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/*
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* one_way_sample.cpp
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* outlet_detection
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*
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* Created by Victor Eruhimov on 8/5/09.
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* Copyright 2009 Argus Corp. All rights reserved.
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*
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*/
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#include <cv.h>
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#include <cvaux.h>
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#include <highgui.h>
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#include <string>
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using namespace cv;
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IplImage* DrawCorrespondences(IplImage* img1, const vector<KeyPoint>& features1, IplImage* img2,
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const vector<KeyPoint>& features2, const vector<int>& desc_idx);
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int main(int argc, char** argv)
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{
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const char images_list[] = "one_way_train_images.txt";
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const CvSize patch_size = cvSize(24, 24);
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const int pose_count = 50;
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if (argc != 3 && argc != 4)
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{
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printf("Format: \n./one_way_sample [path_to_samples] [image1] [image2]\n");
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printf("For example: ./one_way_sample ../../../opencv/samples/c scene_l.bmp scene_r.bmp\n");
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return 0;
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}
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std::string path_name = argv[1];
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std::string img1_name = path_name + "/" + std::string(argv[2]);
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std::string img2_name = path_name + "/" + std::string(argv[3]);
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printf("Reading the images...\n");
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IplImage* img1 = cvLoadImage(img1_name.c_str(), CV_LOAD_IMAGE_GRAYSCALE);
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IplImage* img2 = cvLoadImage(img2_name.c_str(), CV_LOAD_IMAGE_GRAYSCALE);
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// extract keypoints from the first image
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SURF surf_extractor(5.0e3);
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vector<KeyPoint> keypoints1;
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// printf("Extracting keypoints\n");
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surf_extractor(img1, Mat(), keypoints1);
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printf("Extracted %d keypoints...\n", (int)keypoints1.size());
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printf("Training one way descriptors... \n");
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// create descriptors
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OneWayDescriptorBase descriptors(patch_size, pose_count, OneWayDescriptorBase::GetPCAFilename(), path_name,
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images_list);
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descriptors.CreateDescriptorsFromImage(img1, keypoints1);
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printf("done\n");
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// extract keypoints from the second image
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vector<KeyPoint> keypoints2;
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surf_extractor(img2, Mat(), keypoints2);
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printf("Extracted %d keypoints from the second image...\n", (int)keypoints2.size());
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printf("Finding nearest neighbors...");
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// find NN for each of keypoints2 in keypoints1
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vector<int> desc_idx;
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desc_idx.resize(keypoints2.size());
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for (size_t i = 0; i < keypoints2.size(); i++)
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{
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int pose_idx = 0;
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float distance = 0;
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descriptors.FindDescriptor(img2, keypoints2[i].pt, desc_idx[i], pose_idx, distance);
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}
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printf("done\n");
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IplImage* img_corr = DrawCorrespondences(img1, keypoints1, img2, keypoints2, desc_idx);
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cvNamedWindow("correspondences", 1);
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cvShowImage("correspondences", img_corr);
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cvWaitKey(0);
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cvReleaseImage(&img1);
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cvReleaseImage(&img2);
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cvReleaseImage(&img_corr);
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}
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IplImage* DrawCorrespondences(IplImage* img1, const vector<KeyPoint>& features1, IplImage* img2,
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const vector<KeyPoint>& features2, const vector<int>& desc_idx)
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{
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IplImage* img_corr = cvCreateImage(cvSize(img1->width + img2->width, MAX(img1->height, img2->height)),
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IPL_DEPTH_8U, 3);
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cvSetImageROI(img_corr, cvRect(0, 0, img1->width, img1->height));
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cvCvtColor(img1, img_corr, CV_GRAY2RGB);
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cvSetImageROI(img_corr, cvRect(img1->width, 0, img2->width, img2->height));
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cvCvtColor(img2, img_corr, CV_GRAY2RGB);
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cvResetImageROI(img_corr);
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for (size_t i = 0; i < features1.size(); i++)
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{
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cvCircle(img_corr, features1[i].pt, 3, CV_RGB(255, 0, 0));
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}
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for (size_t i = 0; i < features2.size(); i++)
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{
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CvPoint pt = cvPoint(features2[i].pt.x + img1->width, features2[i].pt.y);
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cvCircle(img_corr, pt, 3, CV_RGB(255, 0, 0));
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cvLine(img_corr, features1[desc_idx[i]].pt, pt, CV_RGB(0, 255, 0));
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}
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return img_corr;
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}
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