User,
I want to crop that Triangle on the image and show it in another window with opencv c++. I know all three Coordinates.
Can anyone help me? I did not find any answer on the Internet about "triangle cropping". Thanks!
EDIT: The Problem here is that i cannot use ROI for cropping the Triangle. I have to copy just the triangle without any background or something around. Is it possible to create my own ROI by knowing the Coordinates of the triangle [p1(302,179), p2(329,178), p3(315,205)]?
cv::Mat inputImage = cv::imread("input.png");
if (inputImage.channels() > 1)
{
cv::cvtColor(inputImage, inputImage, CV_RGB2GRAY);
}
// replace these values with your actual coordinates
// I found these by first saving your provided image, then
// using Microsoft Paint
int x0 = 242;
int y0 = 164;
int x1 = 314;
int y1 = 38;
int x2 = 387;
int y2 = 164;
// then create a line masking using these three points
cv::Mat lineMask = cv::Mat::zeros(inputImage.size(), inputImage.type());
cv::line(lineMask, cv::Point(x0, y0), cv::Point(x1, y1), cv::Scalar(255, 255, 0), 1, 8, 0);
cv::line(lineMask, cv::Point(x0, y0), cv::Point(x2, y2), cv::Scalar(255, 255, 0), 1, 8, 0);
cv::line(lineMask, cv::Point(x1, y1), cv::Point(x2, y2), cv::Scalar(255, 255, 0), 1, 8, 0);
// perform contour detection on your line mask
cv::vector<cv::vector<cv::Point>> contours;
cv::vector<cv::Vec4i> hierarchy;
cv::findContours(lineMask, contours, hierarchy, CV_RETR_TREE, CV_CHAIN_APPROX_SIMPLE, cv::Point(0, 0));
// calculate the distance to the contour
cv::Mat raw_dist(lineMask.size(), CV_32FC1);
for (int i = 0; i < lineMask.rows; i++)
{
for (int j = 0; j < lineMask.cols; j++)
{
raw_dist.at<float>(i, j) = cv::pointPolygonTest(contours[0], cv::Point2f(j, i), true);
}
}
double minVal; double maxVal;
cv::minMaxLoc(raw_dist, &minVal, &maxVal, 0, 0, cv::Mat());
minVal = std::abs(minVal);
maxVal = std::abs(maxVal);
// depicting the distances graphically
cv::Mat mask = cv::Mat::zeros(inputImage.size(), CV_8UC1);
for (int i = 0; i < mask.rows; i++)
{
for (int j = 0; j < mask.cols; j++)
{
if (raw_dist.at<float>(i, j) < 0)
{
mask.at<uchar>(i, j) = static_cast<uchar>(0);
continue;
}
mask.at<uchar>(i, j) = static_cast<uchar>(255);
}
}
// inverse the input image
cv::Mat invInput;
cv::bitwise_not(inputImage, invInput);
// then get only the region of your triangle
cv::Mat outputImage;
invInput.copyTo(outputImage, mask);
cv::bitwise_not(outputImage, outputImage);
// display for debugging purpose
cv::imshow("inputImage", inputImage);
cv::imshow("lineMask", lineMask);
cv::imshow("mask", mask);
cv::imshow("outputImage", outputImage);
cv::waitKey();
This is your inputImage:
This is your lineMask:
This is your created binary mask:
And this is your final outputImage:
References:
OpenCV draw line
OpenCV findContours
Point Polygon Test
you can do it by using mask as shown with the code below
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include <iostream>
using namespace cv;
using namespace std;
int main( int, char** argv )
{
Mat src = imread( argv[1] );
Mat gray;
cvtColor(src, gray, COLOR_BGR2GRAY );
gray = gray < 127;
vector<vector<Point> > contours;
findContours(gray, contours,
RETR_EXTERNAL,
CHAIN_APPROX_SIMPLE);
for( size_t i = 0; i< contours.size(); i++ )
{
Rect rect = boundingRect(contours[i]);
Mat mask = gray(rect);
Mat srcROI = src(rect);
srcROI.setTo(Scalar(0,0,255),mask);
imshow("srcROI",srcROI);
waitKey();
}
imshow( "result", src );
waitKey(0);
return(0);
}
EDIT: according the change on the question i suggest the test code below
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
using namespace cv;
using namespace std;
int main( int, char** argv )
{
Mat src = imread("lena.jpg");
vector<Point> points;
points.push_back( Point(200,200));
points.push_back( Point(370,370));
points.push_back( Point(220,410));
Mat mask = Mat::zeros( src.size(), CV_8UC1 );
fillConvexPoly( mask, points, Scalar( 255 ));
Rect rect = boundingRect( points );
Mat roi = src( rect ).clone();
mask = mask( rect ).clone();
rect.x = rect.x - 180;
rect.y = rect.y - 180;
Mat srcROI = src( rect );
roi.copyTo( srcROI, mask );
imshow( "result", src );
waitKey(0);
return(0);
}
As you told that you know co-ordinates of the triangle, using below code you can find triangle.
Mat image = imread("imagePath");
bitwise_not(image, image);
Mat grayImage;
cv::cvtColor(image, grayImage, CV_RGB2GRAY);
cv::vector<cv::vector<cv::Point> > contours;
cv::vector<cv::Vec4i> hierarchy;
cv::findContours(grayImage, contours, hierarchy, CV_RETR_TREE, CV_CHAIN_APPROX_SIMPLE, cv::Point(0, 0));
Mat contourMat(grayImage.size(), grayImage.type(), Scalar(255));
for(int i = 0; i < contours.size(); i++)
{
if(contours[i].data()->x == 314 && contours[i].data()->y == 37)
drawContours(contourMat, contours, i, Scalar(0), CV_FILLED, 8, hierarchy);
}
imshow("WindowName", contourMat);
Hope this will help.
Related
I have an image and I obtained a binary image of it. I would expect a rectangular bounding box, but i didn't get it. This is my code:
vector<vector<Point>> contours;
Vec4i hierarchy;
findContours(binary, contours, CV_RETR_CCOMP, CV_CHAIN_APPROX_SIMPLE, Point(0, 0));
/*Mat drawing = Mat::zeros(binary.size(), CV_8UC3);
for (int i = 0; i < contours.size(); i++)
{
Scalar color = Scalar(rng.uniform(0, 255), rng.uniform(0, 255), rng.uniform(0, 255));
drawContours(drawing, contours, i, color, 1, 8, hierarchy, 0, Point());
}
imshow("contours", drawing);*/
vector<Point> approx, approxRectangle;
Rect bounding_rect(0, 0, 0, 0);
double max_area = 0;
for (int i = 0; i < contours.size(); i++)// xet tung contour
{
approxPolyDP(Mat(contours[i]), approx, arcLength(Mat(contours[i]), true)*0.02, true);
if (approx.size() == 4 && isContourConvex(Mat(approx)))
{
Rect box = boundingRect(contours[i]);
if (bounding_rect.area() == 0){
bounding_rect = box;
approxRectangle = approx;
}
else{
if (bounding_rect.area() < box.area()){
bounding_rect = box;
approxRectangle = approx;
}
}
}
}`
This is my image:
You don't get the desired result, because you're looking for almost rectangular contours, but this won't work since the contours you're interested in is not rectanglar. You can see (in blue) the approximation of that contour (obtained on my binarized image):
This shows you that this is not a reliable constraint.
You can easily solve this, in this case, computing the bounding box for each contour, and keep the largest (in green):
Code:
#include <opencv2/opencv.hpp>
#include <iostream>
#include <algorithm>
using namespace std;
using namespace cv;
int main()
{
// Load image
Mat3b img = imread("path_to_image");
// Convert to grayscale
Mat1b binary;
cvtColor(img, binary, COLOR_BGR2GRAY);
// Binarize (remove anti-aliasing artifacts)
binary = binary > 200;
// Find contours
vector<vector<Point>> contours;
findContours(binary.clone(), contours, RETR_EXTERNAL, CHAIN_APPROX_SIMPLE, Point(0, 0));
// Compute the bounding boxes
vector<Rect> boxes;
for (int i = 0; i < contours.size(); ++i)
{
boxes.push_back(boundingRect(contours[i]));
}
// Find index of largest contours
int idx_largest_box = distance(boxes.begin(), max_element(boxes.begin(), boxes.end(), [](const Rect& lhs, const Rect& rhs) {
return lhs.area() < rhs.area();
}));
// Draw largest box
rectangle(img, boxes[idx_largest_box], Scalar(0,255,0));
imshow("Result", img);
waitKey();
return 0;
}
I have stored the defects using convexity defects in an 4 element vector integer array using vec4i.
My convex hull array is in hull element and contours in Contours;
What i want to do is draw a line from start point of a convexity defect to the end point of one.
For this i need to access the element start index which is present in the vec4i of a defects vector!
How do i do this??
#include <opencv\cv.h>
#include <opencv2\highgui\highgui.hpp>
#include<opencv\cvaux.h>
#include<opencv\cxcore.h>
#include <opencv2\imgproc\imgproc.hpp>
#include <iostream>
#include<conio.h>
#include <stdlib.h>
using namespace cv;
using namespace std;
int main(){
Mat img, frame, img2, img3;
VideoCapture cam(0);
while (true){
cam.read(frame);
cvtColor(frame, img, CV_BGR2HSV);
//thresholding
inRange(img, Scalar(0, 143, 86), Scalar(39, 255, 241), img2);
imshow("hi", img2);
//finding contours
vector<vector<Point>> Contours;
vector<Vec4i> hier;
//morphological transformations
erode(img2, img2, getStructuringElement(MORPH_RECT, Size(3, 3)));
erode(img2, img2, getStructuringElement(MORPH_RECT, Size(3, 3)));
dilate(img2, img2, getStructuringElement(MORPH_RECT, Size(8, 8)));
dilate(img2, img2, getStructuringElement(MORPH_RECT, Size(8, 8)));
//finding the contours required
findContours(img2, Contours, hier, CV_RETR_CCOMP, CV_CHAIN_APPROX_NONE, Point(0, 0));
//finding the contour of largest area and storing its index
int lrgctridx = 0;
int maxarea = 0;
for (int i = 0; i < Contours.size(); i++)
{
double a = contourArea(Contours[i]);
if (a> maxarea)
{
maxarea = a;
lrgctridx = i;
}
}
//convex hulls
vector<vector<Point> >hull(Contours.size());
vector<vector<Vec4i>> defects(Contours.size());
for (int i = 0; i < Contours.size(); i++)
{
convexHull(Contours[i], hull[i], false);
convexityDefects(Contours[i], hull[i], defects[i]);
}
//REQUIRED contour is detected,then convex hell is found and also convexity defects are found and stored in defects
if (maxarea>100){
drawContours(frame, hull, lrgctridx, Scalar(255, 255, 255), 1, 8, vector<Vec4i>(), 0, Point());
\\ drawing the required lines joining defects!im facing problem on how to acheive this since i dont know how to access the elements stored in defects
line(frame, \\startindex, \\endindex, \\color, 1);
}
imshow("output", frame);
char key = waitKey(33);
if (key == 27) break;
}
}
Also my output window shows error when i add the convexityDefects(..) line i think it is in wrong format!
Thanks in advance.
convexityDefects needs a
Convex hull obtained using convexHull() that should contain indices of the contour points that make the hull.
that contains more than 3 indices. So you need this:
vector<vector<Point> >hull(Contours.size());
vector<vector<int> > hullsI(Contours.size()); // Indices to contour points
vector<vector<Vec4i>> defects(Contours.size());
for (int i = 0; i < Contours.size(); i++)
{
convexHull(Contours[i], hull[i], false);
convexHull(Contours[i], hullsI[i], false);
if(hullsI[i].size() > 3 ) // You need more than 3 indices
{
convexityDefects(Contours[i], hullsI[i], defects[i]);
}
}
Then your drawing part is (adapted from here):
/// Draw convexityDefects
for (int i = 0; i < Contours.size(); ++i)
{
for(const Vec4i& v : defects[i])
{
float depth = v[3] / 256;
if (depth > 10) // filter defects by depth, e.g more than 10
{
int startidx = v[0]; Point ptStart(Contours[i][startidx]);
int endidx = v[1]; Point ptEnd(Contours[i][endidx]);
int faridx = v[2]; Point ptFar(Contours[i][faridx]);
line(frame, ptStart, ptEnd, Scalar(0, 255, 0), 1);
line(frame, ptStart, ptFar, Scalar(0, 255, 0), 1);
line(frame, ptEnd, ptFar, Scalar(0, 255, 0), 1);
circle(frame, ptFar, 4, Scalar(0, 255, 0), 2);
}
}
}
Complete code
#include <opencv2\opencv.hpp>
#include <iostream>
using namespace cv;
using namespace std;
int main()
{
Mat img, frame, img2, img3;
VideoCapture cam(0);
while (true){
cam.read(frame);
cvtColor(frame, img, CV_BGR2HSV);
//thresholding
inRange(img, Scalar(0, 143, 86), Scalar(39, 255, 241), img2);
imshow("hi", img2);
//finding contours
vector<vector<Point>> Contours;
vector<Vec4i> hier;
//morphological transformations
erode(img2, img2, getStructuringElement(MORPH_RECT, Size(3, 3)));
erode(img2, img2, getStructuringElement(MORPH_RECT, Size(3, 3)));
dilate(img2, img2, getStructuringElement(MORPH_RECT, Size(8, 8)));
dilate(img2, img2, getStructuringElement(MORPH_RECT, Size(8, 8)));
//finding the contours required
findContours(img2, Contours, hier, CV_RETR_CCOMP, CV_CHAIN_APPROX_NONE, Point(0, 0));
//finding the contour of largest area and storing its index
int lrgctridx = 0;
int maxarea = 0;
for (int i = 0; i < Contours.size(); i++)
{
double a = contourArea(Contours[i]);
if (a> maxarea)
{
maxarea = a;
lrgctridx = i;
}
}
//convex hulls
vector<vector<Point> >hull(Contours.size());
vector<vector<int> > hullsI(Contours.size());
vector<vector<Vec4i>> defects(Contours.size());
for (int i = 0; i < Contours.size(); i++)
{
convexHull(Contours[i], hull[i], false);
convexHull(Contours[i], hullsI[i], false);
if(hullsI[i].size() > 3 )
{
convexityDefects(Contours[i], hullsI[i], defects[i]);
}
}
//REQUIRED contour is detected,then convex hell is found and also convexity defects are found and stored in defects
if (maxarea>100){
drawContours(frame, hull, lrgctridx, Scalar(2555, 0, 255), 3, 8, vector<Vec4i>(), 0, Point());
/// Draw convexityDefects
for(int j=0; j<defects[lrgctridx].size(); ++j)
{
const Vec4i& v = defects[lrgctridx][j];
float depth = v[3] / 256;
if (depth > 10) // filter defects by depth
{
int startidx = v[0]; Point ptStart(Contours[lrgctridx][startidx]);
int endidx = v[1]; Point ptEnd(Contours[lrgctridx][endidx]);
int faridx = v[2]; Point ptFar(Contours[lrgctridx][faridx]);
line(frame, ptStart, ptEnd, Scalar(0, 255, 0), 1);
line(frame, ptStart, ptFar, Scalar(0, 255, 0), 1);
line(frame, ptEnd, ptFar, Scalar(0, 255, 0), 1);
circle(frame, ptFar, 4, Scalar(0, 255, 0), 2);
}
}
}
imshow("output", frame);
char key = waitKey(33);
if (key == 27) break;
}
}
The following code in OpenCV is for me to detect a yellow color ball and draw its convex hull.The code although doesnt give any compilation errors,gives the following error in the output window.
I used the largest area function to avoid smaller unwanted contours.
The error is
Assertion failed <0 <= contourIdx && contourIdx< last> in cv::drawContours ,file C:Buildsmasters..(some path),line 2299****
#include <opencv\cv.h>
#include <opencv2\highgui\highgui.hpp>
#include<opencv\cvaux.h>
#include<opencv\cxcore.h>
#include <opencv2\imgproc\imgproc.hpp>
#include <iostream>
#include<conio.h>
#include <stdlib.h>
using namespace cv;
using namespace std;
int main(){
Mat img, frame, img2, img3;
double maxarea = 0;
int lrgctridx; //largest contour index
VideoCapture cam(0);
while (true){
cam.read(frame);
cvtColor(frame, img, CV_BGR2HSV);
//thresholding
inRange(img, Scalar(0, 143, 86), Scalar(39, 255, 241), img2);
//finding contours
vector<vector<Point>> Contours;
vector<Vec4i> hier;
//morphological transformations
erode(img2, img2, getStructuringElement(MORPH_RECT, Size(3, 3)));
erode(img2, img2, getStructuringElement(MORPH_RECT, Size(3, 3)));
dilate(img2, img2, getStructuringElement(MORPH_RECT, Size(8, 8)));
dilate(img2, img2, getStructuringElement(MORPH_RECT, Size(8, 8)));
//finding the contours required
findContours(img2, Contours, hier, CV_RETR_CCOMP, CV_CHAIN_APPROX_NONE, Point(0, 0));
//finding the contour of largest area and storing its index
for (int i = 0; i < Contours.size(); i++)
{
double a=contourArea(Contours[i]);
if (a> maxarea)
{
maxarea = a;
lrgctridx=i;
}
}
//convex hulls
vector<vector<Point> >hull(Contours.size());
for (int i = 0; i < Contours.size(); i++)
{
convexHull(Contours[i], hull[i], false);
}
//REQUIRED contour is detected,then draw a convex hull
if (maxarea!=0)
drawContours(frame, hull, lrgctridx, Scalar(255, 255, 255), 1, 8, vector<Vec4i>(), 0, Point());
imshow("output", frame);
char key = waitKey(33);
if (key == 27) break;
}
}
Any help would be much appreciated.Thaanks in advance!
You should reset lrgctridx at every iteration.
Say you find a countour at time "t", and you set lrgctridx = 1;. At time "t+1" you don't find any contours, so Contours and hull size will be 0, but you're trying to access position 1.
Just put lrgctridx = 0 before the for loop. Same for maxarea.
lrgctridx = 0;
maxarea = 0;
for (int i = 0; i < Contours.size(); i++)
{
....
Now your condition to draw contours is ok, but you'd better replace it with
if(!Contours.empty()) {
drawContours(...);
....
#include <opencv2/core/core.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/video/background_segm.hpp>
#include <iostream>
#include <windows.h>
using namespace cv;
using namespace std;
//initial min and max HSV filter values.
//these will be changed using trackbars
Mat src; Mat HSV; Mat roi; Mat range; Mat eroded; Mat gray;
int thresh = 100;
int max_thresh = 255;
/** #function main */
int main(int argc, char** argv)
{
createTrackbars();
VideoCapture cap(0); // open the default camera
if (!cap.isOpened()) // check if we succeeded
return -1;
namedWindow("background", 1);
int waitTime = 50;
int counter = 101;
int roiLeft = 20;
int roiTop = 50;
int roiRight = 200;
int roiBottom = 200;
Rect rRoi = Rect(roiLeft, roiTop, roiRight, roiBottom);
Mat background;
cap >> background;
background = background(rRoi);
//cvtColor(background, background, CV_BGR2HSV);
//imshow("background", background);
vector<vector<Point> > contours;
vector<vector < cv::Point >> hull(1);
vector<Vec4i> hierarchy;
vector<CvConvexityDefect> defects;
while (true)
{
cap >> src;
//Create the region of interest.
Mat iRoi = src.clone()(rRoi);
Mat iRoiSRC = src(rRoi);
//Draw a rectangle there.
rectangle(src, rRoi, Scalar(255, 128, 0), 1, 8, 0);
//imshow("roi", iRoi);
//Subtract the static background.
absdiff(iRoi, background, iRoi);
//imshow("diff", iRoi);
//Convert it to a GrayScale and threshold it.
cvtColor(iRoi, iRoi, CV_BGR2GRAY);
threshold(iRoi, gray, 15, 255, CV_THRESH_BINARY);
//Perform a closing.
Mat erodeElement = getStructuringElement(MORPH_ELLIPSE, Size(erodeSize, erodeSize));
Mat dilateElement = getStructuringElement(MORPH_ELLIPSE, Size(dilateSize, dilateSize));
for (int index = 0; index < loopAmount; index++)
{
erode(gray, gray, erodeElement);
dilate(gray, gray, dilateElement);
}
//imshow("range", gray);
//Find the contours.
findContours(gray, contours, hierarchy, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_SIMPLE, Point(0, 0));
//Pick the biggest contour.
int biggestContourIndex = 0;
int largestArea = 0;
for (int i = 0; i < contours.size(); i++)
{
if (contours[i].size() > largestArea)
{
largestArea = contours[i].size();
biggestContourIndex = i;
}
}
vector<int> hullsI;
vector<Point> hullsP;
vector<Vec4i> defects;
//Find the convex hull.
if (contours.size() > 0)
{
convexHull(contours[biggestContourIndex], hullsI, true, true);
convexHull(contours[biggestContourIndex], hullsP, true, true);
}
//Find the convexity defects.
if (contours.size() > 0)
{
if (contours[biggestContourIndex].size() > 3)
{
convexityDefects(contours[biggestContourIndex], hullsI, defects);
}
}
//Draw the biggest contour and its convex hull.
Scalar colorOne = Scalar(255, 128, 0);
Scalar colorTwo = Scalar(0, 0, 255);
if (contours.size() > 0)
{
drawContours(iRoiSRC, contours, biggestContourIndex, colorOne, 2, 8, hierarchy, 0, Point());
drawContours(iRoiSRC, hullsP, 0, colorTwo, 1, 8, vector<Vec4i>(), 0, Point());
rectangle(iRoiSRC, boundingRect(contours[biggestContourIndex]), Scalar(0, 255, 0), 1, 8, 0);
}
imshow("src", src);
if (waitKey(waitTime) >= 0) break;
}
return(0);
}
There is a rectangle in the upper left of the screen, where my hand will be recognized once I hold it there.
The error that i get appears at the first drawContours. The full error which is given to me by the console is: OpenCV Error: Assertion failed <i <0> in cv::_InputArray::getMat, file C:\buildslave64\win64_amdoc1\2_4_PackSlave-win64-vc11-shared\opencv\modules\core\src\matrix.cpp, line 963
I've been extensively searching for a solution on multiple sites, including stackoverflow but none of the solution seem to be working.
Any help would be appreciated.
I use Visual studio 2013 with OpenCV-2.4.10
converting vector<CvConvexityDefect> defects; to a point seemed to do the trick
Base from this here.
I got this error and this is the only one left for almost 3 days of my trial and error in debugging:
Unhandled exception at 0x000007FEEC6315A4 (opencv_imgproc242.dll) in PCA.exe: 0xC0000005: Access violation reading location 0xFFFFFFFFFFFFFFFF.
Please can someone here who can help me with this. Im currently using VS2012 and my os is win7 64-bit. I configure my opencv 2.4.2 following this blog.
Please help!
I've corrected some minor bugs (and now it works perfect for me):
#include <iostream>
#include <opencv2/opencv.hpp>
using namespace cv;
using namespace std;
double getOrientation(vector<Point> &pts, Mat &img)
{
if (pts.size() == 0) return false;
//Construct a buffer used by the pca analysis
Mat data_pts = Mat(pts.size(), 2, CV_64FC1);
for (int i = 0; i < data_pts.rows; ++i)
{
data_pts.at<double>(i, 0) = pts[i].x;
data_pts.at<double>(i, 1) = pts[i].y;
}
//Perform PCA analysis
PCA pca_analysis(data_pts, Mat(), CV_PCA_DATA_AS_ROW);
//Store the position of the object
Point pos = Point(pca_analysis.mean.at<double>(0, 0),
pca_analysis.mean.at<double>(0, 1));
//Store the eigenvalues and eigenvectors
vector<Point2d> eigen_vecs(2);
vector<double> eigen_val(2);
for (int i = 0; i < 2; ++i)
{
eigen_vecs[i] = Point2d(pca_analysis.eigenvectors.at<double>(i, 0),
pca_analysis.eigenvectors.at<double>(i, 1));
eigen_val[i] = pca_analysis.eigenvalues.at<double>(i);
}
// Draw the principal components
circle(img, pos, 3, CV_RGB(255, 0, 255), 2);
line(img, pos, pos + 0.02 * Point(eigen_vecs[0].x * eigen_val[0], eigen_vecs[0].y * eigen_val[0]) , CV_RGB(255, 255, 0));
line(img, pos, pos + 0.02 * Point(eigen_vecs[1].x * eigen_val[1], eigen_vecs[1].y * eigen_val[1]) , CV_RGB(0, 255, 255));
return atan2(eigen_vecs[0].y, eigen_vecs[0].x);
}
int main()
{
// Read the image
Mat bw, img = imread("pca_test1.jpg",1); // "pca_test2.jpg"
// Convert it to greyscale
cvtColor(img, bw, COLOR_BGR2GRAY);
// Apply thresholding
threshold(bw, bw, 150, 255, cv::THRESH_BINARY);
// Find all objects of interest
vector<vector<Point> > contours;
vector<Vec4i> hierarchy;
findContours(bw, contours, hierarchy, cv::RETR_LIST, cv::CHAIN_APPROX_NONE);
// For each object
for (size_t i = 0; i < contours.size(); ++i)
{
// Calculate its area
double area = contourArea(contours[i]);
// Ignore if too small or too large
if (area < 1e2 || 1e5 < area) continue;
// Draw the contour
drawContours(img, contours, i, CV_RGB(255, 0, 0), 2, 8, hierarchy, 0);
// Get the object orientation
getOrientation(contours[i], img);
}
imshow("Image", img);
char key;
while (true)
{
key = waitKey(1);
if (key == 'q') break;
}
cv::destroyAllWindows();
return 0;
}