svm과 머신러닝

ch15/svmplane/main.cpp

@@ -0,0 +1,48 @@
+#include "opencv2/opencv.hpp"
+#include <iostream>
+
+using namespace cv;
+using namespace cv::ml;
+using namespace std;
+
+int main() {
+	Mat train = Mat_<float>({ 8, 2 }, {
+		150, 200, 200, 250, 100, 250, 150, 300,
+		350, 100, 400, 200, 400, 300, 350, 400 });
+	Mat label = Mat_<int>({ 8, 1 }, { 0, 0, 0, 0, 1, 1, 1, 1 });
+
+	Ptr<SVM> svm = SVM::create();
+	svm->setType(SVM::Types::C_SVC);
+	svm->setKernel(SVM::KernelTypes::RBF);
+	svm->trainAuto(train, ROW_SAMPLE, label);
+
+	Mat img = Mat::zeros(Size(500, 500), CV_8UC3);
+
+	for (int j = 0; j < img.rows; j++) {
+		for (int i = 0; i < img.cols; i++) {
+			Mat test = Mat_<float>({ 1, 2 }, { (float)i, (float)j });
+			int res = cvRound(svm->predict(test));
+
+			if (res == 0)
+				img.at<Vec3b>(j, i) = Vec3b(128, 128, 255);
+			else
+				img.at<Vec3b>(j, i) = Vec3b(128, 255, 128);
+		}
+	}
+
+	for (int i = 0; i < train.rows; i++) {
+		int x = cvRound(train.at<float>(i, 0));
+		int y = cvRound(train.at<float>(i, 1));
+		int l = label.at<int>(i, 0);
+
+		if (l == 0)
+			circle(img, Point(x, y), 5, Scalar(0, 0, 128), -1, LINE_AA);
+		else
+			circle(img, Point(x, y), 5, Scalar(0, 128, 0), -1, LINE_AA);
+	}
+
+	imshow("img", img);
+
+	waitKey();
+	return 0;
+}