2017-11-05 21:48:40 +08:00
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// This file is part of OpenCV project.
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// It is subject to the license terms in the LICENSE file found in the top-level directory
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// of this distribution and at http://opencv.org/license.html
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2017-06-07 01:22:30 +08:00
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#include "test_precomp.hpp"
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2017-11-05 21:48:40 +08:00
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namespace opencv_test { namespace {
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2017-06-07 01:22:30 +08:00
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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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2017-07-10 17:43:59 +08:00
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#ifdef __ANDROID__
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2017-06-07 01:22:30 +08:00
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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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2017-08-16 18:53:12 +08:00
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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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2017-06-07 01:22:30 +08:00
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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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2019-03-13 22:42:47 +08:00
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ASSERT_EQ((size_t)1, fwrite(tiff_sample_data[i], 86, 1, fp));
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2017-06-07 01:22:30 +08:00
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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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2017-08-16 18:53:12 +08:00
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EXPECT_EQ(0, remove(filename.c_str()));
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2017-06-07 01:22:30 +08:00
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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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2022-03-12 02:07:12 +08:00
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TEST(Imgcodecs_Tiff, decode_10_12_14)
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{
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/* see issue #21700
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*/
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const string root = cvtest::TS::ptr()->get_data_path();
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const double maxDiff = 256;//samples do not have the exact same values because of the tool that created them
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cv::Mat tmp;
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double diff = 0;
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cv::Mat img8UC1 = imread(root + "readwrite/pattern_8uc1.tif", cv::IMREAD_UNCHANGED);
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ASSERT_FALSE(img8UC1.empty());
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ASSERT_EQ(img8UC1.type(), CV_8UC1);
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cv::Mat img8UC3 = imread(root + "readwrite/pattern_8uc3.tif", cv::IMREAD_UNCHANGED);
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ASSERT_FALSE(img8UC3.empty());
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ASSERT_EQ(img8UC3.type(), CV_8UC3);
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cv::Mat img8UC4 = imread(root + "readwrite/pattern_8uc4.tif", cv::IMREAD_UNCHANGED);
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ASSERT_FALSE(img8UC4.empty());
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ASSERT_EQ(img8UC4.type(), CV_8UC4);
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cv::Mat img16UC1 = imread(root + "readwrite/pattern_16uc1.tif", cv::IMREAD_UNCHANGED);
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ASSERT_FALSE(img16UC1.empty());
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ASSERT_EQ(img16UC1.type(), CV_16UC1);
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ASSERT_EQ(img8UC1.size(), img16UC1.size());
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img8UC1.convertTo(tmp, img16UC1.type(), (1U<<(16-8)));
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diff = cv::norm(tmp.reshape(1), img16UC1.reshape(1), cv::NORM_INF);
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ASSERT_LE(diff, maxDiff);
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cv::Mat img16UC3 = imread(root + "readwrite/pattern_16uc3.tif", cv::IMREAD_UNCHANGED);
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ASSERT_FALSE(img16UC3.empty());
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ASSERT_EQ(img16UC3.type(), CV_16UC3);
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ASSERT_EQ(img8UC3.size(), img16UC3.size());
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img8UC3.convertTo(tmp, img16UC3.type(), (1U<<(16-8)));
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diff = cv::norm(tmp.reshape(1), img16UC3.reshape(1), cv::NORM_INF);
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ASSERT_LE(diff, maxDiff);
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cv::Mat img16UC4 = imread(root + "readwrite/pattern_16uc4.tif", cv::IMREAD_UNCHANGED);
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ASSERT_FALSE(img16UC4.empty());
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ASSERT_EQ(img16UC4.type(), CV_16UC4);
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ASSERT_EQ(img8UC4.size(), img16UC4.size());
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img8UC4.convertTo(tmp, img16UC4.type(), (1U<<(16-8)));
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diff = cv::norm(tmp.reshape(1), img16UC4.reshape(1), cv::NORM_INF);
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ASSERT_LE(diff, maxDiff);
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cv::Mat img10UC1 = imread(root + "readwrite/pattern_10uc1.tif", cv::IMREAD_UNCHANGED);
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ASSERT_FALSE(img10UC1.empty());
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ASSERT_EQ(img10UC1.type(), CV_16UC1);
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ASSERT_EQ(img10UC1.size(), img16UC1.size());
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diff = cv::norm(img10UC1.reshape(1), img16UC1.reshape(1), cv::NORM_INF);
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ASSERT_LE(diff, maxDiff);
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cv::Mat img10UC3 = imread(root + "readwrite/pattern_10uc3.tif", cv::IMREAD_UNCHANGED);
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ASSERT_FALSE(img10UC3.empty());
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ASSERT_EQ(img10UC3.type(), CV_16UC3);
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ASSERT_EQ(img10UC3.size(), img16UC3.size());
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diff = cv::norm(img10UC3.reshape(1), img16UC3.reshape(1), cv::NORM_INF);
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ASSERT_LE(diff, maxDiff);
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cv::Mat img10UC4 = imread(root + "readwrite/pattern_10uc4.tif", cv::IMREAD_UNCHANGED);
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ASSERT_FALSE(img10UC4.empty());
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ASSERT_EQ(img10UC4.type(), CV_16UC4);
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ASSERT_EQ(img10UC4.size(), img16UC4.size());
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diff = cv::norm(img10UC4.reshape(1), img16UC4.reshape(1), cv::NORM_INF);
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ASSERT_LE(diff, maxDiff);
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cv::Mat img12UC1 = imread(root + "readwrite/pattern_12uc1.tif", cv::IMREAD_UNCHANGED);
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ASSERT_FALSE(img12UC1.empty());
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ASSERT_EQ(img12UC1.type(), CV_16UC1);
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ASSERT_EQ(img12UC1.size(), img16UC1.size());
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diff = cv::norm(img12UC1.reshape(1), img16UC1.reshape(1), cv::NORM_INF);
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ASSERT_LE(diff, maxDiff);
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cv::Mat img12UC3 = imread(root + "readwrite/pattern_12uc3.tif", cv::IMREAD_UNCHANGED);
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ASSERT_FALSE(img12UC3.empty());
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ASSERT_EQ(img12UC3.type(), CV_16UC3);
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ASSERT_EQ(img12UC3.size(), img16UC3.size());
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diff = cv::norm(img12UC3.reshape(1), img16UC3.reshape(1), cv::NORM_INF);
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ASSERT_LE(diff, maxDiff);
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cv::Mat img12UC4 = imread(root + "readwrite/pattern_12uc4.tif", cv::IMREAD_UNCHANGED);
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ASSERT_FALSE(img12UC4.empty());
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ASSERT_EQ(img12UC4.type(), CV_16UC4);
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ASSERT_EQ(img12UC4.size(), img16UC4.size());
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diff = cv::norm(img12UC4.reshape(1), img16UC4.reshape(1), cv::NORM_INF);
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ASSERT_LE(diff, maxDiff);
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cv::Mat img14UC1 = imread(root + "readwrite/pattern_14uc1.tif", cv::IMREAD_UNCHANGED);
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ASSERT_FALSE(img14UC1.empty());
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ASSERT_EQ(img14UC1.type(), CV_16UC1);
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ASSERT_EQ(img14UC1.size(), img16UC1.size());
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diff = cv::norm(img14UC1.reshape(1), img16UC1.reshape(1), cv::NORM_INF);
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ASSERT_LE(diff, maxDiff);
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cv::Mat img14UC3 = imread(root + "readwrite/pattern_14uc3.tif", cv::IMREAD_UNCHANGED);
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ASSERT_FALSE(img14UC3.empty());
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ASSERT_EQ(img14UC3.type(), CV_16UC3);
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ASSERT_EQ(img14UC3.size(), img16UC3.size());
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diff = cv::norm(img14UC3.reshape(1), img16UC3.reshape(1), cv::NORM_INF);
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ASSERT_LE(diff, maxDiff);
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cv::Mat img14UC4 = imread(root + "readwrite/pattern_14uc4.tif", cv::IMREAD_UNCHANGED);
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ASSERT_FALSE(img14UC4.empty());
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ASSERT_EQ(img14UC4.type(), CV_16UC4);
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ASSERT_EQ(img14UC4.size(), img16UC4.size());
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diff = cv::norm(img14UC4.reshape(1), img16UC4.reshape(1), cv::NORM_INF);
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ASSERT_LE(diff, maxDiff);
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}
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2017-06-07 01:22:30 +08:00
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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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2017-08-16 18:53:12 +08:00
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EXPECT_EQ(0, remove(filename.c_str()));
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2017-06-07 01:22:30 +08:00
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}
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2022-02-01 01:54:27 +08:00
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TEST(Imgcodecs_Tiff, readWrite_unsigned)
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{
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|
|
|
const string root = cvtest::TS::ptr()->get_data_path();
|
|
|
|
const string filenameInput = root + "readwrite/gray_8u.tif";
|
|
|
|
const string filenameOutput = cv::tempfile(".tiff");
|
|
|
|
const Mat img = cv::imread(filenameInput, IMREAD_UNCHANGED);
|
|
|
|
ASSERT_FALSE(img.empty());
|
|
|
|
ASSERT_EQ(CV_8UC1, img.type());
|
|
|
|
|
|
|
|
Mat matS8;
|
|
|
|
img.convertTo(matS8, CV_8SC1);
|
|
|
|
|
|
|
|
ASSERT_TRUE(cv::imwrite(filenameOutput, matS8));
|
|
|
|
const Mat img2 = cv::imread(filenameOutput, IMREAD_UNCHANGED);
|
|
|
|
ASSERT_EQ(img2.type(), matS8.type());
|
|
|
|
ASSERT_EQ(img2.size(), matS8.size());
|
|
|
|
EXPECT_LE(cvtest::norm(matS8, img2, NORM_INF | NORM_RELATIVE), 1e-3);
|
|
|
|
EXPECT_EQ(0, remove(filenameOutput.c_str()));
|
|
|
|
}
|
|
|
|
|
2018-01-04 20:51:58 +08:00
|
|
|
TEST(Imgcodecs_Tiff, readWrite_32FC1)
|
|
|
|
{
|
|
|
|
const string root = cvtest::TS::ptr()->get_data_path();
|
|
|
|
const string filenameInput = root + "readwrite/test32FC1.tiff";
|
|
|
|
const string filenameOutput = cv::tempfile(".tiff");
|
|
|
|
const Mat img = cv::imread(filenameInput, IMREAD_UNCHANGED);
|
|
|
|
ASSERT_FALSE(img.empty());
|
|
|
|
ASSERT_EQ(CV_32FC1,img.type());
|
|
|
|
|
|
|
|
ASSERT_TRUE(cv::imwrite(filenameOutput, img));
|
|
|
|
const Mat img2 = cv::imread(filenameOutput, IMREAD_UNCHANGED);
|
2019-04-04 08:35:08 +08:00
|
|
|
ASSERT_EQ(img2.type(), img.type());
|
|
|
|
ASSERT_EQ(img2.size(), img.size());
|
|
|
|
EXPECT_LE(cvtest::norm(img, img2, NORM_INF | NORM_RELATIVE), 1e-3);
|
2018-01-04 20:51:58 +08:00
|
|
|
EXPECT_EQ(0, remove(filenameOutput.c_str()));
|
|
|
|
}
|
|
|
|
|
2019-04-04 08:35:08 +08:00
|
|
|
TEST(Imgcodecs_Tiff, readWrite_64FC1)
|
|
|
|
{
|
|
|
|
const string root = cvtest::TS::ptr()->get_data_path();
|
|
|
|
const string filenameInput = root + "readwrite/test64FC1.tiff";
|
|
|
|
const string filenameOutput = cv::tempfile(".tiff");
|
|
|
|
const Mat img = cv::imread(filenameInput, IMREAD_UNCHANGED);
|
|
|
|
ASSERT_FALSE(img.empty());
|
|
|
|
ASSERT_EQ(CV_64FC1, img.type());
|
|
|
|
|
|
|
|
ASSERT_TRUE(cv::imwrite(filenameOutput, img));
|
|
|
|
const Mat img2 = cv::imread(filenameOutput, IMREAD_UNCHANGED);
|
|
|
|
ASSERT_EQ(img2.type(), img.type());
|
|
|
|
ASSERT_EQ(img2.size(), img.size());
|
|
|
|
EXPECT_LE(cvtest::norm(img, img2, NORM_INF | NORM_RELATIVE), 1e-3);
|
|
|
|
EXPECT_EQ(0, remove(filenameOutput.c_str()));
|
|
|
|
}
|
|
|
|
|
|
|
|
TEST(Imgcodecs_Tiff, readWrite_32FC3_SGILOG)
|
|
|
|
{
|
|
|
|
const string root = cvtest::TS::ptr()->get_data_path();
|
|
|
|
const string filenameInput = root + "readwrite/test32FC3_sgilog.tiff";
|
|
|
|
const string filenameOutput = cv::tempfile(".tiff");
|
|
|
|
const Mat img = cv::imread(filenameInput, IMREAD_UNCHANGED);
|
|
|
|
ASSERT_FALSE(img.empty());
|
|
|
|
ASSERT_EQ(CV_32FC3, img.type());
|
|
|
|
|
|
|
|
ASSERT_TRUE(cv::imwrite(filenameOutput, img));
|
|
|
|
const Mat img2 = cv::imread(filenameOutput, IMREAD_UNCHANGED);
|
|
|
|
ASSERT_EQ(img2.type(), img.type());
|
|
|
|
ASSERT_EQ(img2.size(), img.size());
|
|
|
|
EXPECT_LE(cvtest::norm(img, img2, NORM_INF | NORM_RELATIVE), 0.01);
|
|
|
|
EXPECT_EQ(0, remove(filenameOutput.c_str()));
|
|
|
|
}
|
|
|
|
|
|
|
|
TEST(Imgcodecs_Tiff, readWrite_32FC3_RAW)
|
|
|
|
{
|
|
|
|
const string root = cvtest::TS::ptr()->get_data_path();
|
|
|
|
const string filenameInput = root + "readwrite/test32FC3_raw.tiff";
|
|
|
|
const string filenameOutput = cv::tempfile(".tiff");
|
|
|
|
const Mat img = cv::imread(filenameInput, IMREAD_UNCHANGED);
|
|
|
|
ASSERT_FALSE(img.empty());
|
|
|
|
ASSERT_EQ(CV_32FC3, img.type());
|
|
|
|
|
|
|
|
std::vector<int> params;
|
|
|
|
params.push_back(IMWRITE_TIFF_COMPRESSION);
|
|
|
|
params.push_back(1/*COMPRESSION_NONE*/);
|
|
|
|
|
|
|
|
ASSERT_TRUE(cv::imwrite(filenameOutput, img, params));
|
|
|
|
const Mat img2 = cv::imread(filenameOutput, IMREAD_UNCHANGED);
|
|
|
|
ASSERT_EQ(img2.type(), img.type());
|
|
|
|
ASSERT_EQ(img2.size(), img.size());
|
|
|
|
EXPECT_LE(cvtest::norm(img, img2, NORM_INF | NORM_RELATIVE), 1e-3);
|
|
|
|
EXPECT_EQ(0, remove(filenameOutput.c_str()));
|
|
|
|
}
|
|
|
|
|
2021-10-27 13:52:54 +08:00
|
|
|
TEST(Imgcodecs_Tiff, read_palette_color_image)
|
|
|
|
{
|
|
|
|
const string root = cvtest::TS::ptr()->get_data_path();
|
|
|
|
const string filenameInput = root + "readwrite/test_palette_color_image.tif";
|
|
|
|
|
|
|
|
const Mat img = cv::imread(filenameInput, IMREAD_UNCHANGED);
|
|
|
|
ASSERT_FALSE(img.empty());
|
|
|
|
ASSERT_EQ(CV_8UC3, img.type());
|
|
|
|
}
|
|
|
|
|
2022-05-13 14:44:25 +08:00
|
|
|
TEST(Imgcodecs_Tiff, readWrite_predictor)
|
|
|
|
{
|
|
|
|
/* see issue #21871
|
|
|
|
*/
|
|
|
|
const uchar sample_data[160] = {
|
|
|
|
0xff, 0xff, 0xff, 0xff, 0x88, 0x88, 0xff, 0xff, 0x88, 0x88, 0xff, 0xff, 0xff, 0xff, 0xff, 0x88,
|
|
|
|
0xff, 0xff, 0x00, 0x00, 0x00, 0x00, 0x00, 0xff, 0x00, 0x00, 0xff, 0xff, 0xff, 0xff, 0x00, 0x00,
|
|
|
|
0xff, 0x00, 0x00, 0x44, 0xff, 0xff, 0x88, 0xff, 0x33, 0x00, 0x66, 0xff, 0xff, 0x88, 0x00, 0x44,
|
|
|
|
0x88, 0x00, 0x44, 0xff, 0xff, 0xff, 0xff, 0xff, 0xff, 0x00, 0x44, 0xff, 0xff, 0x11, 0x00, 0xff,
|
|
|
|
0x11, 0x00, 0x88, 0xff, 0xff, 0xff, 0xff, 0xff, 0xff, 0x00, 0x00, 0xff, 0xff, 0x00, 0x00, 0xff,
|
|
|
|
0x11, 0x00, 0xff, 0xff, 0xff, 0xff, 0xff, 0xff, 0xff, 0x33, 0x00, 0x88, 0xff, 0x00, 0x66, 0xff,
|
|
|
|
0x11, 0x00, 0x66, 0xff, 0xff, 0xff, 0xff, 0xff, 0xff, 0xff, 0x00, 0x44, 0x33, 0x00, 0xff, 0xff,
|
|
|
|
0x88, 0x00, 0x00, 0xff, 0xff, 0xff, 0xff, 0xff, 0xff, 0xff, 0x00, 0x00, 0x00, 0x00, 0xff, 0xff,
|
|
|
|
0xff, 0x11, 0x00, 0x00, 0x00, 0x00, 0x00, 0xff, 0xff, 0xff, 0x33, 0x00, 0x00, 0x66, 0xff, 0xff,
|
|
|
|
0xff, 0xff, 0x88, 0x00, 0x00, 0x00, 0x00, 0xff, 0xff, 0xff, 0xff, 0x00, 0x00, 0xff, 0xff, 0xff
|
|
|
|
};
|
|
|
|
|
|
|
|
cv::Mat mat(10, 16, CV_8UC1, (void*)sample_data);
|
|
|
|
int methods[] = {
|
|
|
|
COMPRESSION_NONE, COMPRESSION_LZW,
|
|
|
|
COMPRESSION_PACKBITS, COMPRESSION_DEFLATE, COMPRESSION_ADOBE_DEFLATE
|
|
|
|
};
|
|
|
|
for (size_t i = 0; i < sizeof(methods) / sizeof(int); i++)
|
|
|
|
{
|
|
|
|
string out = cv::tempfile(".tif");
|
|
|
|
|
|
|
|
std::vector<int> params;
|
|
|
|
params.push_back(TIFFTAG_COMPRESSION);
|
|
|
|
params.push_back(methods[i]);
|
|
|
|
params.push_back(TIFFTAG_PREDICTOR);
|
|
|
|
params.push_back(PREDICTOR_HORIZONTAL);
|
|
|
|
|
|
|
|
EXPECT_NO_THROW(cv::imwrite(out, mat, params));
|
|
|
|
|
|
|
|
const Mat img = cv::imread(out, IMREAD_UNCHANGED);
|
|
|
|
ASSERT_FALSE(img.empty());
|
|
|
|
|
|
|
|
ASSERT_EQ(0, cv::norm(mat, img, cv::NORM_INF));
|
|
|
|
|
|
|
|
EXPECT_EQ(0, remove(out.c_str()));
|
|
|
|
}
|
|
|
|
}
|
2019-04-04 08:35:08 +08:00
|
|
|
|
|
|
|
|
2017-06-07 01:22:30 +08:00
|
|
|
//==================================================================================================
|
|
|
|
|
|
|
|
typedef testing::TestWithParam<int> Imgcodecs_Tiff_Modes;
|
|
|
|
|
|
|
|
TEST_P(Imgcodecs_Tiff_Modes, decode_multipage)
|
|
|
|
{
|
|
|
|
const int mode = GetParam();
|
|
|
|
const string root = cvtest::TS::ptr()->get_data_path();
|
|
|
|
const string filename = root + "readwrite/multipage.tif";
|
|
|
|
const string page_files[] = {
|
|
|
|
"readwrite/multipage_p1.tif",
|
|
|
|
"readwrite/multipage_p2.tif",
|
|
|
|
"readwrite/multipage_p3.tif",
|
|
|
|
"readwrite/multipage_p4.tif",
|
|
|
|
"readwrite/multipage_p5.tif",
|
|
|
|
"readwrite/multipage_p6.tif"
|
|
|
|
};
|
|
|
|
const size_t page_count = sizeof(page_files)/sizeof(page_files[0]);
|
|
|
|
vector<Mat> pages;
|
|
|
|
bool res = imreadmulti(filename, pages, mode);
|
|
|
|
ASSERT_TRUE(res == true);
|
|
|
|
ASSERT_EQ(page_count, pages.size());
|
|
|
|
for (size_t i = 0; i < page_count; i++)
|
|
|
|
{
|
|
|
|
const Mat page = imread(root + page_files[i], mode);
|
|
|
|
EXPECT_PRED_FORMAT2(cvtest::MatComparator(0, 0), page, pages[i]);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
const int all_modes[] =
|
|
|
|
{
|
|
|
|
IMREAD_UNCHANGED,
|
|
|
|
IMREAD_GRAYSCALE,
|
|
|
|
IMREAD_COLOR,
|
|
|
|
IMREAD_ANYDEPTH,
|
|
|
|
IMREAD_ANYCOLOR
|
|
|
|
};
|
|
|
|
|
|
|
|
INSTANTIATE_TEST_CASE_P(AllModes, Imgcodecs_Tiff_Modes, testing::ValuesIn(all_modes));
|
|
|
|
|
|
|
|
//==================================================================================================
|
|
|
|
|
2017-12-21 04:14:10 +08:00
|
|
|
TEST(Imgcodecs_Tiff_Modes, write_multipage)
|
|
|
|
{
|
|
|
|
const string root = cvtest::TS::ptr()->get_data_path();
|
|
|
|
const string filename = root + "readwrite/multipage.tif";
|
|
|
|
const string page_files[] = {
|
|
|
|
"readwrite/multipage_p1.tif",
|
|
|
|
"readwrite/multipage_p2.tif",
|
|
|
|
"readwrite/multipage_p3.tif",
|
|
|
|
"readwrite/multipage_p4.tif",
|
|
|
|
"readwrite/multipage_p5.tif",
|
|
|
|
"readwrite/multipage_p6.tif"
|
|
|
|
};
|
|
|
|
const size_t page_count = sizeof(page_files) / sizeof(page_files[0]);
|
|
|
|
vector<Mat> pages;
|
|
|
|
for (size_t i = 0; i < page_count; i++)
|
|
|
|
{
|
|
|
|
const Mat page = imread(root + page_files[i]);
|
|
|
|
pages.push_back(page);
|
|
|
|
}
|
|
|
|
|
|
|
|
string tmp_filename = cv::tempfile(".tiff");
|
|
|
|
bool res = imwrite(tmp_filename, pages);
|
|
|
|
ASSERT_TRUE(res);
|
|
|
|
|
|
|
|
vector<Mat> read_pages;
|
|
|
|
imreadmulti(tmp_filename, read_pages);
|
|
|
|
for (size_t i = 0; i < page_count; i++)
|
|
|
|
{
|
|
|
|
EXPECT_PRED_FORMAT2(cvtest::MatComparator(0, 0), read_pages[i], pages[i]);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
//==================================================================================================
|
|
|
|
|
2017-06-07 01:22:30 +08:00
|
|
|
TEST(Imgcodecs_Tiff, imdecode_no_exception_temporary_file_removed)
|
|
|
|
{
|
|
|
|
const string root = cvtest::TS::ptr()->get_data_path();
|
|
|
|
const string filename = root + "../cv/shared/lena.png";
|
|
|
|
cv::Mat img = cv::imread(filename);
|
|
|
|
ASSERT_FALSE(img.empty());
|
|
|
|
std::vector<uchar> buf;
|
|
|
|
EXPECT_NO_THROW(cv::imencode(".tiff", img, buf));
|
|
|
|
EXPECT_NO_THROW(cv::imdecode(buf, IMREAD_UNCHANGED));
|
|
|
|
}
|
|
|
|
|
2018-11-01 19:34:34 +08:00
|
|
|
|
2020-05-26 02:49:37 +08:00
|
|
|
TEST(Imgcodecs_Tiff, decode_black_and_write_image_pr12989_grayscale)
|
2018-11-01 19:34:34 +08:00
|
|
|
{
|
|
|
|
const string filename = cvtest::findDataFile("readwrite/bitsperpixel1.tiff");
|
|
|
|
cv::Mat img;
|
|
|
|
ASSERT_NO_THROW(img = cv::imread(filename, IMREAD_GRAYSCALE));
|
|
|
|
ASSERT_FALSE(img.empty());
|
|
|
|
EXPECT_EQ(64, img.cols);
|
|
|
|
EXPECT_EQ(64, img.rows);
|
|
|
|
EXPECT_EQ(CV_8UC1, img.type()) << cv::typeToString(img.type());
|
|
|
|
// Check for 0/255 values only: 267 + 3829 = 64*64
|
|
|
|
EXPECT_EQ(267, countNonZero(img == 0));
|
|
|
|
EXPECT_EQ(3829, countNonZero(img == 255));
|
|
|
|
}
|
|
|
|
|
|
|
|
TEST(Imgcodecs_Tiff, decode_black_and_write_image_pr12989_default)
|
|
|
|
{
|
|
|
|
const string filename = cvtest::findDataFile("readwrite/bitsperpixel1.tiff");
|
|
|
|
cv::Mat img;
|
|
|
|
ASSERT_NO_THROW(img = cv::imread(filename)); // by default image type is CV_8UC3
|
|
|
|
ASSERT_FALSE(img.empty());
|
|
|
|
EXPECT_EQ(64, img.cols);
|
|
|
|
EXPECT_EQ(64, img.rows);
|
|
|
|
EXPECT_EQ(CV_8UC3, img.type()) << cv::typeToString(img.type());
|
|
|
|
}
|
|
|
|
|
2020-05-26 02:49:37 +08:00
|
|
|
TEST(Imgcodecs_Tiff, decode_black_and_write_image_pr17275_grayscale)
|
|
|
|
{
|
|
|
|
const string filename = cvtest::findDataFile("readwrite/bitsperpixel1_min.tiff");
|
|
|
|
cv::Mat img;
|
|
|
|
ASSERT_NO_THROW(img = cv::imread(filename, IMREAD_GRAYSCALE));
|
|
|
|
ASSERT_FALSE(img.empty());
|
|
|
|
EXPECT_EQ(64, img.cols);
|
|
|
|
EXPECT_EQ(64, img.rows);
|
|
|
|
EXPECT_EQ(CV_8UC1, img.type()) << cv::typeToString(img.type());
|
|
|
|
// Check for 0/255 values only: 267 + 3829 = 64*64
|
|
|
|
EXPECT_EQ(267, countNonZero(img == 0));
|
|
|
|
EXPECT_EQ(3829, countNonZero(img == 255));
|
|
|
|
}
|
|
|
|
|
|
|
|
TEST(Imgcodecs_Tiff, decode_black_and_write_image_pr17275_default)
|
|
|
|
{
|
|
|
|
const string filename = cvtest::findDataFile("readwrite/bitsperpixel1_min.tiff");
|
|
|
|
cv::Mat img;
|
|
|
|
ASSERT_NO_THROW(img = cv::imread(filename)); // by default image type is CV_8UC3
|
|
|
|
ASSERT_FALSE(img.empty());
|
|
|
|
EXPECT_EQ(64, img.cols);
|
|
|
|
EXPECT_EQ(64, img.rows);
|
|
|
|
EXPECT_EQ(CV_8UC3, img.type()) << cv::typeToString(img.type());
|
|
|
|
}
|
|
|
|
|
2021-04-24 04:48:32 +08:00
|
|
|
TEST(Imgcodecs_Tiff, count_multipage)
|
|
|
|
{
|
|
|
|
const string root = cvtest::TS::ptr()->get_data_path();
|
|
|
|
{
|
|
|
|
const string filename = root + "readwrite/multipage.tif";
|
|
|
|
ASSERT_EQ((size_t)6, imcount(filename));
|
|
|
|
}
|
|
|
|
{
|
|
|
|
const string filename = root + "readwrite/test32FC3_raw.tiff";
|
|
|
|
ASSERT_EQ((size_t)1, imcount(filename));
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
TEST(Imgcodecs_Tiff, read_multipage_indexed)
|
|
|
|
{
|
|
|
|
const string root = cvtest::TS::ptr()->get_data_path();
|
|
|
|
const string filename = root + "readwrite/multipage.tif";
|
|
|
|
const string page_files[] = {
|
|
|
|
"readwrite/multipage_p1.tif",
|
|
|
|
"readwrite/multipage_p2.tif",
|
|
|
|
"readwrite/multipage_p3.tif",
|
|
|
|
"readwrite/multipage_p4.tif",
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|
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"readwrite/multipage_p5.tif",
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"readwrite/multipage_p6.tif"
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|
|
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};
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|
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const int page_count = sizeof(page_files) / sizeof(page_files[0]);
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|
|
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vector<Mat> single_pages;
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|
|
|
for (int i = 0; i < page_count; i++)
|
|
|
|
{
|
|
|
|
// imread and imreadmulti have different default values for the flag
|
|
|
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const Mat page = imread(root + page_files[i], IMREAD_ANYCOLOR);
|
|
|
|
single_pages.push_back(page);
|
|
|
|
}
|
|
|
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ASSERT_EQ((size_t)page_count, single_pages.size());
|
|
|
|
|
|
|
|
{
|
|
|
|
SCOPED_TRACE("Edge Cases");
|
|
|
|
vector<Mat> multi_pages;
|
|
|
|
bool res = imreadmulti(filename, multi_pages, 0, 0);
|
|
|
|
// If we asked for 0 images and we successfully read 0 images should this be false ?
|
|
|
|
ASSERT_TRUE(res == false);
|
|
|
|
ASSERT_EQ((size_t)0, multi_pages.size());
|
|
|
|
res = imreadmulti(filename, multi_pages, 0, 123123);
|
|
|
|
ASSERT_TRUE(res == true);
|
|
|
|
ASSERT_EQ((size_t)6, multi_pages.size());
|
|
|
|
}
|
|
|
|
|
|
|
|
{
|
|
|
|
SCOPED_TRACE("Read all with indices");
|
|
|
|
vector<Mat> multi_pages;
|
|
|
|
bool res = imreadmulti(filename, multi_pages, 0, 6);
|
|
|
|
ASSERT_TRUE(res == true);
|
|
|
|
ASSERT_EQ((size_t)page_count, multi_pages.size());
|
|
|
|
for (int i = 0; i < page_count; i++)
|
|
|
|
{
|
|
|
|
EXPECT_PRED_FORMAT2(cvtest::MatComparator(0, 0), multi_pages[i], single_pages[i]);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
{
|
|
|
|
SCOPED_TRACE("Read one by one");
|
|
|
|
vector<Mat> multi_pages;
|
|
|
|
for (int i = 0; i < page_count; i++)
|
|
|
|
{
|
|
|
|
bool res = imreadmulti(filename, multi_pages, i, 1);
|
|
|
|
ASSERT_TRUE(res == true);
|
|
|
|
ASSERT_EQ((size_t)1, multi_pages.size());
|
|
|
|
EXPECT_PRED_FORMAT2(cvtest::MatComparator(0, 0), multi_pages[0], single_pages[i]);
|
|
|
|
multi_pages.clear();
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
{
|
|
|
|
SCOPED_TRACE("Read multiple at a time");
|
|
|
|
vector<Mat> multi_pages;
|
|
|
|
for (int i = 0; i < page_count/2; i++)
|
|
|
|
{
|
|
|
|
bool res = imreadmulti(filename, multi_pages, i*2, 2);
|
|
|
|
ASSERT_TRUE(res == true);
|
|
|
|
ASSERT_EQ((size_t)2, multi_pages.size());
|
|
|
|
EXPECT_PRED_FORMAT2(cvtest::MatComparator(0, 0), multi_pages[0], single_pages[i * 2]) << i;
|
|
|
|
EXPECT_PRED_FORMAT2(cvtest::MatComparator(0, 0), multi_pages[1], single_pages[i * 2 + 1]);
|
|
|
|
multi_pages.clear();
|
|
|
|
}
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
2022-01-15 09:43:20 +08:00
|
|
|
TEST(Imgcodecs_Tiff, read_bigtiff_images)
|
|
|
|
{
|
|
|
|
const string root = cvtest::TS::ptr()->get_data_path();
|
|
|
|
const string filenamesInput[] = {
|
|
|
|
"readwrite/BigTIFF.tif",
|
|
|
|
"readwrite/BigTIFFMotorola.tif",
|
|
|
|
"readwrite/BigTIFFLong.tif",
|
|
|
|
"readwrite/BigTIFFLong8.tif",
|
|
|
|
"readwrite/BigTIFFMotorolaLongStrips.tif",
|
|
|
|
"readwrite/BigTIFFLong8Tiles.tif",
|
|
|
|
"readwrite/BigTIFFSubIFD4.tif",
|
|
|
|
"readwrite/BigTIFFSubIFD8.tif"
|
|
|
|
};
|
|
|
|
|
|
|
|
for (int i = 0; i < 8; i++)
|
|
|
|
{
|
|
|
|
const Mat bigtiff_img = imread(root + filenamesInput[i], IMREAD_UNCHANGED);
|
|
|
|
ASSERT_FALSE(bigtiff_img.empty());
|
|
|
|
EXPECT_EQ(64, bigtiff_img.cols);
|
|
|
|
EXPECT_EQ(64, bigtiff_img.rows);
|
|
|
|
ASSERT_EQ(CV_8UC3, bigtiff_img.type());
|
|
|
|
}
|
|
|
|
}
|
2021-04-24 04:48:32 +08:00
|
|
|
|
2017-06-07 01:22:30 +08:00
|
|
|
#endif
|
2017-11-05 21:48:40 +08:00
|
|
|
|
|
|
|
}} // namespace
|