I was able to successfully load a number of images into a vector, vector<Mat>. The images once loaded in can be displayed with the imread function.
The problem is that I want to apply SIFT on this set of images using the second variant, as mentioned in the documentation:
void FeatureDetector::detect(const vector<Mat>& images, vector<vector<KeyPoint>>& keypoints, const vector<Mat>& masks=vector<Mat>() ) const
This is producing the following error:
error C2664: 'void cv::FeatureDetector::detect(const cv::Mat &,std::vector<_Ty> &,const cv::Mat &) const' : cannot convert parameter 1 from 'std::vector<_Ty>' to 'const cv::Mat &'
The code I am using:
vector<Mat> images;
/* code to add all images to vector not shown as its messy but it was performed with FindFirstFile of windows.h. All images loaded correctly as they can be read by imread*/
initModule_nonfree();
Ptr<FeatureDetector> get_keypoints = FeatureDetector::create("SIFT");
vector<KeyPoint> keypoints;
get_keypoints->detect(images , keypoints);
The error is detected at get_keypoints->detect(images , keypoints);
From the detect signature, keypoints should be vector<vector<KeyPoint>>, yet you declare it as vector<KeyPoint>.
Related
Using g++, I tried to redefine the Opencv's Mat type as
#define CV_32FC1 CV_TYPE_1
But I have error as invalid arguments at
Mat LO_Coefs;
LO_Coefs.create(1, cnt, CV_TYPE_1);
How can I convert a cvMat matrix to IplImage that can be saved using cvSaveImage, in C using OpenCV?
I learnt about a function cvGetImage(const CvArr* arr, IplImage* imageHeader). I understand that arr stands for the cvMat Array, but could not really understand what 'image header' actually is. Is that the pointer that stores the image ?? That is, would the following work?
clusters = cvCreateMat( image2_size, 1, CV_32SC1 );
IplImage *kmeans;
cvGetImage(clusters, &kmeans);
cvSaveImage("kmeans.jpg", kmeans);
//clusters is the output matrix after performing k-means clustering
// on a certain image.
How to use FERN descriptor matcher in OpenCV? Does it take as an input keypoints extracted by some algrithm (sift/surf?) or it calculates everything by itself?
edit:
I'm trying to apply it do database of images
fernmatcher->add(all_images, all_keypoints);
fernmatcher->train();
there are 20 images, in total less than 8MB, i extract keypoints using SURF. Memory usage jumps to 2.6GB and training takes who knows how long...
FERN is not different from rest of the matchers. Here is a sample code for using FERN as Key point Descriptor Matcher.
int octaves= 3;
int octaveLayers=2;
bool upright=false;
double hessianThreshold=0;
std::vector<KeyPoint> keypoints_1,keypoints_2;
SurfFeatureDetector detector1( hessianThreshold, octaves, octaveLayers, upright );
detector1.detect( image1, keypoints_1 );
detector1.detect( image2, keypoints_2 );
std::vector< DMatch > matches;
FernDescriptorMatcher matcher;
matcher.match(image1,keypoints_1,image2,keypoints_2,matches);
Mat img_matches;
drawMatches( templat_img, keypoints_1,tempimg, keypoints_2,matches, img_matches,Scalar::all(-1), Scalar::all(-1),vector<char>(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS);
imshow( "Fern Matches", img_matches);
waitKey(0);
*But But my suggestion is use FAST which is faster compared to FERN and also FERN can be used to train a set of images with keypoints and the trained FERN can be used as classifier just like all other.
//Open the image
Mat img_rgb = imread("sudoku2.png", CV_LOAD_IMAGE_GRAYSCALE);
if (img_rgb.empty())
{
cout<<"Cannot open the image"<<endl;
return;
}
Mat img_bw = img_rgb > 128;
imwrite("image_bw.jpg", img_bw);
Now, I want to get all pixels of img_bw and save it into a matrix M (int[img_bw.rows][img_bw.cols]). How to do it in C++.
What format ?
The raw byte data in cv::Mat is available from the .ptr() function, ie img_bw.ptr().
Opencv also has an xml and json read and write functions for matrices, just by using the << operator - see opencv tutorial on xml and yaml i/o
EDIT: In c++ you can access pixels with the .at operator.
Use img_data.at<uchar>(x,y) for an unsigned char (CV_8U) pixel and img_data.at<float>(x,y) for a CV_32F image.
I am trying to make the dft of one single channeled image, and as cvDft is expecting complex values, I was adviced to merge the original image with another image with all 0's so this last one will be considered as imaginary part.
My problem comes when using cvmerge function,
Mat tmp = imread(filename,0);
if( tmp.empty() )
{cout << "Usage: dft <image_name>" << endl;
return -1;}
Mat Result(tmp.rows,tmp.cols,CV_64F,2);
Mat tmp1(tmp.rows,tmp.cols,CV_64F, 0);
Mat image(tmp.rows,tmp.cols,CV_64F,2);
cvMerge(tmp,tmp1,image);`
It gives me the next error: can not convert cvMAt to cvArr
Anyone could help me? thanks!
1) it seems like you're mixing up 2 different styles of opencv code
cv::Mat (- Mat) is a c++ class from the new version of opencv, cvMerge is a c function from the old version of opencv.
instead of using cvmerge use merge
2) you're trying to merge a matrix (tmp) of type CV_8U (probably) with a CV_64F
use convertTo to get tmp as CV_64F
3) why is your Result & image mats (the destination mat) are initializes to cv::Scalar(2)? i think you're misusing the constractor parameters. see here for more info.
4) you're image mat is a single channel mat and you wanted it as a 2 channel mat (as mentioned in the question), change the declaration to
Mat image(tmp.rows,tmp.cols,CV_64FC2);