samples/c/one_way_sample.cpp

   1 /*
   2  *  one_way_sample.cpp
   3  *  outlet_detection
   4  *
   5  *  Created by Victor  Eruhimov on 8/5/09.
   6  *  Copyright 2009 Argus Corp. All rights reserved.
   7  *
   8  */
   9
  10 #include "opencv2/imgproc/imgproc.hpp"
  11 #include "opencv2/features2d/features2d.hpp"
  12 #include "opencv2/highgui/highgui.hpp"
  13 #include "opencv2/imgproc/imgproc_c.h"
  14 #include "opencv2/nonfree/nonfree.hpp"
  15 #include "opencv2/legacy/legacy.hpp"
  16 #include "opencv2/legacy/compat.hpp"
  17
  18 #include <string>
  19 #include <stdio.h>
  20
  21 static void help()
  22 {
  23     printf("\nThis program demonstrates the one way interest point descriptor found in features2d.hpp\n"
  24             "Correspondences are drawn\n");
  25     printf("Format: \n./one_way_sample <path_to_samples> <image1> <image2>\n");
  26     printf("For example: ./one_way_sample . ../c/scene_l.bmp ../c/scene_r.bmp\n");
  27 }
  28
  29 using namespace std;
  30 using namespace cv;
  31
  32 Mat DrawCorrespondences(const Mat& img1, const vector<KeyPoint>& features1, const Mat& img2,
  33                         const vector<KeyPoint>& features2, const vector<int>& desc_idx);
  34
  35 int main(int argc, char** argv)
  36 {
  37     const char images_list[] = "one_way_train_images.txt";
  38     const CvSize patch_size = cvSize(24, 24);
  39     const int pose_count = 50;
  40
  41     if (argc != 4)
  42     {
  43         help();
  44         return 0;
  45     }
  46
  47     std::string path_name = argv[1];
  48     std::string img1_name = path_name + "/" + std::string(argv[2]);
  49     std::string img2_name = path_name + "/" + std::string(argv[3]);
  50
  51     printf("Reading the images...\n");
  52     Mat img1 = imread(img1_name, IMREAD_GRAYSCALE);
  53     Mat img2 = imread(img2_name, IMREAD_GRAYSCALE);
  54
  55     // extract keypoints from the first image
  56     SURF surf_extractor(5.0e3);
  57     vector<KeyPoint> keypoints1;
  58
  59     // printf("Extracting keypoints\n");
  60     surf_extractor(img1, Mat(), keypoints1);
  61
  62     printf("Extracted %d keypoints...\n", (int)keypoints1.size());
  63
  64     printf("Training one way descriptors... \n");
  65     // create descriptors
  66     OneWayDescriptorBase descriptors(patch_size, pose_count, OneWayDescriptorBase::GetPCAFilename(), path_name,
  67                                      images_list);
  68     IplImage img1_c = img1;
  69     IplImage img2_c = img2;
  70     descriptors.CreateDescriptorsFromImage(&img1_c, keypoints1);
  71     printf("done\n");
  72
  73     // extract keypoints from the second image
  74     vector<KeyPoint> keypoints2;
  75     surf_extractor(img2, Mat(), keypoints2);
  76     printf("Extracted %d keypoints from the second image...\n", (int)keypoints2.size());
  77
  78     printf("Finding nearest neighbors...");
  79     // find NN for each of keypoints2 in keypoints1
  80     vector<int> desc_idx;
  81     desc_idx.resize(keypoints2.size());
  82     for (size_t i = 0; i < keypoints2.size(); i++)
  83     {
  84         int pose_idx = 0;
  85         float distance = 0;
  86         descriptors.FindDescriptor(&img2_c, keypoints2[i].pt, desc_idx[i], pose_idx, distance);
  87     }
  88     printf("done\n");
  89
  90     Mat img_corr = DrawCorrespondences(img1, keypoints1, img2, keypoints2, desc_idx);
  91
  92     imshow("correspondences", img_corr);
  93     waitKey(0);
  94 }
  95
  96 Mat DrawCorrespondences(const Mat& img1, const vector<KeyPoint>& features1, const Mat& img2,
  97                         const vector<KeyPoint>& features2, const vector<int>& desc_idx)
  98 {
  99     Mat part, img_corr(Size(img1.cols + img2.cols, MAX(img1.rows, img2.rows)), CV_8UC3);
 100     img_corr = Scalar::all(0);
 101     part = img_corr(Rect(0, 0, img1.cols, img1.rows));
 102     cvtColor(img1, part, COLOR_GRAY2RGB);
 103     part = img_corr(Rect(img1.cols, 0, img2.cols, img2.rows));
 104     cvtColor(img1, part, COLOR_GRAY2RGB);
 105
 106     for (size_t i = 0; i < features1.size(); i++)
 107     {
 108         circle(img_corr, features1[i].pt, 3, CV_RGB(255, 0, 0));
 109     }
 110
 111     for (size_t i = 0; i < features2.size(); i++)
 112     {
 113         Point pt((int)features2[i].pt.x + img1.cols, (int)features2[i].pt.y);
 114         circle(img_corr, pt, 3, Scalar(0, 0, 255));
 115         line(img_corr, features1[desc_idx[i]].pt, pt, Scalar(0, 255, 0));
 116     }
 117
 118     return img_corr;
 119 }