I succeeded in using cvDrawContour but when I try to use cvMinRectArea2, it only shows one dot. Any ideas? Here's the source code.
IplImage *src = cvLoadImage("SignImg.jpg",0);
IplImage *dst_img = 0;
IplImage *img = cvCreateImage(cvGetSize(src),8,3);
CvBox2D rect;
CvMemStorage *storage = cvCreateMemStorage ();
CvSeq *contours = 0;
char a[255];
sprintf(&a[0],"%s",openFileDialog1->FileName);
dst_img = cvLoadImage(a,0);
cvFindContours (src, storage, &contours, sizeof(CvContour), CV_RETR_EXTERNAL, CV_CHAIN_APPROX_NONE ,cvPoint(0,0));
cvCvtColor(dst_img,img,CV_GRAY2BGR);
cvDrawContours (img, contours, CV_RGB(255,0,0), cvScalarAll(255),1,1,8,cvPoint(0,0));
rect=cvMinAreaRect2 (contours,0);
cvEllipseBox(img,rect,cvScalarAll(0),5,8,0);
The right way to use cvDrawContours is shown here:
for( ; contour != 0; contour = contour->h_next )
{
CvScalar color = CV_RGB( rand()&255, rand()&255, rand()&255 );
/* replace CV_FILLED with 1 to see the outlines */
cvDrawContours( dst, contour, color, color, -1, CV_FILLED, 8 );
}
If it's not obvious enough, your variable contours is an array and you need to iterate over it and draw each element! Else you will be drawing only the first element of the array.
Related
I have an image and want to detect various objects at a time using opencv methods.
I have tried detecting one object using contouring and using the area to filter other counters. But I need to detect other objects too but they vary in area and length.
Can anyone help me to use any methods for detecting it.
This is the original image:
this is the code that I have tried for detection:
int main()
{
Mat msrc = imread("Task6_Resources/Scratch.jpg", 1);
Mat src = imread("Task6_Resources/Scratch.jpg", 0);
Mat imgblur;
GaussianBlur(src, imgblur, Size(13,13), 0);
cv::Ptr<cv::CLAHE> clahe = cv::createCLAHE();
clahe->setClipLimit(8);
cv::Mat gcimg;
clahe->apply(imgblur, gcimg);
Mat thresh;
threshold(gcimg, thresh, 55, 255, THRESH_BINARY_INV);
Mat th_mina = minareafilter(thresh, 195); //function used to filter small and large blobs
Mat th_maxa = maxareafilter(th_mina, 393);
Mat imdilate;
dilate(th_maxa, imdilate, getStructuringElement(MORPH_RECT, Size(3, 1)), Point(-1, -1), 7);
int largest_area = 0;
int largest_contour_index = 0;
Rect bounding_rect;
vector<vector<Point>> contours;
vector<Vec4i> hierarchy;
findContours(imdilate, contours, hierarchy, RETR_TREE, CHAIN_APPROX_SIMPLE);
cout << "Number of contours" << contours.size() << endl;
//Largest contour according to area
for (int i = 0; i < contours.size(); i++){
double a = contourArea(contours[i], false);
if (a > largest_area) {
largest_area = a;
largest_contour_index = i;
bounding_rect = boundingRect(contours[i]);
}
}
for (int c = 0; c < contours.size(); c++){
printf(" * Contour[%d] Area OpenCV: %.2f - Length: %.2f \n",
c,contourArea(contours[c]), arcLength(contours[c], true));
}
rectangle(msrc, bounding_rect, Scalar(0, 255, 0), 2, 8, 0);
imshow("largest contour", msrc);
waitKey(0);
destroyAllWindows();
return 0;
}
This is the image on which I am applying contouring
After the code I am able to detect the green box using largest area in contouring, but I need to detect those red boxes too. (only the region of red boxes)
The problem is here I cannot apply again area parameter to filter the contours as some other contours have same area as the resultant contour.
The image result required:
I'm trying to find the contour area, but contour area only returns 0
whatever the contour is.
no error shows.
void CMFC_DEMODlg::OnBnClickedRun()
{
CString str;
IplImage* src1 = cvLoadImage("onlyone001.JPG",1);
IplImage* src2 = cvLoadImage("b004.JPG",1);
IplImage* grey = cvCreateImage( cvGetSize(src2), 8, 1 );
IplImage* dst = cvCreateImage( cvGetSize(src2), 8, 3 );
IplImage* F = cvCreateImage( cvGetSize(src2), 8, 1 );
IplImage* W = cvCreateImage( cvGetSize(src2), 8, 1 );
cvCvtColor( src2, grey, CV_BGR2GRAY);
cvThreshold( grey, W,200,255,CV_THRESH_BINARY);
CvSeq* c;
CvSeq* contour;
CvSeq* result;
CvMemStorage* storage = cvCreateMemStorage(0);
int Nc = cvFindContours(
W,
storage,
&contour,
sizeof(CvContour),
CV_RETR_LIST,
CV_CHAIN_APPROX_SIMPLE,
cvPoint(0,0));
double Area;
result = cvApproxPoly(contour, sizeof(CvContour), storage,
CV_POLY_APPROX_DP, cvContourPerimeter(contour)*0.02, 0);
Area = fabs(cvContourArea(result, CV_WHOLE_SEQ));
str.Format("Area: %d\n", Area);
GetDlgItem(IDC_STATIC02)->SetWindowText(str);
str.Format("Nc: %d\n", Nc);
GetDlgItem(IDC_STATIC01)->SetWindowText(str);
m_CvvImage.CopyOf(src2,1);
m_CvvImage.DrawToHDC(Disp_hDC1,Disp_Rect);
m_CvvImage.CopyOf(src1,1);
m_CvvImage.DrawToHDC(Disp_hDC2,Disp_Rect);
m_CvvImage.CopyOf(W,1);
m_CvvImage.DrawToHDC(Disp_hDC3,Disp_Rect);
}
I simply want to calculate the area of each contour in my image. What am I doing wrong?
The points should be placed in the vector in a clock-wise sequence.
Take a square for example:
corners2.push_back(Point(0,0));
corners2.push_back(Point(src.rows-1,0));
corners2.push_back(Point(src.rows-1,src.cols-1));
corners2.push_back(Point(1,src.cols-1));
Im trying to detect the colour of a set of shapes in a black image using OpenCV, for which I use Canny detection. However the color output always comes back as black.
std::vector<std::pair<cv::Point, cv::Vec3b> > Asteroids::DetectPoints(const cv::Mat &image)
{
cv::Mat imageGray;
cv::cvtColor( image, imageGray, CV_BGR2GRAY );
cv::threshold(imageGray, imageGray, 1, 255, cv::THRESH_BINARY);
cv::Mat canny_output;
std::vector<std::vector<cv::Point> > contours;
std::vector<cv::Vec4i> hierarchy;
int thresh = 10;
// Detect edges using canny
cv::Canny( imageGray, canny_output, thresh, thresh*2, 3 );
// Find contours
cv::findContours( canny_output, contours, hierarchy, CV_RETR_LIST, CV_CHAIN_APPROX_NONE, cv::Point(0, 0) );
std::vector<std::pair<cv::Point, cv::Vec3b> > points;
for(unsigned int i = 0; i < contours.size(); i++ )
{
cv::Rect rect = cv::boundingRect(contours[i]);
std::pair<cv::Point, cv::Vec3b> posColor;
posColor.first = cv::Point( rect.tl().x + (rect.size().width / 2), rect.tl().y + (rect.size().height / 2));
posColor.second = image.at<cv::Vec3b>( posColor.first.x, posColor.first.y );
//Dont add teh entry to the list if one with the same color and position is already pressent,
//The contour detection sometimes returns duplicates
bool isInList = false;
for(unsigned int j = 0; j < points.size(); j++)
if(points[j].first == posColor.first && points[j].second == posColor.second)
isInList = true;
if(!isInList)
points.push_back( posColor );
}
return points;
}
I know it has to be an issue with the positions or something along those lines, but I cant figure out what
I might be wrong, but off the top of my head :
Shouldn't this read
posColor.second = image.at<cv::Vec3b>(posColor.first.y, posColor.first.x);
and not the other way around like you did it ?
Matrix notation, not cartesian notation ?
I have written a piece of code that finds the connected components and labels the connected components with letter 'R' using cvPutText. Now instead of Letter'R' i need to print the numbers like 1,2,3,....etc according the no.of connected components. After that i need to find area and print the area of connected components as a text. Can anyone help me with this?
Here is my code:
imagelab=cvCreateImage(cvGetSize(mor),IPL_DEPTH_8U,3);
CvMemStorage* contour_storage = cvCreateMemStorage(0);
CvSeq* contours;
CvFont font;
cvInitFont(&font, CV_FONT_HERSHEY_SIMPLEX, 0.6f, 0.6f, 0, 2);
cvFindContours(mor, contour_storage, &contours, sizeof (CvContour), CV_RETR_CCOMP, CV_CHAIN_APPROX_SIMPLE,cvPoint(0,0));
cvZero(imagelab);
for( ; contours != NULL; contours = contours->h_next )
{
CvScalar color = CV_RGB( rand()&255, rand()&255, rand()&255 );
cvDrawContours( imagelab, contours, color, CV_RGB(255,255,255), -1, CV_FILLED, 8 ,cvPoint(0,0));
CvRect iconBox = cvBoundingRect(contours, 0);
CvPoint center = cvPoint(iconBox.x + (iconBox.width / 2), iconBox.y + (iconBox.height / 2));
int area = abs(cvContourArea(contours, CV_WHOLE_SEQ));
cvPutText(imagelab,"R", center, &font, CV_RGB(255, 255, 255));
}
Thanx.
There are many way's to do that what you need is to convert an integer to a string. Just use a counter. My favorit is using stringstreams
for(int ncount = 0 ; contours != NULL; contours = contours->h_next, ncount++ )
...
std::stringstream str;
str << ncount;
cvPutText(imagelab,str.str(), center, &font, CV_RGB(255, 255, 255));
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()