OpenCV  4.5.1
Open Source Computer Vision
samples/cpp/tutorial_code/ml/introduction_to_pca/introduction_to_pca.cpp

Check the corresponding tutorial for more details

#include "opencv2/core.hpp"
#include <iostream>
using namespace std;
using namespace cv;
// Function declarations
void drawAxis(Mat&, Point, Point, Scalar, const float);
double getOrientation(const vector<Point> &, Mat&);
void drawAxis(Mat& img, Point p, Point q, Scalar colour, const float scale = 0.2)
{
double angle = atan2( (double) p.y - q.y, (double) p.x - q.x ); // angle in radians
double hypotenuse = sqrt( (double) (p.y - q.y) * (p.y - q.y) + (p.x - q.x) * (p.x - q.x));
// Here we lengthen the arrow by a factor of scale
q.x = (int) (p.x - scale * hypotenuse * cos(angle));
q.y = (int) (p.y - scale * hypotenuse * sin(angle));
line(img, p, q, colour, 1, LINE_AA);
// create the arrow hooks
p.x = (int) (q.x + 9 * cos(angle + CV_PI / 4));
p.y = (int) (q.y + 9 * sin(angle + CV_PI / 4));
line(img, p, q, colour, 1, LINE_AA);
p.x = (int) (q.x + 9 * cos(angle - CV_PI / 4));
p.y = (int) (q.y + 9 * sin(angle - CV_PI / 4));
line(img, p, q, colour, 1, LINE_AA);
}
double getOrientation(const vector<Point> &pts, Mat &img)
{
//Construct a buffer used by the pca analysis
int sz = static_cast<int>(pts.size());
Mat data_pts = Mat(sz, 2, CV_64F);
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(), PCA::DATA_AS_ROW);
//Store the center of the object
Point cntr = Point(static_cast<int>(pca_analysis.mean.at<double>(0, 0)),
static_cast<int>(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, cntr, 3, Scalar(255, 0, 255), 2);
Point p1 = cntr + 0.02 * Point(static_cast<int>(eigen_vecs[0].x * eigen_val[0]), static_cast<int>(eigen_vecs[0].y * eigen_val[0]));
Point p2 = cntr - 0.02 * Point(static_cast<int>(eigen_vecs[1].x * eigen_val[1]), static_cast<int>(eigen_vecs[1].y * eigen_val[1]));
drawAxis(img, cntr, p1, Scalar(0, 255, 0), 1);
drawAxis(img, cntr, p2, Scalar(255, 255, 0), 5);
double angle = atan2(eigen_vecs[0].y, eigen_vecs[0].x); // orientation in radians
return angle;
}
int main(int argc, char** argv)
{
// Load image
CommandLineParser parser(argc, argv, "{@input | pca_test1.jpg | input image}");
parser.about( "This program demonstrates how to use OpenCV PCA to extract the orientation of an object.\n" );
parser.printMessage();
Mat src = imread( samples::findFile( parser.get<String>("@input") ) );
// Check if image is loaded successfully
if(src.empty())
{
cout << "Problem loading image!!!" << endl;
return EXIT_FAILURE;
}
imshow("src", src);
// Convert image to grayscale
Mat gray;
cvtColor(src, gray, COLOR_BGR2GRAY);
// Convert image to binary
Mat bw;
threshold(gray, bw, 50, 255, THRESH_BINARY | THRESH_OTSU);
// Find all the contours in the thresholded image
vector<vector<Point> > contours;
for (size_t i = 0; i < contours.size(); i++)
{
// Calculate the area of each contour
double area = contourArea(contours[i]);
// Ignore contours that are too small or too large
if (area < 1e2 || 1e5 < area) continue;
// Draw each contour only for visualisation purposes
drawContours(src, contours, static_cast<int>(i), Scalar(0, 0, 255), 2);
// Find the orientation of each shape
getOrientation(contours[i], src);
}
imshow("output", src);
return EXIT_SUCCESS;
}
void drawAxis(InputOutputArray image, InputArray cameraMatrix, InputArray distCoeffs, InputArray rvec, InputArray tvec, float length)
Draw coordinate system axis from pose estimation.
Point2i Point
Definition: types.hpp:194
std::string String
Definition: cvstd.hpp:150
Point_< double > Point2d
Definition: types.hpp:193
Scalar_< double > Scalar
Definition: types.hpp:669
#define CV_64F
Definition: interface.h:79
cv::String findFile(const cv::String &relative_path, bool required=true, bool silentMode=false)
Try to find requested data file.
#define CV_PI
Definition: cvdef.h:354
Quat< T > sin(const Quat< T > &q)
Quat< S > sqrt(const Quat< S > &q, QuatAssumeType assumeUnit=QUAT_ASSUME_NOT_UNIT)
Quat< T > cos(const Quat< T > &q)
__device__ __forceinline__ float1 atan2(const uchar1 &a, const uchar1 &b)
Definition: vec_math.hpp:812
@ circle
Definition: gr_skig.hpp:62
void imshow(const String &winname, InputArray mat)
Displays an image in the specified window.
int waitKey(int delay=0)
Waits for a pressed key.
CV_EXPORTS_W Mat imread(const String &filename, int flags=IMREAD_COLOR)
Loads an image from a file.
void cvtColor(InputArray src, OutputArray dst, int code, int dstCn=0)
Converts an image from one color space to another.
@ COLOR_BGR2GRAY
convert between RGB/BGR and grayscale, color conversions
Definition: imgproc.hpp:546
void line(InputOutputArray img, Point pt1, Point pt2, const Scalar &color, int thickness=1, int lineType=LINE_8, int shift=0)
Draws a line segment connecting two points.
void drawContours(InputOutputArray image, InputArrayOfArrays contours, int contourIdx, const Scalar &color, int thickness=1, int lineType=LINE_8, InputArray hierarchy=noArray(), int maxLevel=INT_MAX, Point offset=Point())
Draws contours outlines or filled contours.
@ LINE_AA
antialiased line
Definition: imgproc.hpp:811
double threshold(InputArray src, OutputArray dst, double thresh, double maxval, int type)
Applies a fixed-level threshold to each array element.
@ THRESH_BINARY
Definition: imgproc.hpp:320
@ THRESH_OTSU
flag, use Otsu algorithm to choose the optimal threshold value
Definition: imgproc.hpp:326
double contourArea(InputArray contour, bool oriented=false)
Calculates a contour area.
void findContours(InputArray image, OutputArrayOfArrays contours, OutputArray hierarchy, int mode, int method, Point offset=Point())
Finds contours in a binary image.
@ CHAIN_APPROX_NONE
Definition: imgproc.hpp:434
@ RETR_LIST
Definition: imgproc.hpp:418
void scale(cv::Mat &mat, const cv::Mat &range, const T min, const T max)
Definition: quality_utils.hpp:90
"black box" representation of the file storage associated with a file on disk.
Definition: affine.hpp:52