init

.gitignore

@@ -3,3 +3,4 @@
 ################################################################################
 
 /.vs/08_SVM/v16
+/08_SVM/x64

08_SVM.sln

@@ -0,0 +1,31 @@
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08_SVM/08_SVM.vcxproj

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08_SVM/08_SVM.vcxproj.filters

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08_SVM/08_SVM.vcxproj.user

@@ -0,0 +1,4 @@
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+<Project ToolsVersion="Current" xmlns="http://schemas.microsoft.com/developer/msbuild/2003">
+  <PropertyGroup />
+</Project>

08_SVM/svm_hog.cpp

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+#include <opencv2/opencv.hpp>
+#include <opencv2/core/utility.hpp>
+#include <opencv2/imgproc.hpp>
+#include <opencv2/highgui.hpp>
+//#include <ppencv2/features2d.hpp>
+
+#include <iostream>
+#include <algorithm>
+
+using namespace std;
+using namespace cv;
+using namespace cv::ml;
+
+void svmplane()
+{
+	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); // R
+			else
+				img.at<Vec3b>(j, i) = Vec3b(128, 255, 128); // G
+		}
+	}
+
+	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 (1 == 0)
+			circle(img, Point(x, y), 5, Scalar(0, 0, 128), -1, LINE_AA); // R
+		else
+			circle(img, Point(x, y), 5, Scalar(0, 128, 0), -1, LINE_AA); // G
+	}
+
+	imshow("svm", img);
+	imwrite("svm_result1.png", img);
+	waitKey();
+
+	return;
+}
+
+
+// //
+Ptr<SVM> train_hog_svm(const HOGDescriptor& hog);
+void on_mouse(int event, int X, int y, int flags, void* userdata);
+
+void svmdigits()
+{
+#if _DEBUG
+	cout << "svndigits.exe should be built as Release mode !" << endl;
+	return;
+#endif
+
+	HOGDescriptor hog(Size(20, 20), Size(10, 10), Size(5, 5), Size(5, 5), 9);
+	Ptr<SVM> svm = train_hog_svm(hog);
+
+	if (svm.empty())
+	{
+		cerr << "Training failed! " << endl;
+		return;
+	}
+
+	Mat img = Mat::zeros(400, 400, CV_8U);
+	imshow("img", img);
+	setMouseCallback("img", on_mouse, (void*)&img);
+
+	while (true)
+	{
+		int c = waitKey();
+
+		if (c == 27)
+			break;
+		else if (c == ' ')
+		{
+			Mat img_resize;
+			resize(img, img_resize, Size(20, 20), 0, 0, INTER_AREA);
+
+			vector<float> desc;
+			hog.compute(img_resize, desc);
+			Mat desc_mat(desc);
+			int res = cvRound(svm->predict(desc_mat.t()));
+			cout << res << endl;
+
+			img.setTo(0);
+			imshow("img", img);
+		}
+	}
+
+	return;
+}
+
+Ptr<SVM> train_hog_svm(const HOGDescriptor& hog)
+{
+	Mat digits = imread("digits.png", IMREAD_GRAYSCALE);
+
+	if (digits.empty())
+	{
+		cerr << "Image load failed!" << endl;
+		return 0;
+	}
+
+	Mat train_hog, train_labels;
+
+	for (int j = 0; j < 50; j++)
+	{
+		for (int i = 0; i < 100; i++)
+		{
+			Mat roi = digits(Rect(i * 20, j * 20, 20, 20));
+			vector<float> desc;
+
+			hog.compute(roi, desc);
+			Mat desc_mat(desc);
+
+			train_hog.push_back(desc_mat.t());
+			train_labels.push_back(j / 5);
+		}
+	}
+
+	Ptr<SVM> svm = SVM::create();
+	svm->setType(SVM::Types::C_SVC);
+	svm->setKernel(SVM::KernelTypes::RBF);
+	svm->setC(2.5);
+	svm->setGamma(0.50625);
+	svm->train(train_hog, ROW_SAMPLE, train_labels);
+
+	return svm;
+}
+
+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);
+		imwrite("svm_result2.png", img);
+	}
+}
+
+// //
+void hog()
+{
+	VideoCapture cap("vtest.avi");
+	if (!cap.isOpened())
+	{
+		cerr << "Video open failed!" << endl;
+		return;
+	}
+
+	HOGDescriptor hog;
+	hog.setSVMDetector(HOGDescriptor::getDefaultPeopleDetector());
+
+	Mat frame;
+	while (true)
+	{
+		cap >> frame;
+		if (frame.empty())
+			break;
+
+		vector<Rect> detected;
+		hog.detectMultiScale(frame, detected);
+
+		for (Rect r : detected) {
+			Scalar c = Scalar(rand() % 256, rand() % 256, rand() % 256);
+			rectangle(frame, r, c, 3);
+		}
+
+		imshow("frame", frame);
+
+		if (waitKey(10) == 27)
+			break;
+	}
+}
+
+
+int main()
+{
+	svmplane();
+	svmdigits();
+	//hog();
+}