数字识别

#include <stdio.h>  
#include <time.h>  
#include <opencv2/opencv.hpp>  
#include <opencv/cv.h>  
#include <iostream> 
#include <opencv2/core/core.hpp>  
#include <opencv2/highgui/highgui.hpp>  
#include <opencv2/ml/ml.hpp>  
#include <io.h>

using namespace std;
using namespace cv;
using namespace ml;

int main()
{
	VideoCapture capture(0);
	string modelpath = "G:\数字识别\svm.xml";
	Ptr<SVM> svm = StatModel::load<SVM>(modelpath);
	while (1)
	{
		Mat img;
		capture >> img;//读取当前帧
		vector<vector<Point>> contours;//点容器的容器，用于存放轮廓的点的容器的容器
		vector<Vec4i> hierarchy;//点的指针容器
		Mat dst, tmp;
		img.copyTo(dst);
		cvtColor(dst, dst, COLOR_RGB2GRAY);
		blur(dst, dst, Size(3, 3));
		//GaussianBlur(dst, dst, Size(3, 3), 0.5, 0.5);
		//medianBlur(dst, dst, 3);

		threshold(dst, tmp, 120, 255, CV_THRESH_BINARY_INV);
		findContours(tmp, contours, hierarchy, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_NONE);
		vector<vector<Point>>::iterator It;
		int sum = 1;
		for (It = contours.begin(); It < contours.end(); It++)
		{                       
			Rect rect = boundingRect(*It);
			
			double  weigth = rect.br().x - rect.tl().x;//宽
			double height = rect.br().y - rect.tl().y;//高

			if ((weigth < height) && (height > 50))
			{
				rectangle(img, rect, Scalar(0, 15, 255), 2);
				
				Mat  inMat;
				Mat roi = img(rect);
				cvtColor(roi, inMat, COLOR_RGB2GRAY);
				namedWindow("hhhh", 0);
				imshow("hhhh", roi);
			
				resize(inMat, inMat, Size(8, 16), (0, 0), (0, 0), INTER_AREA);
				Mat p = inMat.reshape(1, 1);
				p.convertTo(p, CV_32FC1);
				int response = (int)svm->predict(p);
				char result[20];
				sprintf_s(result, "result:%d", response);
				putText(img, result, Point(0, 30 * (sum++)), 2, 1, CV_RGB(25, 200, 25));
			}
			
		}
		if (waitKey(1) >= 0)break;//延时30ms
		imshow("bug", img);
	}

	return  0;
}