Added Neural network code

NeuralDetector/Training.cpp

@@ -0,0 +1,148 @@
+#include "Training.h"
+
+using namespace cv;
+using namespace std;
+
+
+Training::Training()
+{
+
+}
+
+
+Training::~Training()
+{
+}
+
+void Training::CreateTrainingSet()
+{
+	Camera cam = Camera(1);
+	bool running = true;
+
+	while (running)
+	{
+		string in;
+		cout << "Ready for next category" << endl;
+		cout << "Please specifiy name or type exit to stop: ";
+		cin >> in;
+
+		if (in == "exit")
+		{
+			running = false;
+			break;
+		}
+
+		bool takingPhotos = true;
+		int i = 0;
+
+		while (takingPhotos)
+		{
+			Mat image;
+			image = cam.getImage();
+
+			imshow("Live feed", image);
+			
+			int key = waitKey(100);
+			switch (key)
+			{
+			case 32:
+				imwrite("training/" + in + "_" + to_string(i) + ".bmp", image);
+				cout << "Image taken #" << i << endl;
+				i++;
+				break;
+			case 27:
+				destroyWindow("Live feed");
+				takingPhotos = false;
+				running = false;
+				break;
+			case 110:
+				destroyWindow("Live feed");
+				takingPhotos = false;
+			default:
+				break;
+			}
+		}
+	}
+}
+
+void Training::LoadTrainingSet()
+{
+	NeuralNetwork bpn;
+
+	Mat ITset = Mat_<double>();
+	Mat OTset = Mat_<double>();
+
+	vector<string> files;
+	string dir = "training/";
+	
+	read_directory(dir, files);
+
+	cout << "Found " << files.size()-2 << " files in " << dir << endl;
+
+	random_shuffle(files.begin(), files.end());
+
+	for (string file : files)
+	{
+		string loc = dir + file;
+
+		Mat image;
+		image = imread(loc, CV_LOAD_IMAGE_COLOR);
+
+		if (!image.data)
+			continue;
+
+		cout << "Loaded " << file << endl;
+
+		string classname;
+		class_name(file, classname);
+
+		Mat gray_image, binaryImage;
+		cvtColor(image, gray_image, CV_BGR2GRAY);
+		threshold(gray_image, binaryImage, 200, 1, CV_THRESH_BINARY_INV);
+
+		//Extract Features
+		vector<Point> contour;
+		FeatureExtractor::findContour(gray_image, contour);
+		FeatureExtractor ftext = FeatureExtractor(contour);
+
+		Mat descriptors;
+		ftext.Extract(descriptors);
+		Mat output;
+		bpn.getClass(classname, output);
+
+		ITset.push_back<double>(descriptors);
+		OTset.push_back<double>(output);
+	}
+
+	destroyAllWindows();
+
+	cout << "Finished loading all files" << endl;
+
+	bpn.Train(ITset, OTset);
+
+	cout << "Training complete" << endl;
+
+	cin.ignore();
+}
+
+
+
+void Training::read_directory(const string& name, vector<string> &v)
+{
+	string pattern = name;
+	pattern.append("\\*");
+	WIN32_FIND_DATA data;
+	HANDLE hFind;
+	if ((hFind = FindFirstFile(pattern.c_str() , &data)) != INVALID_HANDLE_VALUE) {
+		do {
+			v.push_back(data.cFileName);
+		} while (FindNextFile(hFind, &data) != 0);
+		FindClose(hFind);
+	}
+}
+
+void Training::class_name(const string& name, string& classname)
+{
+	string::size_type const p(name.find_last_of('_'));
+	classname = name.substr(0, p);
+}