mirror of https://github.com/opencv/opencv.git
Open Source Computer Vision Library
https://opencv.org/
You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
221 lines
8.9 KiB
221 lines
8.9 KiB
/*M/////////////////////////////////////////////////////////////////////////////////////// |
|
// |
|
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. |
|
// |
|
// By downloading, copying, installing or using the software you agree to this license. |
|
// If you do not agree to this license, do not download, install, |
|
// copy or use the software. |
|
// |
|
// |
|
// License Agreement |
|
// For Open Source Computer Vision Library |
|
// |
|
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. |
|
// Copyright (C) 2009, Willow Garage Inc., all rights reserved. |
|
// Third party copyrights are property of their respective owners. |
|
// |
|
// Redistribution and use in source and binary forms, with or without modification, |
|
// are permitted provided that the following conditions are met: |
|
// |
|
// * Redistribution's of source code must retain the above copyright notice, |
|
// this list of conditions and the following disclaimer. |
|
// |
|
// * Redistribution's in binary form must reproduce the above copyright notice, |
|
// this list of conditions and the following disclaimer in the documentation |
|
// and/or other materials provided with the distribution. |
|
// |
|
// * The name of the copyright holders may not be used to endorse or promote products |
|
// derived from this software without specific prior written permission. |
|
// |
|
// This software is provided by the copyright holders and contributors "as is" and |
|
// any express or implied warranties, including, but not limited to, the implied |
|
// warranties of merchantability and fitness for a particular purpose are disclaimed. |
|
// In no event shall the Intel Corporation or contributors be liable for any direct, |
|
// indirect, incidental, special, exemplary, or consequential damages |
|
// (including, but not limited to, procurement of substitute goods or services; |
|
// loss of use, data, or profits; or business interruption) however caused |
|
// and on any theory of liability, whether in contract, strict liability, |
|
// or tort (including negligence or otherwise) arising in any way out of |
|
// the use of this software, even if advised of the possibility of such damage. |
|
// |
|
//M*/ |
|
|
|
#include "test_precomp.hpp" |
|
#include "opencv2/highgui/highgui.hpp" |
|
|
|
using namespace cv; |
|
using namespace std; |
|
|
|
class CV_FFmpegWriteBigImageTest : public cvtest::BaseTest |
|
{ |
|
public: |
|
void run(int) |
|
{ |
|
try |
|
{ |
|
ts->printf(cvtest::TS::LOG, "start reading bit image\n"); |
|
Mat img = imread(string(ts->get_data_path()) + "readwrite/read.png"); |
|
ts->printf(cvtest::TS::LOG, "finish reading bit image\n"); |
|
if (img.empty()) ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_TEST_DATA); |
|
ts->printf(cvtest::TS::LOG, "start writing bit image\n"); |
|
imwrite(string(ts->get_data_path()) + "readwrite/write.png", img); |
|
ts->printf(cvtest::TS::LOG, "finish writing bit image\n"); |
|
} |
|
catch(...) |
|
{ |
|
ts->set_failed_test_info(cvtest::TS::FAIL_EXCEPTION); |
|
} |
|
ts->set_failed_test_info(cvtest::TS::OK); |
|
} |
|
}; |
|
|
|
class CV_FFmpegWriteBigVideoTest : public cvtest::BaseTest |
|
{ |
|
public: |
|
void run(int) |
|
{ |
|
const int img_r = 4096; |
|
const int img_c = 4096; |
|
Size frame_s = Size(img_c, img_r); |
|
const double fps = 30; |
|
const double time_sec = 2; |
|
const int coeff = static_cast<int>(static_cast<double>(cv::min(img_c, img_r)) / (fps * time_sec)); |
|
|
|
Mat img(img_r, img_c, CV_8UC3, Scalar::all(0)); |
|
try |
|
{ |
|
VideoWriter writer(string(ts->get_data_path()) + "video/output.avi", CV_FOURCC('X', 'V', 'I', 'D'), fps, frame_s); |
|
|
|
if (writer.isOpened() == false) ts->set_failed_test_info(cvtest::TS::FAIL_EXCEPTION); |
|
|
|
for (int i = 0 ; i < static_cast<int>(fps * time_sec); i++ ) |
|
{ |
|
//circle(img, Point2i(img_c / 2, img_r / 2), cv::min(img_r, img_c) / 2 * (i + 1), Scalar(255, 0, 0, 0), 2); |
|
rectangle(img, Point2i(coeff * i, coeff * i), Point2i(coeff * (i + 1), coeff * (i + 1)), |
|
Scalar::all(255 * (1.0 - static_cast<double>(i) / (fps * time_sec * 2) )), -1); |
|
writer << img; |
|
} |
|
} |
|
catch(...) |
|
{ |
|
ts->set_failed_test_info(cvtest::TS::FAIL_EXCEPTION); |
|
} |
|
ts->set_failed_test_info(cvtest::TS::OK); |
|
} |
|
}; |
|
|
|
string ext_from_int(int ext) |
|
{ |
|
if (ext == 0) return ".png"; |
|
if (ext == 1) return ".bmp"; |
|
if (ext == 2) return ".pgm"; |
|
if (ext == 3) return ".tiff"; |
|
return ""; |
|
} |
|
|
|
class CV_FFmpegWriteSequenceImageTest : public cvtest::BaseTest |
|
{ |
|
public: |
|
void run(int) |
|
{ |
|
try |
|
{ |
|
const int img_r = 640; |
|
const int img_c = 480; |
|
Size frame_s = Size(img_c, img_r); |
|
|
|
for (int k = 1; k <= 5; ++k) |
|
{ |
|
for (int ext = 0; ext < 4; ++ext) // 0 - png, 1 - bmp, 2 - pgm, 3 - tiff |
|
for (int num_channels = 1; num_channels <= 3; num_channels+=2) |
|
{ |
|
ts->printf(ts->LOG, "image type depth:%d channels:%d ext: %s\n", CV_8U, num_channels, ext_from_int(ext).c_str()); |
|
Mat img(img_r * k, img_c * k, CV_MAKETYPE(CV_8U, num_channels), Scalar::all(0)); |
|
circle(img, Point2i((img_c * k) / 2, (img_r * k) / 2), cv::min((img_r * k), (img_c * k)) / 4 , Scalar::all(255)); |
|
ts->printf(ts->LOG, "writing image : %s\n", string(string(ts->get_data_path()) + "readwrite/test" + ext_from_int(ext)).c_str()); |
|
imwrite(string(ts->get_data_path()) + "readwrite/test" + ext_from_int(ext), img); |
|
ts->printf(ts->LOG, "reading test image : %s\n", string(string(ts->get_data_path()) + "readwrite/test" + ext_from_int(ext)).c_str()); |
|
|
|
Mat img_test = imread(string(ts->get_data_path()) + "readwrite/test" + ext_from_int(ext), CV_LOAD_IMAGE_UNCHANGED); |
|
|
|
if (img_test.empty()) ts->set_failed_test_info(ts->FAIL_MISMATCH); |
|
|
|
CV_Assert(img.size() == img_test.size()); |
|
CV_Assert(img.type() == img_test.type()); |
|
|
|
double n = norm(img, img_test); |
|
if ( n > 1.0) |
|
{ |
|
ts->printf(ts->LOG, "norm = %f \n", n); |
|
ts->set_failed_test_info(ts->FAIL_MISMATCH); |
|
} |
|
} |
|
|
|
for (int num_channels = 1; num_channels <= 3; num_channels+=2) |
|
{ |
|
// jpeg |
|
ts->printf(ts->LOG, "image type depth:%d channels:%d ext: %s\n", CV_8U, num_channels, ".jpg"); |
|
Mat img(img_r * k, img_c * k, CV_MAKETYPE(CV_8U, num_channels), Scalar::all(0)); |
|
circle(img, Point2i((img_c * k) / 2, (img_r * k) / 2), cv::min((img_r * k), (img_c * k)) / 4 , Scalar::all(255)); |
|
string filename = string(ts->get_data_path() + "readwrite/test_" + char(k + 48) + "_c" + char(num_channels + 48) + "_.jpg"); |
|
imwrite(filename, img); |
|
img = imread(filename, CV_LOAD_IMAGE_UNCHANGED); |
|
|
|
filename = string(ts->get_data_path() + "readwrite/test_" + char(k + 48) + "_c" + char(num_channels + 48) + ".jpg"); |
|
ts->printf(ts->LOG, "reading test image : %s\n", filename.c_str()); |
|
Mat img_test = imread(filename, CV_LOAD_IMAGE_UNCHANGED); |
|
|
|
if (img_test.empty()) ts->set_failed_test_info(ts->FAIL_MISMATCH); |
|
|
|
CV_Assert(img.size() == img_test.size()); |
|
CV_Assert(img.type() == img_test.type()); |
|
|
|
double n = norm(img, img_test); |
|
if ( n > 1.0) |
|
{ |
|
ts->printf(ts->LOG, "norm = %f \n", n); |
|
ts->set_failed_test_info(ts->FAIL_MISMATCH); |
|
} |
|
} |
|
|
|
for (int num_channels = 1; num_channels <= 3; num_channels+=2) |
|
{ |
|
// tiff |
|
ts->printf(ts->LOG, "image type depth:%d channels:%d ext: %s\n", CV_16U, num_channels, ".tiff"); |
|
Mat img(img_r * k, img_c * k, CV_MAKETYPE(CV_16U, num_channels), Scalar::all(0)); |
|
circle(img, Point2i((img_c * k) / 2, (img_r * k) / 2), cv::min((img_r * k), (img_c * k)) / 4 , Scalar::all(255)); |
|
string filename = string(ts->get_data_path() + "readwrite/test.tiff"); |
|
imwrite(filename, img); |
|
ts->printf(ts->LOG, "reading test image : %s\n", filename.c_str()); |
|
Mat img_test = imread(filename, CV_LOAD_IMAGE_UNCHANGED); |
|
|
|
if (img_test.empty()) ts->set_failed_test_info(ts->FAIL_MISMATCH); |
|
|
|
CV_Assert(img.size() == img_test.size()); |
|
|
|
ts->printf(ts->LOG, "img : %d ; %d \n", img.channels(), img.depth()); |
|
ts->printf(ts->LOG, "img_test : %d ; %d \n", img_test.channels(), img_test.depth()); |
|
|
|
CV_Assert(img.type() == img_test.type()); |
|
|
|
|
|
double n = norm(img, img_test); |
|
if ( n > 1.0) |
|
{ |
|
ts->printf(ts->LOG, "norm = %f \n", n); |
|
ts->set_failed_test_info(ts->FAIL_MISMATCH); |
|
} |
|
} |
|
} |
|
} |
|
catch(const cv::Exception & e) |
|
{ |
|
ts->printf(ts->LOG, "Exception: %s\n" , e.what()); |
|
ts->set_failed_test_info(ts->FAIL_MISMATCH); |
|
} |
|
} |
|
}; |
|
|
|
TEST(Highgui_FFmpeg_WriteBigImage, regression) { CV_FFmpegWriteBigImageTest test; test.safe_run(); } |
|
TEST(Highgui_FFmpeg_WriteBigVideo, regression) { CV_FFmpegWriteBigVideoTest test; test.safe_run(); } |
|
TEST(Highgui_FFmpeg_WriteSequenceImage, regression) { CV_FFmpegWriteSequenceImageTest test; test.safe_run(); }
|
|
|