_UNCHANGED)); |
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} |
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catch(const std::bad_alloc&) |
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{ |
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// not enough memory |
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} |
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EXPECT_EQ(0, remove(file3.c_str())); |
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EXPECT_EQ(0, remove(file4.c_str())); |
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} |
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TEST(Imgcodecs_Tiff, write_read_16bit_big_little_endian) |
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{ |
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// see issue #2601 "16-bit Grayscale TIFF Load Failures Due to Buffer Underflow and Endianness" |
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// Setup data for two minimal 16-bit grayscale TIFF files in both endian formats |
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uchar tiff_sample_data[2][86] = { { |
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// Little endian |
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0x49, 0x49, 0x2a, 0x00, 0x0c, 0x00, 0x00, 0x00, 0xad, 0xde, 0xef, 0xbe, 0x06, 0x00, 0x00, 0x01, |
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0x03, 0x00, 0x01, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x01, 0x01, 0x03, 0x00, 0x01, 0x00, |
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0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x02, 0x01, 0x03, 0x00, 0x01, 0x00, 0x00, 0x00, 0x10, 0x00, |
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0x00, 0x00, 0x06, 0x01, 0x03, 0x00, 0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x11, 0x01, |
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0x04, 0x00, 0x01, 0x00, 0x00, 0x00, 0x08, 0x00, 0x00, 0x00, 0x17, 0x01, 0x04, 0x00, 0x01, 0x00, |
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0x00, 0x00, 0x04, 0x00, 0x00, 0x00 }, { |
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// Big endian |
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0x4d, 0x4d, 0x00, 0x2a, 0x00, 0x00, 0x00, 0x0c, 0xde, 0xad, 0xbe, 0xef, 0x00, 0x06, 0x01, 0x00, |
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0x00, 0x03, 0x00, 0x00, 0x00, 0x01, 0x00, 0x02, 0x00, 0x00, 0x01, 0x01, 0x00, 0x03, 0x00, 0x00, |
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0x00, 0x01, 0x00, 0x01, 0x00, 0x00, 0x01, 0x02, 0x00, 0x03, 0x00, 0x00, 0x00, 0x01, 0x00, 0x10, |
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0x00, 0x00, 0x01, 0x06, 0x00, 0x03, 0x00, 0x00, 0x00, 0x01, 0x00, 0x01, 0x00, 0x00, 0x01, 0x11, |
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0x00, 0x04, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x08, 0x01, 0x17, 0x00, 0x04, 0x00, 0x00, |
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0x00, 0x01, 0x00, 0x00, 0x00, 0x04 } |
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}; |
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// Test imread() for both a little endian TIFF and big endian TIFF |
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for (int i = 0; i < 2; i++) |
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{ |
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string filename = cv::tempfile(".tiff"); |
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// Write sample TIFF file |
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FILE* fp = fopen(filename.c_str(), "wb"); |
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ASSERT_TRUE(fp != NULL); |
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ASSERT_EQ((size_t)1, fwrite(tiff_sample_data, 86, 1, fp)); |
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fclose(fp); |
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Mat img = imread(filename, IMREAD_UNCHANGED); |
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EXPECT_EQ(1, img.rows); |
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EXPECT_EQ(2, img.cols); |
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EXPECT_EQ(CV_16U, img.type()); |
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EXPECT_EQ(sizeof(ushort), img.elemSize()); |
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EXPECT_EQ(1, img.channels()); |
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EXPECT_EQ(0xDEAD, img.at<ushort>(0,0)); |
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EXPECT_EQ(0xBEEF, img.at<ushort>(0,1)); |
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EXPECT_EQ(0, remove(filename.c_str())); |
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} |
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} |
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TEST(Imgcodecs_Tiff, decode_tile_remainder) |
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{ |
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/* see issue #3472 - dealing with tiled images where the tile size is |
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* not a multiple of image size. |
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* The tiled images were created with 'convert' from ImageMagick, |
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* using the command 'convert <input> -define tiff:tile-geometry=128x128 -depth [8|16] <output> |
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* Note that the conversion to 16 bits expands the range from 0-255 to 0-255*255, |
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* so the test converts back but rounding errors cause small differences. |
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*/ |
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const string root = cvtest::TS::ptr()->get_data_path(); |
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cv::Mat img = imread(root + "readwrite/non_tiled.tif",-1); |
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ASSERT_FALSE(img.empty()); |
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ASSERT_TRUE(img.channels() == 3); |
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cv::Mat tiled8 = imread(root + "readwrite/tiled_8.tif", -1); |
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ASSERT_FALSE(tiled8.empty()); |
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ASSERT_PRED_FORMAT2(cvtest::MatComparator(0, 0), img, tiled8); |
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cv::Mat tiled16 = imread(root + "readwrite/tiled_16.tif", -1); |
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ASSERT_FALSE(tiled16.empty()); |
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ASSERT_TRUE(tiled16.elemSize() == 6); |
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tiled16.convertTo(tiled8, CV_8UC3, 1./256.); |
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ASSERT_PRED_FORMAT2(cvtest::MatComparator(2, 0), img, tiled8); |
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// What about 32, 64 bit? |
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} |
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TEST(Imgcodecs_Tiff, decode_infinite_rowsperstrip) |
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{ |
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const uchar sample_data[142] = { |
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0x49, 0x49, 0x2a, 0x00, 0x10, 0x00, 0x00, 0x00, 0x56, 0x54, |
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0x56, 0x5a, 0x59, 0x55, 0x5a, 0x00, 0x0a, 0x00, 0x00, 0x01, |
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0x03, 0x00, 0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, |
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0x01, 0x01, 0x03, 0x00, 0x01, 0x00, 0x00, 0x00, 0x07, 0x00, |
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0x00, 0x00, 0x02, 0x01, 0x03, 0x00, 0x01, 0x00, 0x00, 0x00, |
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0x08, 0x00, 0x00, 0x00, 0x03, 0x01, 0x03, 0x00, 0x01, 0x00, |
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0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x06, 0x01, 0x03, 0x00, |
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0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x11, 0x01, |
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0x04, 0x00, 0x01, 0x00, 0x00, 0x00, 0x08, 0x00, 0x00, 0x00, |
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0x15, 0x01, 0x03, 0x00, 0x01, 0x00, 0x00, 0x00, 0x01, 0x00, |
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0x00, 0x00, 0x16, 0x01, 0x04, 0x00, 0x01, 0x00, 0x00, 0x00, |
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0xff, 0xff, 0xff, 0xff, 0x17, 0x01, 0x04, 0x00, 0x01, 0x00, |
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0x00, 0x00, 0x07, 0x00, 0x00, 0x00, 0x1c, 0x01, 0x03, 0x00, |
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0x01, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x00, 0x00, |
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0x00, 0x00 |
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}; |
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const string filename = cv::tempfile(".tiff"); |
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std::ofstream outfile(filename.c_str(), std::ofstream::binary); |
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outfile.write(reinterpret_cast<const char *>(sample_data), sizeof sample_data); |
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outfile.close(); |
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EXPECT_NO_THROW(cv::imread(filename, IMREAD_UNCHANGED)); |
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EXPECT_EQ(0, remove(filename.c_str())); |
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} |
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TEST(Imgcodecs_Tiff, readWrite_32FC1) |
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{ |
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const string root = cvtest::TS::ptr()->get_data_path(); |
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const string filenameInput = root + "readwrite/test32FC1.tiff"; |
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const string filenameOutput = cv::tempfile(".tiff"); |
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const Mat img = cv::imread(filenameInput, IMREAD_UNCHANGED); |
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ASSERT_FALSE(img.empty()); |
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ASSERT_EQ(CV_32FC1,img.type()); |
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ASSERT_TRUE(cv::imwrite(filenameOutput, img)); |
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const Mat img2 = cv::imread(filenameOutput, IMREAD_UNCHANGED); |
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ASSERT_EQ(img2.type(),img.type()); |
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ASSERT_EQ(img2.size(),img.size()); |
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EXPECT_GE(1e-3, cvtest::norm(img, img2, NORM_INF | NORM_RELATIVE)); |
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EXPECT_EQ(0, remove(filenameOutput.c_str())); |
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} |
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//================================================================================================== |
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typedef testing::TestWithParam<int> Imgcodecs_Tiff_Modes; |
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TEST_P(Imgcodecs_Tiff_Modes, decode_multipage) |
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{ |
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const int mode = GetParam(); |
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const string root = cvtest::TS::ptr()->get_data_path(); |
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const string filename = root + "readwrite/multipage.tif"; |
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const string page_files[] = { |
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"readwrite/multipage_p1.tif", |
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"readwrite/multipage_p2.tif", |
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"readwrite/multipage_p3.tif", |
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"readwrite/multipage_p4.tif", |
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"readwrite/multipage_p5.tif", |
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"readwrite/multipage_p6.tif" |
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}; |
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const size_t page_count = sizeof(page_files)/sizeof(page_files[0]); |
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vector<Mat> pages; |
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bool res = imreadmulti(filename, pages, mode); |
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ASSERT_TRUE(res == true); |
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ASSERT_EQ(page_count, pages.size()); |
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for (size_t i = 0; i < page_count; i++) |
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{ |
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const Mat page = imread(root + page_files[i], mode); |
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EXPECT_PRED_FORMAT2(cvtest::MatComparator(0, 0), page, pages[i]); |
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} |
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} |
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const int all_modes[] = |
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{ |
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IMREAD_UNCHANGED, |
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IMREAD_GRAYSCALE, |
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IMREAD_COLOR, |
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IMREAD_ANYDEPTH, |
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IMREAD_ANYCOLOR |
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}; |
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INSTANTIATE_TEST_CASE_P(AllModes, Imgcodecs_Tiff_Modes, testing::ValuesIn(all_modes)); |
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//================================================================================================== |
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TEST(Imgcodecs_Tiff, imdecode_no_exception_temporary_file_removed) |
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{ |
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const string root = cvtest::TS::ptr()->get_data_path(); |
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const string filename = root + "../cv/shared/lena.png"; |
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cv::Mat img = cv::imread(filename); |
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ASSERT_FALSE(img.empty()); |
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std::vector<uchar> buf; |
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EXPECT_NO_THROW(cv::imencode(".tiff", img, buf)); |
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EXPECT_NO_THROW(cv::imdecode(buf, IMREAD_UNCHANGED)); |
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} |
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#endif
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