Merge pull request #23442 from LaurentBerger:tuto_findFile

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

samples/cpp/tutorial_code/Histograms_Matching/MatchTemplate_Demo.cpp

@@ -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()))

samples/cpp/tutorial_code/Histograms_Matching/calcBackProject_Demo1.cpp

@@ -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;

samples/cpp/tutorial_code/Histograms_Matching/compareHist_Demo.cpp

@@ -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;

samples/cpp/tutorial_code/ImgProc/anisotropic_image_segmentation/anisotropic_image_segmentation.cpp

@@ -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;
@@ -46,13 +48,18 @@ 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);
-    //! [main_extra]
+     waitKey(0);
+   //! [main_extra]
     return 0;
 }
 //! [calcGST]

samples/cpp/tutorial_code/ImgProc/out_of_focus_deblur_filter/out_of_focus_deblur_filter.cpp

@@ -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;
 }
 

samples/cpp/tutorial_code/ImgProc/periodic_noise_removing_filter/periodic_noise_removing_filter.cpp

@@ -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;
 }
 

samples/cpp/tutorial_code/ImgTrans/generalizedHoughTransform.cpp

@@ -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;
@@ -105,4 +106,4 @@ int main() {
     //! [generalized-hough-transform-draw-results]
 
     return EXIT_SUCCESS;
-}
+}