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#include "opencv2/ml/ml.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include <iostream>
#include <stdio.h>
#include <curses.h>
#include <iomanip>
using namespace cv;
using namespace std;
#define SX 20
#define PATH "/home/supernova/Desktop/Resources/"
void createInputVec(Mat_<float>,Mat_<int>);
Mat trainPrePos(Mat);
int main() {
Mat_<float> featureVector(10,SX*SY);
Mat_<int> labelVector(1,10);
createInputVec(featureVector,labelVector);
Ptr<ml::KNearest> knn(ml::KNearest::create());
knn->train(featureVector, ml::ROW_SAMPLE, labelVector);
Mat img =imread("/home/supernova/Desktop/Resources/0.png");
img = trainPrePos(img);
img = img.reshape(1,1);
Mat_<float> test(1,SX*SY);
for(int i=0;i<1;++i) {
test.at<float>(0,i)=float(img.at<uchar>(0,i));
}
float ans;
Mat res,dist;
ans=knn->findNearest(test, 1, noArray(),res,dist);
std::cout << ans<< "\n";
std::cout << dist ;
getch();
return 0;
}
void createInputVec(Mat_<float> features,Mat_<int> labels) {
Mat img;
char file[255];
for (int j = 0; j < 2; j++) {
sprintf(file, "%s%d.png", PATH, j);
img = imread(file, 1);
if (!img.data) {
std::cout << "File " << file << " not found\n";
exit(1);
}
img = trainPrePos(img);
imshow("after img = trainPrePos(img)", img);
img = img.reshape(1,1);
imshow("after img.reshape(1,1)", img);
cout << img.size() << endl;
for(int i=0;i<SX*SY;++i) {
cout << "img.at<float>(0,i =" << i << " j " << j << "|" << img.at<float>(0,i) <<")" << endl;
features.at<float>(j,i)=float(img.at<uchar>(0,i));
}
labels.at<int>(0,j)=j;
cout << "labels" << labels.at<float>(0,j) << endl;
}
}
Mat trainPrePos(Mat img) A
{
imshow("Image Before BGRA2GRAY", img);
cvtColor(img,img,cv::COLOR_BGRA2GRAY);
imshow("Image After BGRA2GRAY", img);
GaussianBlur(img, img, Size(5, 5), 2, 2);
imshow("After GaussianBlur", img);
adaptiveThreshold(img, img, 255, cv::ADAPTIVE_THRESH_MEAN_C, cv::THRESH_BINARY, 11, 2);
imshow("After adaptiveThreshold", img);
THRESH_BINARY = 0,
THRESH_BINARY_INV = 1,
THRESH_TRUNC = 2,
THRESH_TOZERO = 3,
THRESH_TOZERO_INV = 4,
THRESH_MASK = 7,
THRESH_OTSU = 8,
THRESH_TRIANGLE = 16,
};
std::vector<std::vector<Point> >contours;
Mat contourImage,out;
img.copyTo(contourImage);
findContours(contourImage, contours, cv::RETR_EXTERNAL, CHAIN_APPROX_SIMPLE);
cout << "Total contours" << contours.size() << endl;
int idx = 0;
size_t area = 0;
for (size_t i = 0; i < contours.size(); i++) {
cout << "i = "<< i << "controurse[i].size" << contours[i].size() << endl;
if (area < contours[i].size() ) {
idx = i;
area = contours[i].size();
}
}
Rect rec = boundingRect(contours[idx]);
resize(img(rec),out, Size(SX, SY));
for (int q = 0; q < 5; q++)
cout << "q" << q << contours[q];
waitKey(0);
return out;
}
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