mirror of https://github.com/opencv/opencv.git
Open Source Computer Vision Library
https://opencv.org/
You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
110 lines
3.7 KiB
110 lines
3.7 KiB
/* |
|
* one_way_sample.cpp |
|
* outlet_detection |
|
* |
|
* Created by Victor Eruhimov on 8/5/09. |
|
* Copyright 2009 Argus Corp. All rights reserved. |
|
* |
|
*/ |
|
|
|
#include <cv.h> |
|
#include <cvaux.h> |
|
#include <highgui.h> |
|
|
|
#include <string> |
|
|
|
using namespace cv; |
|
|
|
IplImage* DrawCorrespondences(IplImage* img1, const vector<KeyPoint>& features1, IplImage* img2, |
|
const vector<KeyPoint>& features2, const vector<int>& 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<KeyPoint> 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<KeyPoint> 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<int> 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<KeyPoint>& features1, IplImage* img2, |
|
const vector<KeyPoint>& features2, const vector<int>& 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; |
|
}
|
|
|