If I want to crop image center at (x,y) with window size ws using
void cvWarpAffine(const CvArr* src, CvArr* dst, const CvMat* map_matrix,
int flags=CV_INTER_LINEAR+CV_WARP_FILL_OUTLIERS, CvScalar fillval=cvScalarAll(0) )
in openCV, how should I set the parameters of transformation matrix? I am confused about how to set the default parameters of other transformations except crop?
P.S. In my situation I also want to crop the point centre at edge and need padding in the fix window. So use cv:rect will be more complecated to deal with the edge.
Related
I am doing Inverse Perspective Mapping using opencv C++. I am following this code to get the desired result. Please have a look at the result.
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I am using opencv c++ remap function. In addition to the current result I need to how to project a pixel from the source image to the distination image. i.e if I click on the pixel (320, 140), how would I get the corresponding pixel i.e (0, 0) in the distination picture.
void remap(InputArray src, OutputArray dst, InputArray map1, InputArray map2, int interpolation, int borderMode=BORDER_CONSTANT, const Scalar& borderValue=Scalar())
I have the calculated the arguments map1, map2. I guess I have to use them but i don't know how.
I have a program that detects objects in a live video stream. I am looking to compensate for the distortion in the camera, I have used the OpenCV calibration tool and produced an XML file with the relevant parameters.
However I am unsure how to then apply this using the undistort function, it is my understanding that this will need to be applied to each frame as it is captured?
void undistort(InputArray src, OutputArray dst, InputArray cameraMatrix, InputArray distCoeffs, InputArray newCameraMatrix=noArray() )
I am having trouble identifying each of these parameters, below is my current understanding.
undistorted(currentFrame, resultsWindow, calibrationFile, notSure, notSure);
Is this function called as below:
if(captureOpen == false){
img_scene = cvCaptureFromFile(videoFeed);
}
while(1) {
image = cvQueryFrame(img_scene);
undistort();
undistorted(currentFrame, resultsWindow, calibrationFile, notSure,
notSure);
No, that will not work. You need to manually read your XML file beforehand and fill the corresponding parameters with the data found in the file. The file should contain the camera matrix (look for cx, cy, fx, fy values) and the distortion parameters (k1, k2, k3, p1, p2, etc.).
The documentation for undistort for 2.4.x is here : http://docs.opencv.org/2.4/modules/imgproc/doc/geometric_transformations.html#undistort
Typically src is a Mat containing the current frame. dst an output Mat of the same size that will be filled with the undistorted image. You will have to convert that back to your preferred format or display it in the window. cameraMatrix is a 3x3 Mat that you have filled with your camera intrinsics. distCoeffs is usually a 1x4 or 1x5 Mat containing the distorsion coeffs. (Note that p1 and p2 must be written right after k2).
I'm working in OpenCV C++ to filtering image color. I want to filter the image using my own matrix. See this code:
img= "c:/Test/tes.jpg";
Mat im = imread(img);
And then i want to filtering/multiply with my matrix (this matrix can replaced with another matrix 3x3)
Mat filter = (Mat_<double>(3, 3) <<17.8824, 43.5161, 4.11935,
3.45565, 27.1554, 3.86714,
0.0299566, 0.184309, 1.46709);
How to multiply the img mat matrix with my own matrix? I'm still not understand how to multiply 3 channel (RGB) matrix with another matrix (single channel) and resulted image with new color.
you should take a look at the opencv documentation. You could use this function:
filter2D(InputArray src, OutputArray dst, int ddepth, InputArray kernel, Point anchor=Point(-1,-1), double delta=0, int borderType=BORDER_DEFAULT )
which would give you something like this in your code:
Mat output;
filter2D(im, output, -1, filter);
About your question for 3-channel matrix; it is specified in the documentation:
kernel – convolution kernel (or rather a correlation kernel), a single-channel floating point matrix; if you want to apply different kernels to different channels, split the image into separate color planes using split() and process them individually.
So by default your "filter" matrix will be applied equally to each color plane.
EDIT You find a fully functional example on the opencv site: http://docs.opencv.org/doc/tutorials/imgproc/imgtrans/filter_2d/filter_2d.html
I am new to OpenCV2 and working on a project in emotion recognition and would like to align a facial image in relation to a reference facial image. I would like to get the image translation working before moving to rotation. Current idea is to run a search within a limited range on both x and y coordinates and use the sum of squared differences as error metric to select the optimal x/y parameters to align the image. I'm using the OpenCV face_cascade function to detect the face images, all images are resized to a fixed (128x128). Question: Which parameters of the Mat image do I need to modify to shift the image in a positive/negative direction on both x and y axis? I believe setImageROI is no longer supported by Mat datatypes? I have the ROIs for both faces available however I am unsure how to use them.
void alignImage(vector<Rect> faceROIstore, vector<Mat> faceIMGstore)
{
Mat refimg = faceIMGstore[1]; //reference image
Mat dispimg = faceIMGstore[52]; // "displaced" version of reference image
//Rect refROI = faceROIstore[1]; //Bounding box for face in reference image
//Rect dispROI = faceROIstore[52]; //Bounding box for face in displaced image
Mat aligned;
matchTemplate(dispimg, refimg, aligned, CV_TM_SQDIFF_NORMED);
imshow("Aligned image", aligned);
}
The idea for this approach is based on Image Alignment Tutorial by Richard Szeliski Working on Windows with OpenCV 2.4. Any suggestions are much appreciated.
cv::Mat does support ROI. (But it does not support COI - channel-of-interest.)
To apply ROI you can use operator() or special constructor:
Mat refimgROI = faceIMGstore[1](faceROIstore[1]); //reference image ROI
Mat dispimgROI(faceIMGstore[52], faceROIstore[52]); // "displaced" version of reference image ROI
And to find the best position inside a displaced image you can utilize matchTemplate function.
Based on your comments I can suggest the following code which will find the best position of reference patch nearby the second (displaced) patch:
Mat ref = faceIMGstore[1](faceROIstore[1]);
Mat disp = faceIMGstore[52](faceROIstore[52]);
disp = disp.adjustROI(5,5,5,5); //allow 5 pixel max adjustment in any direction
if(disp.cols < ref.cols || disp.rows < ref.rows)
return 0;
Mat map;
cv::matchTemplate( disp, ref, map, CV_TM_SQDIFF_NORMED );
Point minLoc;
cv::minMaxLoc( map, 0, &minLoc );
Mat adjusted = disp(Rect(minLoc.x, minLoc.y, ref.cols, ref.rows));
The problem is solved....I used cvGet2D,below is the sample code
CvScalar s;
s=cvGet2D(src_Image,pixel[i].x,pixel[i].y);
cvSet2D(dst_Image,pixel[i].x,pixel[i].y,s);
Where src_Iamge and dst_Image is the source and destination image correspondingly and pixel[i] is the selected pixel i wanted to draw in the dst image. I have include the real out image below.
have an source Ipl image, I want to copy some of the part of the image to a new destination image pixel by pixel. can any body tell me how can do it? I use c,c++ in opencv. For example if the below image is source image,
The real output image
EDIT:
I can see the comments suggesting cvGet2d. I think, if you just want to show "points", it is best to show them with a small neighbourhood so they can be seen where they are. For that you can draw white filled circles with origins at (x,y), on a mask, then you do the copyTo.
using namespace cv;
Mat m(input_iplimage);
Mat mask=Mat::zeros(m.size(), CV_8UC1);
p1 = Point(x,y);
r = 3;
circle(mask,p1,r, 1); // draws the circle around your point.
floodFill(mask, p1, 1); // fills the circle.
//p2, p3, ...
Mat output = Mat::zeros(m.size(),m.type()); // output starts with a black background.
m.copyTo(output, mask); // copies the selected parts of m to output
OLD post:
Create a mask and copy those pixels:
#include<opencv2/opencv.hpp>
using namespace cv;
Mat m(input_iplimage);
Mat mask=Mat::zeros(m.size(), CV_8UC1); // set mask 1 for every pixel you wanna copy.
Rect roi=Rect(x,y,width,height); // create a rectangle
mask(roi) = 1; // set it to 0.
roi = Rect(x2,y2,w2,h2);
mask(roi)=1; // set the second rectangular area for copying...
Mat output = 100*Mat::ones(m.size(),m.type()); // output with a gray background.
m.copyTo(output, mask); // copy selected areas of m to output
Alternatively you can copy Rect-by-Rect:
Mat m(input_iplimage);
Mat output = 100*Mat::ones(m.size(),m.type()); // output with a gray background.
Rect roi=Rect(x,y,width,height);
Mat m_temp, out_temp;
m_temp=m(roi);
out_temp = output(roi);
m_temp.copyTo(out_temp);
roi=Rect(x2,y2,w2,h2);
Mat m_temp, out_temp;
m_temp=m(roi);
out_temp = output(roi);
m_temp.copyTo(out_temp);
The answer to your question only requires to have look at the OpenCV documentation or just to search in your favourite search engine.
Here you've an answer for Ipl images and for newer Mat data.
For having an output as I see in your images, I'd do it setting ROI's, it's more efficient.