718c41634f
1.项目后端整体迁移至PaddleOCR-NCNN算法，已通过基本的兼容性测试 2.工程改为使用CMake组织，后续为了更好地兼容第三方库，不再提供QMake工程 3.重整权利声明文件，重整代码工程，确保最小化侵权风险 Log: 切换后端至PaddleOCR-NCNN，切换工程为CMake Change-Id: I4d5d2c5d37505a4a24b389b1a4c5d12f17bfa38c
452 lines
17 KiB
C++
452 lines
17 KiB
C++
// 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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#include "test_precomp.hpp"
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namespace opencv_test { namespace {
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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[i], 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_LE(cvtest::norm(img, img2, NORM_INF | NORM_RELATIVE), 1e-3);
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EXPECT_EQ(0, remove(filenameOutput.c_str()));
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}
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TEST(Imgcodecs_Tiff, readWrite_64FC1)
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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/test64FC1.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_64FC1, 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_LE(cvtest::norm(img, img2, NORM_INF | NORM_RELATIVE), 1e-3);
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EXPECT_EQ(0, remove(filenameOutput.c_str()));
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}
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TEST(Imgcodecs_Tiff, readWrite_32FC3_SGILOG)
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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/test32FC3_sgilog.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_32FC3, 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_LE(cvtest::norm(img, img2, NORM_INF | NORM_RELATIVE), 0.01);
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EXPECT_EQ(0, remove(filenameOutput.c_str()));
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}
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TEST(Imgcodecs_Tiff, readWrite_32FC3_RAW)
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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/test32FC3_raw.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_32FC3, img.type());
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std::vector<int> params;
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params.push_back(IMWRITE_TIFF_COMPRESSION);
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params.push_back(1/*COMPRESSION_NONE*/);
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ASSERT_TRUE(cv::imwrite(filenameOutput, img, params));
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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_LE(cvtest::norm(img, img2, NORM_INF | NORM_RELATIVE), 1e-3);
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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_Modes, write_multipage)
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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 + "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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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]);
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pages.push_back(page);
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}
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string tmp_filename = cv::tempfile(".tiff");
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bool res = imwrite(tmp_filename, pages);
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ASSERT_TRUE(res);
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vector<Mat> read_pages;
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imreadmulti(tmp_filename, read_pages);
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for (size_t i = 0; i < page_count; i++)
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{
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EXPECT_PRED_FORMAT2(cvtest::MatComparator(0, 0), read_pages[i], pages[i]);
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}
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}
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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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TEST(Imgcodecs_Tiff, decode_black_and_write_image_pr12989_grayscale)
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{
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const string filename = cvtest::findDataFile("readwrite/bitsperpixel1.tiff");
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cv::Mat img;
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ASSERT_NO_THROW(img = cv::imread(filename, IMREAD_GRAYSCALE));
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ASSERT_FALSE(img.empty());
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EXPECT_EQ(64, img.cols);
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EXPECT_EQ(64, img.rows);
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EXPECT_EQ(CV_8UC1, img.type()) << cv::typeToString(img.type());
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// Check for 0/255 values only: 267 + 3829 = 64*64
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EXPECT_EQ(267, countNonZero(img == 0));
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EXPECT_EQ(3829, countNonZero(img == 255));
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}
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TEST(Imgcodecs_Tiff, decode_black_and_write_image_pr12989_default)
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{
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const string filename = cvtest::findDataFile("readwrite/bitsperpixel1.tiff");
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cv::Mat img;
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ASSERT_NO_THROW(img = cv::imread(filename)); // by default image type is CV_8UC3
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ASSERT_FALSE(img.empty());
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EXPECT_EQ(64, img.cols);
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EXPECT_EQ(64, img.rows);
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EXPECT_EQ(CV_8UC3, img.type()) << cv::typeToString(img.type());
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}
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TEST(Imgcodecs_Tiff, decode_black_and_write_image_pr17275_grayscale)
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{
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const string filename = cvtest::findDataFile("readwrite/bitsperpixel1_min.tiff");
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cv::Mat img;
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ASSERT_NO_THROW(img = cv::imread(filename, IMREAD_GRAYSCALE));
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ASSERT_FALSE(img.empty());
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EXPECT_EQ(64, img.cols);
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EXPECT_EQ(64, img.rows);
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EXPECT_EQ(CV_8UC1, img.type()) << cv::typeToString(img.type());
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// Check for 0/255 values only: 267 + 3829 = 64*64
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EXPECT_EQ(267, countNonZero(img == 0));
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EXPECT_EQ(3829, countNonZero(img == 255));
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}
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TEST(Imgcodecs_Tiff, decode_black_and_write_image_pr17275_default)
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{
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const string filename = cvtest::findDataFile("readwrite/bitsperpixel1_min.tiff");
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cv::Mat img;
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ASSERT_NO_THROW(img = cv::imread(filename)); // by default image type is CV_8UC3
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ASSERT_FALSE(img.empty());
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EXPECT_EQ(64, img.cols);
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EXPECT_EQ(64, img.rows);
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EXPECT_EQ(CV_8UC3, img.type()) << cv::typeToString(img.type());
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}
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TEST(Imgcodecs_Tiff, count_multipage)
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{
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const string root = cvtest::TS::ptr()->get_data_path();
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{
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const string filename = root + "readwrite/multipage.tif";
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ASSERT_EQ((size_t)6, imcount(filename));
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}
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{
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const string filename = root + "readwrite/test32FC3_raw.tiff";
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ASSERT_EQ((size_t)1, imcount(filename));
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}
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}
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TEST(Imgcodecs_Tiff, read_multipage_indexed)
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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 + "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 int page_count = sizeof(page_files) / sizeof(page_files[0]);
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vector<Mat> single_pages;
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for (int i = 0; i < page_count; i++)
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{
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// imread and imreadmulti have different default values for the flag
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const Mat page = imread(root + page_files[i], IMREAD_ANYCOLOR);
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single_pages.push_back(page);
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}
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ASSERT_EQ((size_t)page_count, single_pages.size());
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{
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SCOPED_TRACE("Edge Cases");
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vector<Mat> multi_pages;
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bool res = imreadmulti(filename, multi_pages, 0, 0);
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// If we asked for 0 images and we successfully read 0 images should this be false ?
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ASSERT_TRUE(res == false);
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ASSERT_EQ((size_t)0, multi_pages.size());
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res = imreadmulti(filename, multi_pages, 0, 123123);
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ASSERT_TRUE(res == true);
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ASSERT_EQ((size_t)6, multi_pages.size());
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}
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|
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{
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SCOPED_TRACE("Read all with indices");
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vector<Mat> multi_pages;
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bool res = imreadmulti(filename, multi_pages, 0, 6);
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ASSERT_TRUE(res == true);
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ASSERT_EQ((size_t)page_count, multi_pages.size());
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for (int i = 0; i < page_count; i++)
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{
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EXPECT_PRED_FORMAT2(cvtest::MatComparator(0, 0), multi_pages[i], single_pages[i]);
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}
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}
|
|
|
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{
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SCOPED_TRACE("Read one by one");
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|
vector<Mat> multi_pages;
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|
for (int i = 0; i < page_count; i++)
|
|
{
|
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bool res = imreadmulti(filename, multi_pages, i, 1);
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ASSERT_TRUE(res == true);
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ASSERT_EQ((size_t)1, multi_pages.size());
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EXPECT_PRED_FORMAT2(cvtest::MatComparator(0, 0), multi_pages[0], single_pages[i]);
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multi_pages.clear();
|
|
}
|
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}
|
|
|
|
{
|
|
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());
|
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EXPECT_PRED_FORMAT2(cvtest::MatComparator(0, 0), multi_pages[0], single_pages[i * 2]) << i;
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EXPECT_PRED_FORMAT2(cvtest::MatComparator(0, 0), multi_pages[1], single_pages[i * 2 + 1]);
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|
multi_pages.clear();
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|
}
|
|
}
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}
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#endif
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}} // namespace
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