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[GSOC 2025] PNG&WebP Metadata Reading Writing Improvements #27503 Merge with https://github.com/opencv/opencv_extra/pull/1271 ### Pull Request Readiness Checklist See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request - [x] I agree to contribute to the project under Apache 2 License. - [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV - [x] The PR is proposed to the proper branch - [ ] There is a reference to the original bug report and related work - [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable Patch to opencv_extra has the same branch name. - [ ] The feature is well documented and sample code can be built with the project CMake
582 lines
21 KiB
C++
582 lines
21 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
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// directory of this distribution and at http://opencv.org/license.html
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#include <string>
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#include <vector>
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#include "test_precomp.hpp"
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namespace opencv_test { namespace {
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static Mat makeCirclesImage(Size size, int type, int nbits)
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{
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Mat img(size, type);
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img.setTo(Scalar::all(0));
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RNG& rng = theRNG();
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int maxval = (int)(1 << nbits);
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for (int i = 0; i < 100; i++) {
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int x = rng.uniform(0, img.cols);
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int y = rng.uniform(0, img.rows);
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int radius = rng.uniform(5, std::min(img.cols, img.rows) / 5);
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int b = rng.uniform(0, maxval);
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int g = rng.uniform(0, maxval);
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int r = rng.uniform(0, maxval);
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circle(img, Point(x, y), radius, Scalar(b, g, r), -1, LINE_AA);
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}
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return img;
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}
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static std::vector<uchar> getSampleExifData() {
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return {
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'M', 'M', 0, '*', 0, 0, 0, 8, 0, 10, 1, 0, 0, 4, 0, 0, 0, 1, 0, 0, 5,
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0, 1, 1, 0, 4, 0, 0, 0, 1, 0, 0, 2, 208, 1, 2, 0, 3, 0, 0, 0, 1,
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0, 10, 0, 0, 1, 18, 0, 3, 0, 0, 0, 1, 0, 1, 0, 0, 1, 14, 0, 2, 0, 0,
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0, '"', 0, 0, 0, 176, 1, '1', 0, 2, 0, 0, 0, 7, 0, 0, 0, 210, 1, 26,
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0, 5, 0, 0, 0, 1, 0, 0, 0, 218, 1, 27, 0, 5, 0, 0, 0, 1, 0, 0, 0,
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226, 1, '(', 0, 3, 0, 0, 0, 1, 0, 2, 0, 0, 135, 'i', 0, 4, 0, 0, 0,
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1, 0, 0, 0, 134, 0, 0, 0, 0, 0, 3, 144, 0, 0, 7, 0, 0, 0, 4, '0', '2',
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'2', '1', 160, 2, 0, 4, 0, 0, 0, 1, 0, 0, 5, 0, 160, 3, 0, 4, 0, 0,
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0, 1, 0, 0, 2, 208, 0, 0, 0, 0, 'S', 'a', 'm', 'p', 'l', 'e', ' ', '1', '0',
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'-', 'b', 'i', 't', ' ', 'i', 'm', 'a', 'g', 'e', ' ', 'w', 'i', 't', 'h', ' ',
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'm', 'e', 't', 'a', 'd', 'a', 't', 'a', 0, 'O', 'p', 'e', 'n', 'C', 'V', 0, 0,
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0, 0, 0, 'H', 0, 0, 0, 1, 0, 0, 0, 'H', 0, 0, 0, 1
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};
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}
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static std::vector<uchar> getSampleXmpData() {
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return {
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'<','x',':','x','m','p','m','e','t','a',' ','x','m','l','n','s',':','x','=',
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'"','a','d','o','b','e',':','x','m','p','"','>',
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'<','x','m','p',':','C','r','e','a','t','o','r','T','o','o','l','>',
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'O','p','e','n','C','V',
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'<','/','x','m','p',':','C','r','e','a','t','o','r','T','o','o','l','>',
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'<','/','x',':','x','m','p','m','e','t','a','>',0
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};
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}
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// Returns a Minimal ICC profile data (Generated with help from ChatGPT)
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static std::vector<uchar> getSampleIccpData() {
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std::vector<uchar> iccp_data(192, 0);
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iccp_data[3] = 192; // Profile size: 192 bytes
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iccp_data[12] = 'm';
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iccp_data[13] = 'n';
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iccp_data[14] = 't';
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iccp_data[15] = 'r';
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iccp_data[16] = 'R';
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iccp_data[17] = 'G';
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iccp_data[18] = 'B';
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iccp_data[19] = ' ';
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iccp_data[20] = 'X';
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iccp_data[21] = 'Y';
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iccp_data[22] = 'Z';
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iccp_data[23] = ' ';
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// File signature 'acsp' at offset 36 (0x24)
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iccp_data[36] = 'a';
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iccp_data[37] = 'c';
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iccp_data[38] = 's';
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iccp_data[39] = 'p';
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// Illuminant D50 at offset 68 (0x44), example values:
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iccp_data[68] = 0x00;
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iccp_data[69] = 0x00;
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iccp_data[70] = 0xF6;
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iccp_data[71] = 0xD6; // 0.9642
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iccp_data[72] = 0x00;
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iccp_data[73] = 0x01;
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iccp_data[74] = 0x00;
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iccp_data[75] = 0x00; // 1.0
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iccp_data[76] = 0x00;
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iccp_data[77] = 0x00;
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iccp_data[78] = 0xD3;
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iccp_data[79] = 0x2D; // 0.8249
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// Tag count at offset 128 (0x80) = 1
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iccp_data[131] = 1;
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// Tag record at offset 132 (0x84): signature 'desc', offset 128, size 64
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iccp_data[132] = 'd';
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iccp_data[133] = 'e';
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iccp_data[134] = 's';
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iccp_data[135] = 'c';
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iccp_data[139] = 128; // offset
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iccp_data[143] = 64; // size
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// Tag data 'desc' at offset 128 (start of tag data)
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// Set type 'desc' etc. here, for simplicity fill zeros
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iccp_data[144] = 'd';
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iccp_data[145] = 'e';
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iccp_data[146] = 's';
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iccp_data[147] = 'c';
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// ASCII string length at offset 156
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iccp_data[156] = 20; // length
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// ASCII string "Minimal ICC Profile" starting at offset 160
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iccp_data[160] = 'M';
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iccp_data[161] = 'i';
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iccp_data[162] = 'n';
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iccp_data[163] = 'i';
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iccp_data[164] = 'm';
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iccp_data[165] = 'a';
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iccp_data[166] = 'l';
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iccp_data[167] = ' ';
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iccp_data[168] = 'I';
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iccp_data[169] = 'C';
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iccp_data[170] = 'C';
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iccp_data[171] = ' ';
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iccp_data[172] = 'P';
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iccp_data[173] = 'r';
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iccp_data[174] = 'o';
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iccp_data[175] = 'f';
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iccp_data[176] = 'i';
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iccp_data[177] = 'l';
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iccp_data[178] = 'e';
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return iccp_data;
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}
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/**
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* Test to check whether the EXIF orientation tag was processed successfully or not.
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* The test uses a set of 8 images named testExifOrientation_{1 to 8}.(extension).
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* Each test image is a 10x10 square, divided into four smaller sub-squares:
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* (R corresponds to Red, G to Green, B to Blue, W to White)
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* --------- ---------
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* | R | G | | G | R |
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* |-------| - (tag 1) |-------| - (tag 2)
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* | B | W | | W | B |
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* --------- ---------
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*
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* --------- ---------
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* | W | B | | B | W |
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* |-------| - (tag 3) |-------| - (tag 4)
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* | G | R | | R | G |
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* --------- ---------
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*
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* --------- ---------
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* | R | B | | G | W |
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* |-------| - (tag 5) |-------| - (tag 6)
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* | G | W | | R | B |
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* --------- ---------
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*
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* --------- ---------
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* | W | G | | B | R |
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* |-------| - (tag 7) |-------| - (tag 8)
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* | B | R | | W | G |
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* --------- ---------
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*
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*
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* Each image contains an EXIF field with an orientation tag (0x112).
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* After reading each image and applying the orientation tag,
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* the resulting image should be:
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* ---------
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* | R | G |
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* |-------|
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* | B | W |
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* ---------
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*
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* Note:
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* The flags parameter of the imread function is set as IMREAD_COLOR | IMREAD_ANYCOLOR | IMREAD_ANYDEPTH.
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* Using this combination is an undocumented trick to load images similarly to the IMREAD_UNCHANGED flag,
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* preserving the alpha channel (if present) while also applying the orientation.
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*/
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typedef testing::TestWithParam<string> Exif;
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TEST_P(Exif, exif_orientation)
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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 + GetParam();
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const int colorThresholdHigh = 250;
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const int colorThresholdLow = 5;
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// Refer to the note in the explanation above.
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Mat m_img = imread(filename, IMREAD_COLOR | IMREAD_ANYCOLOR | IMREAD_ANYDEPTH);
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ASSERT_FALSE(m_img.empty());
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if (m_img.channels() == 3)
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{
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Vec3b vec;
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//Checking the first quadrant (with supposed red)
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vec = m_img.at<Vec3b>(2, 2); //some point inside the square
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EXPECT_LE(vec.val[0], colorThresholdLow);
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EXPECT_LE(vec.val[1], colorThresholdLow);
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EXPECT_GE(vec.val[2], colorThresholdHigh);
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//Checking the second quadrant (with supposed green)
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vec = m_img.at<Vec3b>(2, 7); //some point inside the square
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EXPECT_LE(vec.val[0], colorThresholdLow);
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EXPECT_GE(vec.val[1], colorThresholdHigh);
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EXPECT_LE(vec.val[2], colorThresholdLow);
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//Checking the third quadrant (with supposed blue)
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vec = m_img.at<Vec3b>(7, 2); //some point inside the square
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EXPECT_GE(vec.val[0], colorThresholdHigh);
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EXPECT_LE(vec.val[1], colorThresholdLow);
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EXPECT_LE(vec.val[2], colorThresholdLow);
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}
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else
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{
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Vec4b vec;
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//Checking the first quadrant (with supposed red)
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vec = m_img.at<Vec4b>(2, 2); //some point inside the square
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EXPECT_LE(vec.val[0], colorThresholdLow);
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EXPECT_LE(vec.val[1], colorThresholdLow);
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EXPECT_GE(vec.val[2], colorThresholdHigh);
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//Checking the second quadrant (with supposed green)
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vec = m_img.at<Vec4b>(2, 7); //some point inside the square
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EXPECT_LE(vec.val[0], colorThresholdLow);
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EXPECT_GE(vec.val[1], colorThresholdHigh);
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EXPECT_LE(vec.val[2], colorThresholdLow);
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//Checking the third quadrant (with supposed blue)
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vec = m_img.at<Vec4b>(7, 2); //some point inside the square
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EXPECT_GE(vec.val[0], colorThresholdHigh);
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EXPECT_LE(vec.val[1], colorThresholdLow);
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EXPECT_LE(vec.val[2], colorThresholdLow);
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}
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}
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const std::vector<std::string> exif_files
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{
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#ifdef HAVE_JPEG
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"readwrite/testExifOrientation_1.jpg",
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"readwrite/testExifOrientation_2.jpg",
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"readwrite/testExifOrientation_3.jpg",
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"readwrite/testExifOrientation_4.jpg",
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"readwrite/testExifOrientation_5.jpg",
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"readwrite/testExifOrientation_6.jpg",
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"readwrite/testExifOrientation_7.jpg",
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"readwrite/testExifOrientation_8.jpg",
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#endif
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#ifdef OPENCV_IMGCODECS_PNG_WITH_EXIF
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"readwrite/testExifOrientation_1.png",
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"readwrite/testExifOrientation_2.png",
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"readwrite/testExifOrientation_3.png",
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"readwrite/testExifOrientation_4.png",
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"readwrite/testExifOrientation_5.png",
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"readwrite/testExifOrientation_6.png",
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"readwrite/testExifOrientation_7.png",
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"readwrite/testExifOrientation_8.png",
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#endif
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#ifdef HAVE_AVIF
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"readwrite/testExifOrientation_1.avif",
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"readwrite/testExifOrientation_2.avif",
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"readwrite/testExifOrientation_3.avif",
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"readwrite/testExifOrientation_4.avif",
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"readwrite/testExifOrientation_5.avif",
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"readwrite/testExifOrientation_6.avif",
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"readwrite/testExifOrientation_7.avif",
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"readwrite/testExifOrientation_8.avif",
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#endif
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#ifdef HAVE_WEBP
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"readwrite/testExifOrientation_1.webp",
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"readwrite/testExifOrientation_2.webp",
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"readwrite/testExifOrientation_3.webp",
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"readwrite/testExifOrientation_4.webp",
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"readwrite/testExifOrientation_5.webp",
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"readwrite/testExifOrientation_6.webp",
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"readwrite/testExifOrientation_7.webp",
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"readwrite/testExifOrientation_8.webp",
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#endif
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};
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INSTANTIATE_TEST_CASE_P(Imgcodecs, Exif,
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testing::ValuesIn(exif_files));
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#ifdef HAVE_AVIF
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TEST(Imgcodecs_Avif, ReadWriteWithExif)
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{
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int avif_nbits = 10;
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int avif_speed = 10;
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int avif_quality = 85;
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int imgdepth = avif_nbits > 8 ? CV_16U : CV_8U;
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int imgtype = CV_MAKETYPE(imgdepth, 3);
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const string outputname = cv::tempfile(".avif");
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Mat img = makeCirclesImage(Size(1280, 720), imgtype, avif_nbits);
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std::vector<int> metadata_types = {IMAGE_METADATA_EXIF};
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std::vector<std::vector<uchar>> metadata = {
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getSampleExifData() };
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std::vector<int> write_params = {
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IMWRITE_AVIF_DEPTH, avif_nbits,
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IMWRITE_AVIF_SPEED, avif_speed,
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IMWRITE_AVIF_QUALITY, avif_quality
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};
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imwriteWithMetadata(outputname, img, metadata_types, metadata, write_params);
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std::vector<uchar> compressed;
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imencodeWithMetadata(outputname, img, metadata_types, metadata, compressed, write_params);
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std::vector<int> read_metadata_types, read_metadata_types2;
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std::vector<std::vector<uchar> > read_metadata, read_metadata2;
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Mat img2 = imreadWithMetadata(outputname, read_metadata_types, read_metadata, IMREAD_UNCHANGED);
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Mat img3 = imdecodeWithMetadata(compressed, read_metadata_types2, read_metadata2, IMREAD_UNCHANGED);
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EXPECT_EQ(img2.cols, img.cols);
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EXPECT_EQ(img2.rows, img.rows);
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EXPECT_EQ(img2.type(), imgtype);
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EXPECT_EQ(read_metadata_types, read_metadata_types2);
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EXPECT_GE(read_metadata_types.size(), 1u);
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EXPECT_EQ(read_metadata, read_metadata2);
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EXPECT_EQ(read_metadata_types[0], IMAGE_METADATA_EXIF);
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EXPECT_EQ(read_metadata_types.size(), read_metadata.size());
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EXPECT_EQ(read_metadata[0], metadata[0]);
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EXPECT_EQ(cv::norm(img2, img3, NORM_INF), 0.);
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double mse = cv::norm(img, img2, NORM_L2SQR)/(img.rows*img.cols);
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EXPECT_LT(mse, 1500);
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remove(outputname.c_str());
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}
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#endif // HAVE_AVIF
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#ifdef HAVE_WEBP
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TEST(Imgcodecs_WebP, Read_Write_With_Exif_Xmp_Iccp)
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{
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int imgtype = CV_MAKETYPE(CV_8U, 3);
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const std::string outputname = cv::tempfile(".webp");
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cv::Mat img = makeCirclesImage(cv::Size(160, 120), imgtype, 8);
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std::vector<int> metadata_types = {IMAGE_METADATA_EXIF, IMAGE_METADATA_XMP, IMAGE_METADATA_ICCP};
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std::vector<std::vector<uchar>> metadata = {
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getSampleExifData(),
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getSampleXmpData(),
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getSampleIccpData()
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};
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int webp_quality = 101; // 101 is lossless compression
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std::vector<int> write_params = {IMWRITE_WEBP_QUALITY, webp_quality};
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imwriteWithMetadata(outputname, img, metadata_types, metadata, write_params);
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std::vector<uchar> compressed;
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imencodeWithMetadata(outputname, img, metadata_types, metadata, compressed, write_params);
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std::vector<int> read_metadata_types, read_metadata_types2;
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std::vector<std::vector<uchar>> read_metadata, read_metadata2;
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cv::Mat img2 = imreadWithMetadata(outputname, read_metadata_types, read_metadata, cv::IMREAD_UNCHANGED);
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cv::Mat img3 = imdecodeWithMetadata(compressed, read_metadata_types2, read_metadata2, cv::IMREAD_UNCHANGED);
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EXPECT_EQ(img2.cols, img.cols);
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EXPECT_EQ(img2.rows, img.rows);
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EXPECT_EQ(img2.type(), imgtype);
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EXPECT_EQ(read_metadata_types, read_metadata_types2);
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EXPECT_EQ(read_metadata_types.size(), 3u);
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EXPECT_EQ(read_metadata, read_metadata2);
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EXPECT_EQ(read_metadata, metadata);
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EXPECT_EQ(cv::norm(img2, img3, cv::NORM_INF), 0.0);
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double mse = cv::norm(img, img2, cv::NORM_L2SQR) / (img.rows * img.cols);
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EXPECT_EQ(mse, 0);
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remove(outputname.c_str());
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}
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#endif // HAVE_WEBP
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TEST(Imgcodecs_Jpeg, Read_Write_With_Exif)
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{
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int jpeg_quality = 95;
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int imgtype = CV_MAKETYPE(CV_8U, 3);
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const string outputname = cv::tempfile(".jpeg");
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Mat img = makeCirclesImage(Size(1280, 720), imgtype, 8);
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std::vector<int> metadata_types = {IMAGE_METADATA_EXIF};
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std::vector<std::vector<uchar>> metadata = {
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getSampleExifData() };
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std::vector<int> write_params = {
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IMWRITE_JPEG_QUALITY, jpeg_quality
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};
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imwriteWithMetadata(outputname, img, metadata_types, metadata, write_params);
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std::vector<uchar> compressed;
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imencodeWithMetadata(outputname, img, metadata_types, metadata, compressed, write_params);
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std::vector<int> read_metadata_types, read_metadata_types2;
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std::vector<std::vector<uchar> > read_metadata, read_metadata2;
|
|
Mat img2 = imreadWithMetadata(outputname, read_metadata_types, read_metadata, IMREAD_UNCHANGED);
|
|
Mat img3 = imdecodeWithMetadata(compressed, read_metadata_types2, read_metadata2, IMREAD_UNCHANGED);
|
|
EXPECT_EQ(img2.cols, img.cols);
|
|
EXPECT_EQ(img2.rows, img.rows);
|
|
EXPECT_EQ(img2.type(), imgtype);
|
|
EXPECT_EQ(read_metadata_types, read_metadata_types2);
|
|
EXPECT_GE(read_metadata_types.size(), 1u);
|
|
EXPECT_EQ(read_metadata, read_metadata2);
|
|
EXPECT_EQ(read_metadata_types[0], IMAGE_METADATA_EXIF);
|
|
EXPECT_EQ(read_metadata_types.size(), read_metadata.size());
|
|
EXPECT_EQ(read_metadata[0], metadata[0]);
|
|
EXPECT_EQ(cv::norm(img2, img3, NORM_INF), 0.);
|
|
double mse = cv::norm(img, img2, NORM_L2SQR)/(img.rows*img.cols);
|
|
EXPECT_LT(mse, 80);
|
|
remove(outputname.c_str());
|
|
}
|
|
|
|
TEST(Imgcodecs_Png, Read_Write_With_Exif)
|
|
{
|
|
int png_compression = 3;
|
|
int imgtype = CV_MAKETYPE(CV_8U, 3);
|
|
const string outputname = cv::tempfile(".png");
|
|
Mat img = makeCirclesImage(Size(160, 120), imgtype, 8);
|
|
|
|
std::vector<int> metadata_types = {IMAGE_METADATA_EXIF};
|
|
std::vector<std::vector<uchar>> metadata = {
|
|
getSampleExifData() };
|
|
|
|
std::vector<int> write_params = {
|
|
IMWRITE_PNG_COMPRESSION, png_compression
|
|
};
|
|
|
|
imwriteWithMetadata(outputname, img, metadata_types, metadata, write_params);
|
|
std::vector<uchar> compressed;
|
|
imencodeWithMetadata(outputname, img, metadata_types, metadata, compressed, write_params);
|
|
|
|
std::vector<int> read_metadata_types, read_metadata_types2;
|
|
std::vector<std::vector<uchar> > read_metadata, read_metadata2;
|
|
Mat img2 = imreadWithMetadata(outputname, read_metadata_types, read_metadata, IMREAD_UNCHANGED);
|
|
Mat img3 = imdecodeWithMetadata(compressed, read_metadata_types2, read_metadata2, IMREAD_UNCHANGED);
|
|
EXPECT_EQ(img2.cols, img.cols);
|
|
EXPECT_EQ(img2.rows, img.rows);
|
|
EXPECT_EQ(img2.type(), imgtype);
|
|
EXPECT_EQ(read_metadata_types, read_metadata_types2);
|
|
EXPECT_GE(read_metadata_types.size(), 1u);
|
|
EXPECT_EQ(read_metadata, read_metadata2);
|
|
EXPECT_EQ(read_metadata_types[0], IMAGE_METADATA_EXIF);
|
|
EXPECT_EQ(read_metadata_types.size(), read_metadata.size());
|
|
EXPECT_EQ(read_metadata[0], metadata[0]);
|
|
EXPECT_EQ(cv::norm(img2, img3, NORM_INF), 0.);
|
|
double mse = cv::norm(img, img2, NORM_L2SQR)/(img.rows*img.cols);
|
|
EXPECT_EQ(mse, 0); // png is lossless
|
|
remove(outputname.c_str());
|
|
}
|
|
|
|
TEST(Imgcodecs_Png, Read_Write_With_Exif_Xmp_Iccp)
|
|
{
|
|
int png_compression = 3;
|
|
int imgtype = CV_MAKETYPE(CV_8U, 3);
|
|
const string outputname = cv::tempfile(".png");
|
|
Mat img = makeCirclesImage(Size(160, 120), imgtype, 8);
|
|
|
|
std::vector<int> metadata_types = { IMAGE_METADATA_EXIF, IMAGE_METADATA_XMP, IMAGE_METADATA_ICCP };
|
|
std::vector<std::vector<uchar>> metadata = {
|
|
getSampleExifData(),
|
|
getSampleXmpData(),
|
|
getSampleIccpData(),
|
|
};
|
|
|
|
std::vector<int> write_params = {
|
|
IMWRITE_PNG_COMPRESSION, png_compression
|
|
};
|
|
|
|
imwriteWithMetadata(outputname, img, metadata_types, metadata, write_params);
|
|
std::vector<uchar> compressed;
|
|
imencodeWithMetadata(outputname, img, metadata_types, metadata, compressed, write_params);
|
|
|
|
std::vector<int> read_metadata_types, read_metadata_types2;
|
|
std::vector<std::vector<uchar> > read_metadata, read_metadata2;
|
|
Mat img2 = imreadWithMetadata(outputname, read_metadata_types, read_metadata, IMREAD_UNCHANGED);
|
|
Mat img3 = imdecodeWithMetadata(compressed, read_metadata_types2, read_metadata2, IMREAD_UNCHANGED);
|
|
EXPECT_EQ(img2.cols, img.cols);
|
|
EXPECT_EQ(img2.rows, img.rows);
|
|
EXPECT_EQ(img2.type(), imgtype);
|
|
|
|
EXPECT_EQ(metadata_types, read_metadata_types);
|
|
EXPECT_EQ(read_metadata_types, read_metadata_types2);
|
|
EXPECT_EQ(metadata, read_metadata);
|
|
remove(outputname.c_str());
|
|
}
|
|
|
|
TEST(Imgcodecs_Png, Read_Exif_From_Text)
|
|
{
|
|
const string root = cvtest::TS::ptr()->get_data_path();
|
|
const string filename = root + "../perf/320x260.png";
|
|
const string dst_file = cv::tempfile(".png");
|
|
|
|
std::vector<uchar> exif_data =
|
|
{ 'M' , 'M' , 0, '*' , 0, 0, 0, 8, 0, 4, 1,
|
|
26, 0, 5, 0, 0, 0, 1, 0, 0, 0, 62, 1, 27, 0, 5, 0, 0, 0, 1, 0, 0, 0,
|
|
70, 1, 40, 0, 3, 0, 0, 0, 1, 0, 2, 0, 0, 1, 49, 0, 2, 0, 0, 0, 18, 0,
|
|
0, 0, 78, 0, 0, 0, 0, 0, 0, 0, 96, 0, 0, 0, 1, 0, 0, 0, 96, 0, 0, 0,
|
|
1, 80, 97, 105, 110, 116, 46, 78, 69, 84, 32, 118, 51, 46, 53, 46, 49, 48, 0
|
|
};
|
|
|
|
std::vector<int> read_metadata_types;
|
|
std::vector<std::vector<uchar> > read_metadata;
|
|
Mat img = imreadWithMetadata(filename, read_metadata_types, read_metadata, IMREAD_GRAYSCALE);
|
|
|
|
std::vector<int> metadata_types = { IMAGE_METADATA_EXIF };
|
|
EXPECT_EQ(read_metadata_types, metadata_types);
|
|
EXPECT_EQ(read_metadata[0], exif_data);
|
|
}
|
|
|
|
static size_t locateString(const uchar* exif, size_t exif_size, const std::string& pattern)
|
|
{
|
|
size_t plen = pattern.size();
|
|
for (size_t i = 0; i + plen <= exif_size; i++) {
|
|
if (exif[i] == pattern[0] && memcmp(&exif[i], pattern.c_str(), plen) == 0)
|
|
return i;
|
|
}
|
|
return 0xFFFFFFFFu;
|
|
}
|
|
|
|
typedef std::tuple<std::string, size_t, std::string, size_t> ReadExif_Sanity_Params;
|
|
typedef testing::TestWithParam<ReadExif_Sanity_Params> ReadExif_Sanity;
|
|
|
|
TEST_P(ReadExif_Sanity, Check)
|
|
{
|
|
std::string filename = get<0>(GetParam());
|
|
size_t exif_size = get<1>(GetParam());
|
|
std::string pattern = get<2>(GetParam());
|
|
size_t ploc = get<3>(GetParam());
|
|
|
|
const string root = cvtest::TS::ptr()->get_data_path();
|
|
filename = root + filename;
|
|
|
|
std::vector<int> metadata_types;
|
|
std::vector<Mat> metadata;
|
|
Mat img = imreadWithMetadata(filename, metadata_types, metadata, 1);
|
|
|
|
EXPECT_EQ(img.type(), CV_8UC3);
|
|
ASSERT_GE(metadata_types.size(), 1u);
|
|
EXPECT_EQ(metadata_types.size(), metadata.size());
|
|
const Mat& exif = metadata[IMAGE_METADATA_EXIF];
|
|
EXPECT_EQ(exif.type(), CV_8U);
|
|
EXPECT_EQ(exif.total(), exif_size);
|
|
ASSERT_GE(exif_size, 26u); // minimal exif should take at least 26 bytes
|
|
// (the header + IDF0 with at least 1 entry).
|
|
EXPECT_TRUE(exif.data[0] == 'I' || exif.data[0] == 'M');
|
|
EXPECT_EQ(exif.data[0], exif.data[1]);
|
|
EXPECT_EQ(locateString(exif.data, exif_size, pattern), ploc);
|
|
}
|
|
|
|
static const std::vector<ReadExif_Sanity_Params> exif_sanity_params
|
|
{
|
|
#ifdef HAVE_JPEG
|
|
{"readwrite/testExifOrientation_3.jpg", 916, "Photoshop", 120},
|
|
#endif
|
|
#ifdef OPENCV_IMGCODECS_PNG_WITH_EXIF
|
|
{"readwrite/testExifOrientation_5.png", 112, "ExifTool", 102},
|
|
#endif
|
|
#ifdef HAVE_AVIF
|
|
{"readwrite/testExifOrientation_7.avif", 913, "Photoshop", 120},
|
|
#endif
|
|
};
|
|
|
|
INSTANTIATE_TEST_CASE_P(Imgcodecs, ReadExif_Sanity,
|
|
testing::ValuesIn(exif_sanity_params));
|
|
|
|
}}
|