svm과 머신러닝

ch15/knndigits/main.cpp

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+#include "opencv2/opencv.hpp"
+#include <iostream>
+
+using namespace cv;
+using namespace cv::ml;
+using namespace std;
+
+Ptr<KNearest> train_knn();
+
+void on_mouse(int event, int x, int y, int flags, void* userdata);
+
+int main() {
+	Ptr<KNearest> knn = train_knn();
+
+	Mat img = Mat::zeros(400, 400, CV_8U);
+
+	imshow("img", img);
+	setMouseCallback("img", on_mouse, (void*)&img);
+
+	while (true) {
+		int c = waitKey(0);
+
+		if (c == 27)
+			break;
+		else if (c == ' ') {
+			Mat img_resize, img_float, img_flatten, res;
+
+			resize(img, img_resize, Size(20, 20), 0, 0, INTER_AREA);
+			img_resize.convertTo(img_float, CV_32F);
+			img_flatten = img_float.reshape(1, 1);
+
+			knn->findNearest(img_flatten, 3, res);
+			cout << cvRound(res.at<float>(0, 0)) << endl;
+
+			img.setTo(0);
+			imshow("img", img);
+		}
+	}
+
+	return 0;
+}
+
+Ptr<KNearest> train_knn() {
+	Mat digits = imread("../../resources/images/digits.png", IMREAD_GRAYSCALE);
+
+	Mat train_images, train_labels;
+
+	for (int j = 0; j < 50; j++) {
+		for (int i = 0; i < 100; i++) {
+			Mat roi, roi_float, roi_flatten;
+			roi = digits(Rect(i * 20, j * 20, 20, 20));
+			roi.convertTo(roi_float, CV_32F);
+			roi_flatten = roi_float.reshape(1, 1);
+
+			train_images.push_back(roi_flatten);
+			train_labels.push_back(j / 5);
+		}
+	}
+
+	Ptr<KNearest> knn = KNearest::create();
+	knn->train(train_images, ROW_SAMPLE, train_labels);
+
+	return knn;
+}
+
+Point ptPrev(-1, -1);
+
+void on_mouse(int event, int x, int y, int flags, void* userdata) {
+	Mat img = *(Mat*)userdata;
+
+	if (event == EVENT_LBUTTONDOWN) {
+		ptPrev = Point(x, y);
+	}
+	else if (event == EVENT_LBUTTONUP) {
+		ptPrev = Point(-1, -1);
+	}
+	else if (event == EVENT_MOUSEMOVE && (flags & EVENT_FLAG_LBUTTON)) {
+		line(img, ptPrev, Point(x, y), Scalar::all(255), 40, LINE_AA, 0);
+		ptPrev = Point(x, y);
+
+		imshow("img", img);
+	}
+}