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Merge pull request #23442 from LaurentBerger:tuto_findFile

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Fix image loading in tutorials code #23442

Fixes https://github.com/opencv/opencv/issues/23378

### 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
- [X] There is a reference to the original bug report and related work
- [X] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [X] The feature is well documented and sample code can be built with the project CMake
This commit is contained in:
Laurent Berger 2023-04-06 12:02:00 +02:00 committed by GitHub
parent 793c966c40
commit 9742c73254
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GPG Key ID: 4AEE18F83AFDEB23
7 changed files with 63 additions and 33 deletions
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20
samples/cpp/tutorial_code/Histograms_Matching/MatchTemplate_Demo.cpp
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@ -26,26 +26,28 @@ int max_Trackbar = 5;
/// Function Headers
void MatchingMethod( int, void* );
const char* keys =
"{ help h| | Print help message. }"
"{ @input1 | Template_Matching_Original_Image.jpg | image_name }"
"{ @input2 | Template_Matching_Template_Image.jpg | template_name }"
"{ @input3 | | mask_name }";
/**
* @function main
*/
int main( int argc, char** argv )
{
if (argc < 3)
{
cout << "Not enough parameters" << endl;
cout << "Usage:\n" << argv[0] << " <image_name> <template_name> [<mask_name>]" << endl;
return -1;
}
CommandLineParser parser( argc, argv, keys );
samples::addSamplesDataSearchSubDirectory( "doc/tutorials/imgproc/histograms/template_matching/images" );
//! [load_image]
/// Load image and template
img = imread( argv[1], IMREAD_COLOR );
templ = imread( argv[2], IMREAD_COLOR );
img = imread( samples::findFile( parser.get<String>("@input1") ) );
templ = imread( samples::findFile( parser.get<String>("@input2") ), IMREAD_COLOR );
if(argc > 3) {
use_mask = true;
mask = imread( argv[3], IMREAD_COLOR );
mask = imread(samples::findFile( parser.get<String>("@input3") ), IMREAD_COLOR );
}
if(img.empty() || templ.empty() || (use_mask && mask.empty()))

5
samples/cpp/tutorial_code/Histograms_Matching/calcBackProject_Demo1.cpp
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@ -26,8 +26,9 @@ void Hist_and_Backproj(int, void* );
int main( int argc, char* argv[] )
{
//! [Read the image]
CommandLineParser parser( argc, argv, "{@input | | input image}" );
Mat src = imread( parser.get<String>( "@input" ) );
CommandLineParser parser( argc, argv, "{@input |Back_Projection_Theory0.jpg| input image}" );
samples::addSamplesDataSearchSubDirectory("doc/tutorials/imgproc/histograms/back_projection/images");
Mat src = imread(samples::findFile(parser.get<String>( "@input" )) );
if( src.empty() )
{
cout << "Could not open or find the image!\n" << endl;

13
samples/cpp/tutorial_code/Histograms_Matching/compareHist_Demo.cpp
View File

@ -14,9 +14,9 @@ using namespace cv;
const char* keys =
"{ help h| | Print help message. }"
"{ @input1 | | Path to input image 1. }"
"{ @input2 | | Path to input image 2. }"
"{ @input3 | | Path to input image 3. }";
"{ @input1 |Histogram_Comparison_Source_0.jpg | Path to input image 1. }"
"{ @input2 |Histogram_Comparison_Source_1.jpg | Path to input image 2. }"
"{ @input3 |Histogram_Comparison_Source_2.jpg | Path to input image 3. }";
/**
* @function main
@ -25,9 +25,10 @@ int main( int argc, char** argv )
{
//! [Load three images with different environment settings]
CommandLineParser parser( argc, argv, keys );
Mat src_base = imread( parser.get<String>("input1") );
Mat src_test1 = imread( parser.get<String>("input2") );
Mat src_test2 = imread( parser.get<String>("input3") );
samples::addSamplesDataSearchSubDirectory( "doc/tutorials/imgproc/histograms/histogram_comparison/images" );
Mat src_base = imread(samples::findFile( parser.get<String>( "@input1" ) ) );
Mat src_test1 = imread(samples::findFile( parser.get<String>( "@input2" ) ) );
Mat src_test2 = imread(samples::findFile( parser.get<String>( "@input3" ) ) );
if( src_base.empty() || src_test1.empty() || src_test2.empty() )
{
cout << "Could not open or find the images!\n" << endl;

15
samples/cpp/tutorial_code/ImgProc/anisotropic_image_segmentation/anisotropic_image_segmentation.cpp
View File

@ -1,9 +1,10 @@
/**
/**
* @brief You will learn how to segment an anisotropic image with a single local orientation by a gradient structure tensor (GST)
* @author Karpushin Vladislav, karpushin@ngs.ru, https://github.com/VladKarpushin
*/
#include <iostream>
#include "opencv2/highgui.hpp"
#include "opencv2/imgproc.hpp"
#include "opencv2/imgcodecs.hpp"
@ -21,7 +22,8 @@ int main()
int LowThr = 35; // threshold1 for orientation, it ranges from 0 to 180
int HighThr = 57; // threshold2 for orientation, it ranges from 0 to 180
Mat imgIn = imread("input.jpg", IMREAD_GRAYSCALE);
samples::addSamplesDataSearchSubDirectory("doc/tutorials/imgproc/anisotropic_image_segmentation/images");
Mat imgIn = imread(samples::findFile("gst_input.jpg"), IMREAD_GRAYSCALE);
if (imgIn.empty()) //check whether the image is loaded or not
{
cout << "ERROR : Image cannot be loaded..!!" << endl;
@ -46,12 +48,17 @@ int main()
//! [combining]
//! [main]
normalize(imgCoherency, imgCoherency, 0, 255, NORM_MINMAX);
normalize(imgOrientation, imgOrientation, 0, 255, NORM_MINMAX);
normalize(imgCoherency, imgCoherency, 0, 255, NORM_MINMAX, CV_8U);
normalize(imgOrientation, imgOrientation, 0, 255, NORM_MINMAX, CV_8U);
imshow("Original", imgIn);
imshow("Result", 0.5 * (imgIn + imgBin));
imshow("Coherency", imgCoherency);
imshow("Orientation", imgOrientation);
imwrite("result.jpg", 0.5*(imgIn + imgBin));
imwrite("Coherency.jpg", imgCoherency);
imwrite("Orientation.jpg", imgOrientation);
waitKey(0);
//! [main_extra]
return 0;
}

15
samples/cpp/tutorial_code/ImgProc/out_of_focus_deblur_filter/out_of_focus_deblur_filter.cpp
View File

@ -1,8 +1,9 @@
/**
/**
* @brief You will learn how to recover an out-of-focus image by Wiener filter
* @author Karpushin Vladislav, karpushin@ngs.ru, https://github.com/VladKarpushin
*/
#include <iostream>
#include "opencv2/highgui.hpp"
#include "opencv2/imgproc.hpp"
#include "opencv2/imgcodecs.hpp"
@ -17,9 +18,9 @@ void calcWnrFilter(const Mat& input_h_PSF, Mat& output_G, double nsr);
const String keys =
"{help h usage ? | | print this message }"
"{image |original.JPG | input image name }"
"{R |53 | radius }"
"{SNR |5200 | signal to noise ratio}"
"{image |original.jpg | input image name }"
"{R |5 | radius }"
"{SNR |100 | signal to noise ratio}"
;
int main(int argc, char *argv[])
@ -35,6 +36,7 @@ int main(int argc, char *argv[])
int R = parser.get<int>("R");
int snr = parser.get<int>("SNR");
string strInFileName = parser.get<String>("image");
samples::addSamplesDataSearchSubDirectory("doc/tutorials/imgproc/out_of_focus_deblur_filter/images");
if (!parser.check())
{
@ -43,7 +45,7 @@ int main(int argc, char *argv[])
}
Mat imgIn;
imgIn = imread(strInFileName, IMREAD_GRAYSCALE);
imgIn = imread(samples::findFile( strInFileName ), IMREAD_GRAYSCALE);
if (imgIn.empty()) //check whether the image is loaded or not
{
cout << "ERROR : Image cannot be loaded..!!" << endl;
@ -69,7 +71,10 @@ int main(int argc, char *argv[])
imgOut.convertTo(imgOut, CV_8U);
normalize(imgOut, imgOut, 0, 255, NORM_MINMAX);
imshow("Original", imgIn);
imshow("Debluring", imgOut);
imwrite("result.jpg", imgOut);
waitKey(0);
return 0;
}

19
samples/cpp/tutorial_code/ImgProc/periodic_noise_removing_filter/periodic_noise_removing_filter.cpp
View File

@ -1,8 +1,9 @@
/**
/**
* @brief You will learn how to remove periodic noise in the Fourier domain
* @author Karpushin Vladislav, karpushin@ngs.ru, https://github.com/VladKarpushin
*/
#include <iostream>
#include "opencv2/highgui.hpp"
#include <opencv2/imgcodecs.hpp>
#include <opencv2/imgproc.hpp>
@ -14,15 +15,25 @@ void filter2DFreq(const Mat& inputImg, Mat& outputImg, const Mat& H);
void synthesizeFilterH(Mat& inputOutput_H, Point center, int radius);
void calcPSD(const Mat& inputImg, Mat& outputImg, int flag = 0);
int main()
const String keys =
"{help h usage ? | | print this message }"
"{@image |period_input.jpg | input image name }"
;
int main(int argc, char* argv[])
{
Mat imgIn = imread("input.jpg", IMREAD_GRAYSCALE);
CommandLineParser parser(argc, argv, keys);
string strInFileName = parser.get<String>("@image");
samples::addSamplesDataSearchSubDirectory("doc/tutorials/imgproc/periodic_noise_removing_filter/images");
Mat imgIn = imread(samples::findFile(strInFileName), IMREAD_GRAYSCALE);
if (imgIn.empty()) //check whether the image is loaded or not
{
cout << "ERROR : Image cannot be loaded..!!" << endl;
return -1;
}
imshow("Image corrupted", imgIn);
imgIn.convertTo(imgIn, CV_32F);
//! [main]
@ -57,7 +68,9 @@ int main()
imwrite("PSD.jpg", imgPSD);
fftshift(H, H);
normalize(H, H, 0, 255, NORM_MINMAX);
imshow("Debluring", imgOut);
imwrite("filter.jpg", H);
waitKey(0);
return 0;
}

5
samples/cpp/tutorial_code/ImgTrans/generalizedHoughTransform.cpp
View File

@ -13,8 +13,9 @@ using namespace std;
int main() {
//! [generalized-hough-transform-load-and-setup]
// load source image and grayscale template
Mat image = imread("images/generalized_hough_mini_image.jpg");
Mat templ = imread("images/generalized_hough_mini_template.jpg", IMREAD_GRAYSCALE);
samples::addSamplesDataSearchSubDirectory("doc/tutorials/imgproc/generalized_hough_ballard_guil");
Mat image = imread(samples::findFile("images/generalized_hough_mini_image.jpg"));
Mat templ = imread(samples::findFile("images/generalized_hough_mini_template.jpg"), IMREAD_GRAYSCALE);
// create grayscale image
Mat grayImage;