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