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9f417268b3
Fixed visualization by choosing the color appropriate to the detection score. Previously the example showed all detections with the same color disregarding the confidence. This led to the impression that the object detection did not work at all because there are many detections with low confidences. PR to master was https://github.com/Itseez/opencv/pull/320
106 lines
3.2 KiB
C++
106 lines
3.2 KiB
C++
#include "opencv2/objdetect/objdetect.hpp"
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#include "opencv2/highgui/highgui.hpp"
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#include <stdio.h>
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#ifdef HAVE_CVCONFIG_H
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#include <cvconfig.h>
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#endif
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#ifdef HAVE_TBB
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#include "tbb/task_scheduler_init.h"
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#endif
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using namespace cv;
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static void help()
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{
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printf( "This program demonstrated the use of the latentSVM detector.\n"
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"It reads in a trained object model and then uses that to detect the object in an image\n"
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"Call:\n"
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"./latentsvmdetect [<image_filename> <model_filename> [<threads_number>]]\n"
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" The defaults for image_filename and model_filename are cat.jpg and cat.xml respectively\n"
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" Press any key to quit.\n");
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}
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const char* model_filename = "cat.xml";
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const char* image_filename = "cat.jpg";
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int tbbNumThreads = -1;
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static void detect_and_draw_objects( IplImage* image, CvLatentSvmDetector* detector, int numThreads = -1)
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{
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CvMemStorage* storage = cvCreateMemStorage(0);
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CvSeq* detections = 0;
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int i = 0;
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int64 start = 0, finish = 0;
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#ifdef HAVE_TBB
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tbb::task_scheduler_init init(tbb::task_scheduler_init::deferred);
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if (numThreads > 0)
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{
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init.initialize(numThreads);
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printf("Number of threads %i\n", numThreads);
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}
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else
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{
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printf("Number of threads is not correct for TBB version");
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return;
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}
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#endif
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start = cvGetTickCount();
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detections = cvLatentSvmDetectObjects(image, detector, storage, 0.5f, numThreads);
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finish = cvGetTickCount();
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printf("detection time = %.3f\n", (float)(finish - start) / (float)(cvGetTickFrequency() * 1000000.0));
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#ifdef HAVE_TBB
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init.terminate();
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#endif
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for( i = 0; i < detections->total; i++ )
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{
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CvObjectDetection detection = *(CvObjectDetection*)cvGetSeqElem( detections, i );
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float score = detection.score;
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CvRect bounding_box = detection.rect;
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cvRectangle( image, cvPoint(bounding_box.x, bounding_box.y),
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cvPoint(bounding_box.x + bounding_box.width,
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bounding_box.y + bounding_box.height),
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CV_RGB(cvRound(255.0f*score),0,0), 3 );
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}
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cvReleaseMemStorage( &storage );
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}
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int main(int argc, char* argv[])
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{
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help();
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if (argc > 2)
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{
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image_filename = argv[1];
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model_filename = argv[2];
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if (argc > 3)
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{
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tbbNumThreads = atoi(argv[3]);
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}
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}
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IplImage* image = cvLoadImage(image_filename);
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if (!image)
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{
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printf( "Unable to load the image\n"
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"Pass it as the first parameter: latentsvmdetect <path to cat.jpg> <path to cat.xml>\n" );
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return -1;
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}
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CvLatentSvmDetector* detector = cvLoadLatentSvmDetector(model_filename);
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if (!detector)
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{
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printf( "Unable to load the model\n"
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"Pass it as the second parameter: latentsvmdetect <path to cat.jpg> <path to cat.xml>\n" );
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cvReleaseImage( &image );
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return -1;
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}
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detect_and_draw_objects( image, detector, tbbNumThreads );
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cvNamedWindow( "test", 0 );
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cvShowImage( "test", image );
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cvWaitKey(0);
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cvReleaseLatentSvmDetector( &detector );
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cvReleaseImage( &image );
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cvDestroyAllWindows();
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return 0;
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}
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