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Open Source Computer Vision Library
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117 lines
4.0 KiB
117 lines
4.0 KiB
/* |
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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 "opencv2/imgproc/imgproc.hpp" |
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#include "opencv2/features2d/features2d.hpp" |
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#include "opencv2/highgui/highgui.hpp" |
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#include "opencv2/imgproc/imgproc_c.h" |
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#include <string> |
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void help() |
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{ |
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printf("\nThis program demonstrates the one way interest point descriptor found in features2d.hpp\n" |
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"Correspondences are drawn\n"); |
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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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} |
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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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help(); |
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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((int)features2[i].pt.x + img1->width, (int)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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