I have an image with detected circles and am trying to read value of these circles in HSV format. I can get the BGR values but not HSv. is there any way to convert bgr to hsv after getting bgr value or what?
source code below
#include <stdio.h>
#include <cv.h>
#include <highgui.h>
#include <math.h>
int main(int argc, char** argv)
{
//load image from directory
IplImage* img = cvLoadImage("C:\\Users\\Nathan\\Desktop\\SnookerPic.png");
IplImage* gray = cvCreateImage(cvGetSize(img), IPL_DEPTH_8U, 1);
CvMemStorage* storage = cvCreateMemStorage(0);
//covert to grayscale
cvCvtColor(img, gray, CV_BGR2GRAY);
// This is done so as to prevent a lot of false circles from being detected
cvSmooth(gray, gray, CV_GAUSSIAN, 7, 7);
IplImage* canny = cvCreateImage(cvGetSize(img),IPL_DEPTH_8U,1);
IplImage* rgbcanny = cvCreateImage(cvGetSize(img),IPL_DEPTH_8U,3);
cvCanny(gray, canny, 50, 100, 3);
//detect circles
CvSeq* circles = cvHoughCircles(gray, storage, CV_HOUGH_GRADIENT, 1, 35.0, 75, 60,0,0);
cvCvtColor(canny, rgbcanny, CV_GRAY2BGR);
//draw all detected circles
for (int i = 0; i < circles->total; i++)
{
// round the floats to an int
float* p = (float*)cvGetSeqElem(circles, i);
cv::Point center(cvRound(p[0]), cvRound(p[1]));
int radius = cvRound(p[2]);
uchar* ptr;
ptr = cvPtr2D(img, center.y, center.x, NULL);
printf("B: %d G: %d R: %d\n", ptr[0],ptr[1],ptr[2]);
//CvScalar c;
//if(center.x > 0 && center.x < 1280 && center.y > 0 && center.y < 720)
//{
//c = cvGet2D(img,center.x, center.y);//colour of circle
//}
// draw the circle center
cvCircle(img, center, 3, CV_RGB(0,255,0), -1, 8, 0 );
// draw the circle outline
cvCircle(img, center, radius+1, CV_RGB(0,0,255), 2, 8, 0 );
//display coordinates
printf("x: %d y: %d r: %d\n",center.x,center.y, radius);
}
//create window
//cvNamedWindow("circles", 1);
cvNamedWindow("SnookerImage", 1);
//show image in window
//cvShowImage("circles", rgbcanny);
cvShowImage("SnookerImage", img);
cvSaveImage("out.png", img);
//cvDestroyWindow("SnookerImage");
//cvDestroyWindow("circles");
//cvReleaseMemStorage("storage");
cvWaitKey(0);
return 0;
}
OpenCV comes with a utility function to convert between colorspaces called cvCvtColor().
Related
I'm trying to generate a bird's eye view from an image. For the camera intrinsics and disortions, I'm using hard coded values that I retrieved from a driving simulator that has a camera mounted on it's roof.
The basis for the code is from "Learning OpenCV Computer Vision with the OpenCV Library", Pg 409.
When I run the code on an image containing a chess board with 3 inner corners per row and 4 inner corners per column, my bird's eye view is upside down. I need the image to correctly turn into a bird's eye and that is right side up because I need the homography matrix for another function call.
Here are the input and output images, and the code i'm using:
Input image:
Corners detected:
Output Image/bird's eye (upside down!):
The code:
#include <highgui.h>
#include <cv.h>
#include <cxcore.h>
#include <math.h>
#include <vector>
#include <stdio.h>
#include <iostream>
using namespace cv;
using namespace std;
int main(int argc, char* argv[]) {
if(argc != 4) return -1;
// INPUT PARAMETERS:
//
int board_w = atoi(argv[1]); //inner corners per row
int board_h = atoi(argv[2]); //inner corners per column
int board_n = board_w * board_h;
CvSize board_sz = cvSize( board_w, board_h );
//Hard coded intrinsics for the camera
Mat intrinsicMat = (Mat_<double>(3, 3) <<
418.7490, 0., 236.8528,
0.,558.6650,322.7346,
0., 0., 1.);
//Hard coded distortions for the camera
CvMat* distortion = cvCreateMat(1, 4, CV_32F);
cvmSet(distortion, 0, 0, -0.0019);
cvmSet(distortion, 0, 1, 0.0161);
cvmSet(distortion, 0, 2, 0.0011);
cvmSet(distortion, 0, 3, -0.0016);
IplImage* image = 0;
IplImage* gray_image = 0;
if( (image = cvLoadImage(argv[3])) == 0 ) {
printf("Error: Couldn’t load %s\n",argv[3]);
return -1;
}
gray_image = cvCreateImage( cvGetSize(image), 8, 1 );
cvCvtColor(image, gray_image, CV_BGR2GRAY );
// UNDISTORT OUR IMAGE
//
IplImage* mapx = cvCreateImage( cvGetSize(image), IPL_DEPTH_32F, 1 );
IplImage* mapy = cvCreateImage( cvGetSize(image), IPL_DEPTH_32F, 1 );
CvMat intrinsic (intrinsicMat);
//This initializes rectification matrices
//
cvInitUndistortMap(
&intrinsic,
distortion,
mapx,
mapy
);
IplImage *t = cvCloneImage(image);
// Rectify our image
//
cvRemap( t, image, mapx, mapy );
// GET THE CHESSBOARD ON THE PLANE
//
cvNamedWindow("Chessboard");
CvPoint2D32f* corners = new CvPoint2D32f[ board_n ];
int corner_count = 0;
int found = cvFindChessboardCorners(
image,
board_sz,
corners,
&corner_count,
CV_CALIB_CB_ADAPTIVE_THRESH | CV_CALIB_CB_FILTER_QUADS
);
if(!found){
printf("Couldn’t aquire chessboard on %s, "
"only found %d of %d corners\n",
argv[3],corner_count,board_n
);
return -1;
}
//Get Subpixel accuracy on those corners:
cvFindCornerSubPix(
gray_image,
corners,
corner_count,
cvSize(11,11),
cvSize(-1,-1),
cvTermCriteria( CV_TERMCRIT_EPS | CV_TERMCRIT_ITER, 30, 0.1 )
);
//GET THE IMAGE AND OBJECT POINTS:
// We will choose chessboard object points as (r,c):
// (0,0), (board_w-1,0), (0,board_h-1), (board_w-1,board_h-1).
//
CvPoint2D32f objPts[4], imgPts[4];
imgPts[0] = corners[0];
imgPts[1] = corners[board_w-1];
imgPts[2] = corners[(board_h-1)*board_w];
imgPts[3] = corners[(board_h-1)*board_w + board_w-1];
objPts[0].x = 0; objPts[0].y = 0;
objPts[1].x = board_w -1; objPts[1].y = 0;
objPts[2].x = 0; objPts[2].y = board_h -1;
objPts[3].x = board_w -1; objPts[3].y = board_h -1;
// DRAW THE POINTS in order: B,G,R,YELLOW
//
cvCircle( image, cvPointFrom32f(imgPts[0]), 9, CV_RGB(0,0,255), 3); //blue
cvCircle( image, cvPointFrom32f(imgPts[1]), 9, CV_RGB(0,255,0), 3); //green
cvCircle( image, cvPointFrom32f(imgPts[2]), 9, CV_RGB(255,0,0), 3); //red
cvCircle( image, cvPointFrom32f(imgPts[3]), 9, CV_RGB(255,255,0), 3); //yellow
// DRAW THE FOUND CHESSBOARD
//
cvDrawChessboardCorners(
image,
board_sz,
corners,
corner_count,
found
);
cvShowImage( "Chessboard", image );
// FIND THE HOMOGRAPHY
//
CvMat *H = cvCreateMat( 3, 3, CV_32F);
cvGetPerspectiveTransform( objPts, imgPts, H);
Mat homography = H;
cvSave("Homography.xml",H); //We can reuse H for the same camera mounting
/**********************GENERATING 3X4 MATRIX***************************/
// LET THE USER ADJUST THE Z HEIGHT OF THE VIEW
//
float Z = 23;
int key = 0;
IplImage *birds_image = cvCloneImage(image);
cvNamedWindow("Birds_Eye");
// LOOP TO ALLOW USER TO PLAY WITH HEIGHT:
//
// escape key stops
//
while(key != 27) {
// Set the height
//
CV_MAT_ELEM(*H,float,2,2) = Z;
// COMPUTE THE FRONTAL PARALLEL OR BIRD’S-EYE VIEW:
// USING HOMOGRAPHY TO REMAP THE VIEW
//
cvWarpPerspective(
image,
birds_image,
H,
CV_INTER_LINEAR | CV_WARP_INVERSE_MAP | CV_WARP_FILL_OUTLIERS
);
cvShowImage( "Birds_Eye", birds_image );
imwrite("/home/lee/bird.jpg", birds_image);
key = cvWaitKey();
if(key == 'u') Z += 0.5;
if(key == 'd') Z -= 0.5;
}
return 0;
}
The homography result seems correct. Since you're mapping the camera's z-axe as the world's y-axe, the image resulting of the bird's eye view (BEV) remap is upside down.
If you really need the BEV image as the camera shot you can have use H as H = Ty * Rx * H, where R is a 180 degree rotation around x-axe, T is a translation in y-axe and H is your original homography. The translation is required since your rotation remapped your old BEV on the negative side of y-axe.
how would you go about reading the pixel value in HSV format rather than RGB? The code below reads the pixel value of the circles' centers in RGB format. Is there much difference when it comes to reading value in HSV?
int main(int argc, char** argv)
{
//load image from directory
IplImage* img = cvLoadImage("C:\\Users\\Nathan\\Desktop\\SnookerPic.png");
IplImage* gray = cvCreateImage(cvGetSize(img), IPL_DEPTH_8U, 1);
CvMemStorage* storage = cvCreateMemStorage(0);
//covert to grayscale
cvCvtColor(img, gray, CV_BGR2GRAY);
// This is done so as to prevent a lot of false circles from being detected
cvSmooth(gray, gray, CV_GAUSSIAN, 7, 7);
IplImage* canny = cvCreateImage(cvGetSize(img),IPL_DEPTH_8U,1);
IplImage* rgbcanny = cvCreateImage(cvGetSize(img),IPL_DEPTH_8U,3);
cvCanny(gray, canny, 50, 100, 3);
//detect circles
CvSeq* circles = cvHoughCircles(gray, storage, CV_HOUGH_GRADIENT, 1, 35.0, 75, 60,0,0);
cvCvtColor(canny, rgbcanny, CV_GRAY2BGR);
//draw all detected circles
for (int i = 0; i < circles->total; i++)
{
// round the floats to an int
float* p = (float*)cvGetSeqElem(circles, i);
cv::Point center(cvRound(p[0]), cvRound(p[1]));
int radius = cvRound(p[2]);
//uchar* ptr;
//ptr = cvPtr2D(img, center.y, center.x, NULL);
//printf("B: %d G: %d R: %d\n", ptr[0],ptr[1],ptr[2]);
CvScalar s;
s = cvGet2D(img,center.y, center.x);//colour of circle
printf("B: %f G: %f R: %f\n",s.val[0],s.val[1],s.val[2]);
// draw the circle center
cvCircle(img, center, 3, CV_RGB(0,255,0), -1, 8, 0 );
// draw the circle outline
cvCircle(img, center, radius+1, CV_RGB(0,0,255), 2, 8, 0 );
//display coordinates
printf("x: %d y: %d r: %d\n",center.x,center.y, radius);
}
//create window
//cvNamedWindow("circles", 1);
cvNamedWindow("SnookerImage", 1);
//show image in window
//cvShowImage("circles", rgbcanny);
cvShowImage("SnookerImage", img);
cvSaveImage("out.png", img);
//cvDestroyWindow("SnookerImage");
//cvDestroyWindow("circles");
//cvReleaseMemStorage("storage");
cvWaitKey(0);
return 0;
}
If you use the C++ interface, you can use
cv::cvtColor(img, img, CV_BGR2HSV);
See the documentation for cvtColor for more information.
Update:
Reading and writing pixels the slow way (assuming that the HSV values are stored as a cv::Vec3b (doc))
cv::Vec3b pixel = image.at<cv::Vec3b>(0,0); // read pixel (0,0) (make copy)
pixel[0] = 0; // H
pixel[1] = 0; // S
pixel[2] = 0; // V
image.at<cv::Vec3b>(0,0) = pixel; // write pixel (0,0) (copy pixel back to image)
Using the image.at<...>(x, y) (doc, scroll down a lot) notation is quite slow, if you want to manipulate every pixel. There is an article in the documentation on how to access the pixels faster. You can apply the iterator method also like this:
cv::MatIterator_<cv::Vec3b> it = image.begin<cv::Vec3b>(),
it_end = image.end<cv::Vec3b>();
for(; it != it_end; ++it)
{
// work with pixel in here, e.g.:
cv::Vec3b& pixel = *it; // reference to pixel in image
pixel[0] = 0; // changes pixel in image
}
I am detecting circles like in the image. i am trying to read the pixel value of the centres of these circels to get the color of them. I am using cvPtr2D(img, center.x, center.y, NULL);to read the value of each circle in a for loop but i am getting an error the " one of arguments' value is out of range(index is out of range) in inknown function, line 179(which is the line of cvPtr2D(). i dont understand how these values sare out of range. anyone able to help? il post my code
#include <stdio.h>
#include <cv.h>
#include <highgui.h>
#include <math.h>
int main(int argc, char** argv)
{
//load image from directory
IplImage* img = cvLoadImage("C:\\Users\\Nathan\\Desktop\\SnookerPic.png");
IplImage* gray = cvCreateImage(cvGetSize(img), IPL_DEPTH_8U, 1);
CvMemStorage* storage = cvCreateMemStorage(0);
//covert to grayscale
cvCvtColor(img, gray, CV_BGR2GRAY);
// This is done so as to prevent a lot of false circles from being detected
cvSmooth(gray, gray, CV_GAUSSIAN, 7, 7);
IplImage* canny = cvCreateImage(cvGetSize(img),IPL_DEPTH_8U,1);
IplImage* rgbcanny = cvCreateImage(cvGetSize(img),IPL_DEPTH_8U,3);
cvCanny(gray, canny, 50, 100, 3);
//detect circles
CvSeq* circles = cvHoughCircles(gray, storage, CV_HOUGH_GRADIENT, 1, 35.0, 75, 60,0,0);
cvCvtColor(canny, rgbcanny, CV_GRAY2BGR);
//draw all detected circles
for (int i = 0; i < circles->total; i++)
{
// round the floats to an int
float* p = (float*)cvGetSeqElem(circles, i);
cv::Point center(cvRound(p[0]), cvRound(p[1]));
int radius = cvRound(p[2]);
uchar* ptr;
ptr = cvPtr2D(img, center.x, center.y, NULL);
printf("B: %d G: %d R: %d\n", ptr[0],ptr[1],ptr[2]);
//CvScalar c;
//if(center.x > 0 && center.x < 1280 && center.y > 0 && center.y < 720)
//{
//c = cvGet2D(img,center.x, center.y);//colour of circle
//}
// draw the circle center
cvCircle(img, center, 3, CV_RGB(0,255,0), -1, 8, 0 );
// draw the circle outline
cvCircle(img, center, radius+1, CV_RGB(0,0,255), 2, 8, 0 );
//display coordinates
printf("x: %d y: %d r: %d\n",center.x,center.y, radius);
}
//create window
cvNamedWindow("circles", 1);
cvNamedWindow("SnookerImage", 1);
//show image in window
cvShowImage("circles", rgbcanny);
cvShowImage("SnookerImage", img);
cvSaveImage("out.png", img);
//cvDestroyWindow("SnookerImage");
//cvDestroyWindow("circles");
//cvReleaseMemStorage("storage");
cvWaitKey(0);
return 0;
}
You're problem is that the line:
ptr = cvPtr2D(img, center.x, center.y, NULL);
Should be:
ptr = cvPtr2D(img, center.y, center.x, NULL);
Unfortunately, the documentation is not very clear on this. My intuition told me that this was what was happening, but I had to actually grep the OpenCV source code to see how it was used to get a confirmation on this.
You example looks to be working now.
I have detected 22 balls and am struggling to find a way to run a color detection algorithm on these circles to get their colors. I am using HoughCircles to detect the circles but don't know how to check what color these circles are?
Source Code:
#include <stdio.h>
#include <cv.h>
#include <highgui.h>
#include <math.h>
int main(int argc, char** argv)
{
//load image from directory
IplImage* img = cvLoadImage("C:\\Users\\Nathan\\Desktop\\SnookerPic.png");
IplImage* gray = cvCreateImage(cvGetSize(img), IPL_DEPTH_8U, 1);
CvMemStorage* storage = cvCreateMemStorage(0);
//covert to grayscale
cvCvtColor(img, gray, CV_BGR2GRAY);
// This is done so as to prevent a lot of false circles from being detected
cvSmooth(gray, gray, CV_GAUSSIAN, 7, 7);
IplImage* canny = cvCreateImage(cvGetSize(img),IPL_DEPTH_8U,1);
IplImage* rgbcanny = cvCreateImage(cvGetSize(img),IPL_DEPTH_8U,3);
cvCanny(gray, canny, 50, 100, 3);
//detect circles
CvSeq* circles = cvHoughCircles(gray, storage, CV_HOUGH_GRADIENT, 1, 35.0, 75, 60,0,0);
cvCvtColor(canny, rgbcanny, CV_GRAY2BGR);
//draw all detected circles
for (int i = 0; i < circles->total; i++)
{
// round the floats to an int
float* p = (float*)cvGetSeqElem(circles, i);
cv::Point center(cvRound(p[0]), cvRound(p[1]));
int radius = cvRound(p[2]);
cvScalar c = cvGet2D(center.x, center.y);//colour of circle
// draw the circle center
cvCircle(img, center, 3, CV_RGB(0,255,0), -1, 8, 0 );
// draw the circle outline
cvCircle(img, center, radius+1, CV_RGB(0,0,255), 2, 8, 0 );
//display coordinates
printf("x: %d y: %d r: %d\n",center.x,center.y, radius);
}
//create window
cvNamedWindow("circles", 1);
cvNamedWindow("SnookerImage", 1);
//show image in window
cvShowImage("circles", rgbcanny);
cvShowImage("SnookerImage", img);
cvSaveImage("out.png", rgbcanny);
cvWaitKey(0);
return 0;
}
If the balls each have a uniform color, you can check the color at the center:
CvMemStorage* storage = cvCreateMemStorage(0);
cvSmooth(image, image, CV_GAUSSIAN, 5, 5 );
CvSeq* results = cvHoughCircles(
image,
storage,
CV_HOUGH_GRADIENT,
2,
image->width/10
);
for( int i = 0; i < results->total; i++ )
{
float* p = (float*) cvGetSeqElem( results, i );
CvPoint center = cvPoint( cvRound( p[0] ), cvRound( p[1] ) );
CvScalar c = cvGet2D(image, center.x, center.y); //color of the center
}
Haven't tested the code but it should be ok.
EDIT:
Ooops, I forgot one parameter from the Get2D method, the actual image from which to get the color. Changed to the correct form.
We have written our own blob detection library in the open source vision framework:
http://www.simplecv.org
The code to do what you want is as easy as:
img = Image("/path/to/image.png")
blobs = img.findBlobs()
circle_blobs = blobs.filter(blobs.isCircle() == True)
list_of_blobs_colors = circle_blobs.meanColor()
My code is straightforward. i am trying to detect 22 balls but ionly getting a few. I think it has something to do with the CvSeq* circles = cvHoughCircles Can anyone help me please and thank you!
#include <stdio.h>
#include <cv.h>
#include <highgui.h>
#include <math.h>
int main(int argc, char** argv)
{
IplImage* img = cvLoadImage("C:\\Users\\Nathan\\Desktop\\SnookerPic.png");
IplImage* gray = cvCreateImage
(cvGetSize(img), IPL_DEPTH_8U, 1);
CvMemStorage* storage = cvCreateMemStorage(0);
cvCvtColor(img, gray, CV_BGR2GRAY);
// This is done so as to prevent a lot of false circles from being detected
cvSmooth(gray, gray, CV_GAUSSIAN, 7, 7);
IplImage* canny = cvCreateImage(cvGetSize(img),IPL_DEPTH_8U,1);
IplImage* rgbcanny = cvCreateImage(cvGetSize(img),IPL_DEPTH_8U,3);
cvCanny(gray, canny, 50, 100, 3);
CvSeq* circles = cvHoughCircles(gray, storage, CV_HOUGH_GRADIENT, 1, 40.0, 100, 100,0,0);
cvCvtColor(canny, rgbcanny, CV_GRAY2BGR);
for (int i = 0; i < circles->total; i++)
{
// round the floats to an int
float* p = (float*)cvGetSeqElem(circles, i);
cv::Point center(cvRound(p[0]), cvRound(p[1]));
int radius = cvRound(p[2]);
// draw the circle center
cvCircle(img, center, 3, CV_RGB(0,255,0), -1, 8, 0 );
// draw the circle outline
cvCircle(img, center, radius+1, CV_RGB(0,0,255), 2, 8, 0 );
printf("x: %d y: %d r: %d\n",center.x,center.y, radius);
}
cvNamedWindow("circles", 1);
cvNamedWindow("Image", 1);
cvShowImage("circles", rgbcanny);
cvShowImage("Image", img);
cvSaveImage("out.png", rgbcanny);
cvWaitKey(0);
return 0;
}
I believe that the problem comes from your cvHoughCircles parameters:
CvSeq* cvHoughCircles(CvArr* image, CvMemStorage* circleStorage, int method, double dp, double minDist, double param1=100, double param2=100, int minRadius=0, int maxRadius=0 )
minDist – Minimum distance between the centers of the detected circles. If the parameter is too small, multiple neighbor circles may be falsely detected in addition to a true one. If it is too large, some circles may be missed.
You are using maybe a too large minDist (in your case max 2-3 balls will be detected vertically and probably also horizontally).