vendor: OpenCV 5.0.0 snapshot at 755e50675d97db9b7d449d8bd6b09888646f6c6e

2026-08-22 00:11:13 +08:00
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+/*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) 2013, OpenCV Foundation, 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 <opencv2/core/utility.hpp>
+#include <opencv2/saliency.hpp>
+#include <opencv2/highgui.hpp>
+#include <iostream>
+
+using namespace std;
+using namespace cv;
+using namespace saliency;
+
+static const char* keys =
+{ "{@saliency_algorithm | | Saliency algorithm <saliencyAlgorithmType.[saliencyAlgorithmTypeSubType]> }"
+    "{@video_name      | | video name            }"
+    "{@start_frame     |1| Start frame           }"
+    "{@training_path   |ObjectnessTrainedModel| Path of the folder containing the trained files}" };
+
+static void help()
+{
+  cout << "\nThis example shows the functionality of \"Saliency \""
+       "Call:\n"
+       "./example_saliency_computeSaliency <saliencyAlgorithmSubType> <video_name> <start_frame> \n"
+       << endl;
+}
+
+int main( int argc, char** argv )
+{
+
+  CommandLineParser parser( argc, argv, keys );
+
+  String saliency_algorithm = parser.get<String>( 0 );
+  String video_name = parser.get<String>( 1 );
+  int start_frame = parser.get<int>( 2 );
+  String training_path = parser.get<String>( 3 );
+
+  if( saliency_algorithm.empty() || video_name.empty() )
+  {
+    help();
+    return -1;
+  }
+
+  //open the capture
+  VideoCapture cap;
+  cap.open( video_name );
+  cap.set( CAP_PROP_POS_FRAMES, start_frame );
+
+  if( !cap.isOpened() )
+  {
+    help();
+    cout << "***Could not initialize capturing...***\n";
+    cout << "Current parameter's value: \n";
+    parser.printMessage();
+    return -1;
+  }
+
+  Mat frame;
+
+  //instantiates the specific Saliency
+  Ptr<Saliency> saliencyAlgorithm;
+
+  Mat binaryMap;
+  Mat image;
+
+  cap >> frame;
+  if( frame.empty() )
+  {
+    return 0;
+  }
+
+  frame.copyTo( image );
+
+  if( saliency_algorithm.find( "SPECTRAL_RESIDUAL" ) == 0 )
+  {
+    Mat saliencyMap;
+    saliencyAlgorithm = StaticSaliencySpectralResidual::create();
+    if( saliencyAlgorithm->computeSaliency( image, saliencyMap ) )
+    {
+      StaticSaliencySpectralResidual spec;
+      spec.computeBinaryMap( saliencyMap, binaryMap );
+
+      imshow( "Saliency Map", saliencyMap );
+      imshow( "Original Image", image );
+      imshow( "Binary Map", binaryMap );
+      waitKey( 0 );
+    }
+
+  }
+  else if( saliency_algorithm.find( "FINE_GRAINED" ) == 0 )
+  {
+    Mat saliencyMap;
+    saliencyAlgorithm = StaticSaliencyFineGrained::create();
+    if( saliencyAlgorithm->computeSaliency( image, saliencyMap ) )
+    {
+      imshow( "Saliency Map", saliencyMap );
+      imshow( "Original Image", image );
+      waitKey( 0 );
+    }
+
+  }
+  else if( saliency_algorithm.find( "BING" ) == 0 )
+  {
+    if( training_path.empty() )
+    {
+
+      cout << "Path of trained files missing! " << endl;
+      return -1;
+    }
+
+    else
+    {
+      saliencyAlgorithm = ObjectnessBING::create();
+      vector<Vec4i> saliencyMap;
+      saliencyAlgorithm.dynamicCast<ObjectnessBING>()->setTrainingPath( training_path );
+      saliencyAlgorithm.dynamicCast<ObjectnessBING>()->setBBResDir( "Results" );
+
+      if( saliencyAlgorithm->computeSaliency( image, saliencyMap ) )
+      {
+        int ndet = int(saliencyMap.size());
+        std::cout << "Objectness done " << ndet << std::endl;
+        // The result are sorted by objectness. We only use the first maxd boxes here.
+        int maxd = 7, step = 255 / maxd, jitter=9; // jitter to separate single rects
+        Mat draw = image.clone();
+        for (int i = 0; i < std::min(maxd, ndet); i++) {
+          Vec4i bb = saliencyMap[i];
+          Scalar col = Scalar(((i*step)%255), 50, 255-((i*step)%255));
+          Point off(theRNG().uniform(-jitter,jitter), theRNG().uniform(-jitter,jitter));
+          rectangle(draw, Point(bb[0]+off.x, bb[1]+off.y), Point(bb[2]+off.x, bb[3]+off.y), col, 2);
+          rectangle(draw, Rect(20, 20+i*10, 10,10), col, -1); // mini temperature scale
+        }
+        imshow("BING", draw);
+        waitKey();
+      }
+      else
+      {
+        std::cout << "No saliency found for " << video_name << std::endl;
+      }
+    }
+
+  }
+  else if( saliency_algorithm.find( "BinWangApr2014" ) == 0 )
+  {
+    saliencyAlgorithm = MotionSaliencyBinWangApr2014::create();
+    saliencyAlgorithm.dynamicCast<MotionSaliencyBinWangApr2014>()->setImagesize( image.cols, image.rows );
+    saliencyAlgorithm.dynamicCast<MotionSaliencyBinWangApr2014>()->init();
+
+    bool paused = false;
+    for ( ;; )
+    {
+      if( !paused )
+      {
+
+        cap >> frame;
+        if( frame.empty() )
+        {
+          return 0;
+        }
+        cvtColor( frame, frame, COLOR_BGR2GRAY );
+
+        Mat saliencyMap;
+        saliencyAlgorithm->computeSaliency( frame, saliencyMap );
+
+        imshow( "image", frame );
+        imshow( "saliencyMap", saliencyMap * 255 );
+      }
+
+      char c = (char) waitKey( 2 );
+      if( c == 'q' )
+        break;
+      if( c == 'p' )
+        paused = !paused;
+
+    }
+  }
+
+  return 0;
+}