#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();

	if (knn.empty()) {
		cerr << "Training failed!" << endl;
		return -1;
	}

	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, 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("digits.png", IMREAD_GRAYSCALE);

	if (digits.empty()) {
		cerr << "Image load failed!" << endl;
		return 0;
	}

	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);
	}
}
