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Open Source Computer Vision Library
https://opencv.org/
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269 lines
10 KiB
269 lines
10 KiB
8 months ago
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/*******************************************************************************
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*
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* This program demonstrates various shape fitting techniques using OpenCV.
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* It reads an image, applies binary thresholding, and then detects contours.
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*
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* For each contour, it fits and draws several geometric shapes including
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* convex hulls, minimum enclosing circles, rectangles, triangles, and ellipses
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* using different fitting methods:
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* 1: OpenCV's original method fitEllipse which implements Fitzgibbon 1995 method.
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* 2: The Approximate Mean Square (AMS) method fitEllipseAMS proposed by Taubin 1991
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* 3: The Direct least square (Direct) method fitEllipseDirect proposed by Fitzgibbon1999
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*
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* The results are displayed with unique colors
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* for each shape and fitting method for clear differentiation.
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*
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*
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*********************************************************************************/
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#include "opencv2/imgproc.hpp"
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#include "opencv2/highgui.hpp"
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#include <iostream>
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#include <vector>
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using namespace cv;
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using namespace std;
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const string hot_keys =
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"\n\nHot keys: \n"
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"\tESC - quit the program\n"
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"\tq - quit the program\n"
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"\tc - make the circle\n"
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"\tr - make the rectangle\n"
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"\th - make the convexhull\n"
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"\tt - make the triangle\n"
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"\te - make the ellipse\n"
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"\ta - make all shapes\n"
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"\t0 - use OpenCV's method for ellipse fitting\n"
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"\t1 - use Approximate Mean Square (AMS) method for ellipse fitting \n"
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"\t2 - use Direct least square (Direct) method for ellipse fitting\n";
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static void help(char** argv)
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{
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cout << "\nThis program demonstrates various shape fitting techniques on a set of points using functions: \n"
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<< "minAreaRect(), minEnclosingTriangle(), minEnclosingCircle(), convexHull(), and ellipse().\n\n"
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<< "Usage: " << argv[0] << " [--image_name=<image_path> Default: ellipses.jpg]\n\n";
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cout << hot_keys << endl;
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}
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void processImage(int, void*);
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void drawShapes(Mat &img, const vector<Point> &points, int ellipseMethod, string shape);
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void drawConvexHull(Mat &img, const vector<Point> &points);
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void drawMinAreaRect(Mat &img, const vector<Point> &points);
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void drawFittedEllipses(Mat &img, const vector<Point> &points, int ellipseMethod);
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void drawMinEnclosingCircle(Mat &img, const vector<Point> &points);
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void drawMinEnclosingTriangle(Mat &img, const vector<Point> &points);
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// Shape fitting options
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Mat image;
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enum EllipseFittingMethod {
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OpenCV_Method,
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AMS_Method,
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Direct_Method
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};
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struct UserData {
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int sliderPos = 70;
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string shape = "--all";
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int ellipseMethod = OpenCV_Method;
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};
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const char* keys =
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"{help h | | Show help message }"
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"{@image |ellipses.jpg| Path to input image file }";
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int main(int argc, char** argv) {
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cv::CommandLineParser parser(argc, argv, keys);
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help(argv);
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if (parser.has("help"))
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{
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return 0;
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}
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UserData userData; // variable to pass all the necessary values to trackbar callback
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string filename = parser.get<string>("@image");
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image = imread(samples::findFile(filename), IMREAD_COLOR); // Read the image from the specified path
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if (image.empty()) {
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cout << "Could not open or find the image" << endl;
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return -1;
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}
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namedWindow("Shapes", WINDOW_AUTOSIZE); // Create a window to display the results
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createTrackbar("Threshold", "Shapes", NULL, 255, processImage, &userData); // Create a threshold trackbar
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setTrackbarPos("Threshold", "Shapes", userData.sliderPos);
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for(;;) {
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char key = (char)waitKey(0); // Listen for a key press
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if (key == 'q' || key == 27) break; // Exit the loop if 'q' or ESC is pressed
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switch (key) {
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case 'h': userData.shape = "--convexhull"; break;
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case 'a': userData.shape = "--all"; break;
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case 't': userData.shape = "--triangle"; break;
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case 'c': userData.shape = "--circle"; break;
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case 'e': userData.shape = "--ellipse"; break;
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case 'r': userData.shape = "--rectangle"; break;
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case '0': userData.ellipseMethod = OpenCV_Method; break;
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case '1': userData.ellipseMethod = AMS_Method; break;
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case '2': userData.ellipseMethod = Direct_Method; break;
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default: break; // Do nothing for other keys
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}
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processImage(userData.sliderPos, &userData); // Process the image with the current settings
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}
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return 0;
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}
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// Function to draw the minimum enclosing circle around given points
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void drawMinEnclosingCircle(Mat &img, const vector<Point> &points) {
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Point2f center;
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float radius = 0;
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minEnclosingCircle(points, center, radius); // Find the enclosing circle
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// Draw the circle
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circle(img, center, cvRound(radius), Scalar(0, 0, 255), 2, LINE_AA);
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}
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// Function to draw the minimum enclosing triangle around given points
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void drawMinEnclosingTriangle(Mat &img, const vector<Point> &points) {
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vector<Point> triangle;
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minEnclosingTriangle(points, triangle); // Find the enclosing triangle
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if (triangle.size() != 3) {
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return;
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}
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// Use polylines to draw the triangle. The 'true' argument closes the triangle.
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polylines(img, triangle, true, Scalar(255, 0, 0), 2, LINE_AA);
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}
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// Function to draw the minimum area rectangle around given points
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void drawMinAreaRect(Mat &img, const vector<Point> &points) {
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RotatedRect box = minAreaRect(points); // Find the minimum area rectangle
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Point2f vtx[4];
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box.points(vtx);
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// Convert Point2f to Point because polylines expects a vector of Point
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vector<Point> rectPoints;
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for (int i = 0; i < 4; i++) {
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rectPoints.push_back(Point(cvRound(vtx[i].x), cvRound(vtx[i].y)));
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}
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// Use polylines to draw the rectangle. The 'true' argument closes the loop, drawing a rectangle.
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polylines(img, rectPoints, true, Scalar(0, 255, 0), 2, LINE_AA);
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}
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// Function to draw the convex hull of given points
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void drawConvexHull(Mat &img, const vector<Point> &points) {
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vector<Point> hull;
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convexHull(points, hull, false); // Find the convex hull
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// Draw the convex hull
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polylines(img, hull, true, Scalar(255, 255, 0), 2, LINE_AA);
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}
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inline static bool isGoodBox(const RotatedRect& box) {
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//size.height >= size.width awalys,only if the pts are on a line or at the same point,size.width=0
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return (box.size.height <= box.size.width * 30) && (box.size.width > 0);
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}
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// Function to draw fitted ellipses using different methods
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void drawFittedEllipses(Mat &img, const vector<Point> &points, int ellipseMethod) {
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switch (ellipseMethod) {
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case OpenCV_Method: // Standard ellipse fitting
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{
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RotatedRect fittedEllipse = fitEllipse(points);
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if (isGoodBox(fittedEllipse)) {
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ellipse(img, fittedEllipse, Scalar(255, 0, 255), 2, LINE_AA);
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}
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putText(img, "OpenCV", Point(img.cols - 80, 20), FONT_HERSHEY_SIMPLEX, 0.5, Scalar(255, 0, 255), 2, LINE_AA);
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}
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break;
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case AMS_Method: // AMS ellipse fitting
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{
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RotatedRect fittedEllipseAMS = fitEllipseAMS(points);
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if (isGoodBox(fittedEllipseAMS)) {
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ellipse(img, fittedEllipseAMS, Scalar(255, 0, 255), 2, LINE_AA);
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}
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putText(img, "AMS", Point(img.cols - 80, 20), FONT_HERSHEY_SIMPLEX, 0.5, Scalar(255, 0, 255), 2, LINE_AA);
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}
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break;
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case Direct_Method: // Direct ellipse fitting
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{
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RotatedRect fittedEllipseDirect = fitEllipseDirect(points);
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if (isGoodBox(fittedEllipseDirect)) {
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ellipse(img, fittedEllipseDirect, Scalar(255, 0, 255), 2, LINE_AA);
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}
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putText(img, "Direct", Point(img.cols - 80, 20), FONT_HERSHEY_SIMPLEX, 0.5, Scalar(255, 0, 255), 2, LINE_AA);
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}
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break;
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default: // Default case falls back to OpenCV method
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{
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RotatedRect fittedEllipse = fitEllipse(points);
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if (isGoodBox(fittedEllipse)) {
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ellipse(img, fittedEllipse, Scalar(255, 0, 255), 2, LINE_AA);
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}
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putText(img, "OpenCV (default)", Point(img.cols - 80, 20), FONT_HERSHEY_SIMPLEX, 0.5, Scalar(255, 0, 255), 2, LINE_AA);
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cout << "Warning: Invalid ellipseMethod value. Falling back to default OpenCV method." << endl;
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}
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break;
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}
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}
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// Function to draw shapes
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void drawShapes(Mat &img, const vector<Point> &points, int ellipseMethod, string shape) {
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if (shape == "--circle") {
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drawMinEnclosingCircle(img, points);
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} else if (shape == "--triangle") {
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drawMinEnclosingTriangle(img, points);
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} else if (shape == "--rectangle") {
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drawMinAreaRect(img, points);
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} else if (shape == "--convexhull") {
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drawConvexHull(img, points);
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} else if (shape == "--ellipse"){
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drawFittedEllipses(img, points, ellipseMethod);
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}
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else if (shape == "--all") {
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drawMinEnclosingCircle(img, points);
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drawMinEnclosingTriangle(img, points);
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drawMinAreaRect(img, points);
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drawConvexHull(img, points);
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drawFittedEllipses(img, points, ellipseMethod);
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}
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}
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// Main function to process the image based on the current trackbar position
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void processImage(int position, void* userData){
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UserData* data = static_cast<UserData*>(userData);
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data->sliderPos = position;
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Mat processedImg = image.clone(); // Clone the original image for processing
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Mat gray;
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cvtColor(processedImg, gray, COLOR_BGR2GRAY); // Convert to grayscale
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threshold(gray, gray, data->sliderPos, 255, THRESH_BINARY); // Apply binary threshold
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Mat filteredImg;
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medianBlur(gray, filteredImg, 3);
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vector<vector<Point>> contours;
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findContours(filteredImg, contours, RETR_EXTERNAL, CHAIN_APPROX_SIMPLE); // Find contours
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if (contours.empty()) {
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return;
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}
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imshow("Mask", filteredImg); // Show the mask
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for (size_t i = 0; i < contours.size(); ++i) {
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if (contours[i].size() < 5) { // Check if the contour has enough points
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continue;
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}
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drawShapes(processedImg, contours[i], data->ellipseMethod, data->shape);
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}
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imshow("Shapes", processedImg); // Display the processed image with fitted shapes
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}
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