84 lines
1.8 KiB
C++
84 lines
1.8 KiB
C++
#include "opencv2/opencv.hpp"
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#include <math.h>
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#include <algorithm>
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#include "math.hpp"
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int filter(const cv::Mat& img, cv::Mat output, int seuil) {
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bool detect = false;
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uchar R, G, B;
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int rows = img.rows;
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int cols = img.cols;
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int dim = img.channels();
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int indexNB;
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for (int index=0,indexNB=0;index<dim*rows*cols;index+=dim,indexNB++) {
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detect=0;
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B = img.data[index ];
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G = img.data[index + 1];
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R = img.data[index + 2];
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if ((R>G) && (R>B))
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if (((R-B)>=seuil) || ((R-G)>=seuil))
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detect=1;
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if (detect==1)
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output.data[indexNB]=255;
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else
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output.data[indexNB]=0;
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}
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}
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int main(int argc, char** argv) {
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int seuil=0;
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if (argc > 1) {
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seuil = atol(argv[1]);
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}
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int cmax = 10;
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int N = 5000;
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char detect;
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cv::VideoCapture cap(0);
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if(!cap.isOpened())
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return -1;
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cv::namedWindow("Image",1);
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cv::namedWindow("Detection",1);
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cv::namedWindow("Contours",1);
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while(true) {
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int X, Y, DIM, index;
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unsigned int numc;
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uchar R, G, B;
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std::vector<std::vector<cv::Point>> contours;
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std::vector<cv::Vec4i> hierarchy;
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cv::Mat frame;
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cap >> frame;
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X=frame.rows;
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Y=frame.cols;
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cv::Mat binaire(X,Y,CV_8UC1);
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cv::imshow("Image", frame);
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cv::GaussianBlur(frame, frame, cv::Size(7,7), 1.5, 1.5);
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X=frame.rows;
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Y=frame.cols;
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DIM=frame.channels();
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filter(frame, binaire, seuil);
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cv::imshow("Detection", binaire);
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cv::findContours(binaire, contours, hierarchy, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_NONE);
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cv::Mat Dessin = cv::Mat::zeros(X,Y, CV_8UC1);
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int id = math::max_cont(contours);
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std::cout << contours[id].size() << std::endl;
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std::vector<cv::Point> new_cont = math::simplify_contour(contours[id], cmax);
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cv::drawContours(Dessin, contours, id, 255);
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cv::drawContours(Dessin, new_cont, id, 255);
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cv::imshow("Contours", Dessin);
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if(cv::waitKey(30) == 27) {
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break;
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}
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}
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return 0;
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}
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