opencv-识别手写数字

首先拆分图片得到数据

#include "stdafx.h"

#include <iostream>

#include "opencv2/opencv.hpp"

using namespace std;

using namespace cv;

int mainss(int argc, const char** argv)

{

	char ad[128] = { 0 };

	int  filename = 0, filenum = 0;

	Mat img = imread("digits.png");

	Mat gray;

	cvtColor(img, gray, CV_BGR2GRAY);

	int b = 20;

	int m = gray.rows / b;   //原图为1000*2000

	int n = gray.cols / b;   //裁剪为5000个20*20的小图块

	for (int i = 0; i < m; i++)

	{

		int offsetRow = i*b;  //行上的偏移量

		if (i % 5 == 0 && i != 0)

		{

			filename++;

			filenum = 0;

		}

		for (int j = 0; j < n; j++)

		{

			int offsetCol = j*b; //列上的偏移量

			sprintf_s(ad, "C:\\Users\\dongufang\\Documents\\Visual Studio 2015\\Projects\\opencvtest\\opencvtest\\data\\%d\\%d.jpg", filename, filenum++);

			//截取20*20的小块

			Mat tmp;

			gray(Range(offsetRow, offsetRow + b), Range(offsetCol, offsetCol + b)).copyTo(tmp);

			imwrite(ad, tmp);

		}

	}

	return 0;

}

然后knn

#include "stdafx.h"

#include <iostream>

#include <opencv2/opencv.hpp>

#include <opencv2/ml/ml.hpp>

using namespace std;

using namespace cv;

using namespace ml;

char ad[128] = { 0 };

int main()

{

	Mat traindata, trainlabel;

	int k = 5, testnum = 0, truenum = 0;

	//读取训练数据 4000张

	for (int i = 0; i < 10; i++)

	{

		for (int j = 0; j<400; j++)

		{

			sprintf_s(ad, "C:\\Users\\dongufang\\Documents\\Visual Studio 2015\\Projects\\opencvtest\\opencvtest\\data\\%d\\%d.jpg", i, j);

			Mat srcimage = imread(ad);

			srcimage = srcimage.reshape(1, 1);

			traindata.push_back(srcimage);

			trainlabel.push_back(i);

		}

	}

	traindata.convertTo(traindata, CV_32F);

	Ptr<KNearest> knn = KNearest::create();

	knn->setDefaultK(k);

	knn->setIsClassifier(true);

	Ptr<TrainData> tdata = TrainData::create(traindata,ROW_SAMPLE, trainlabel);

	knn->train(tdata);

	cv::Mat nearests(1, k, CV_32F);

	//读取测试数据  1000张

	for (int i = 0; i < 10; i++)

	{

		for (int j = 400; j<500; j++)

		{

			testnum++;

			sprintf_s(ad, "C:\\Users\\dongufang\\Documents\\Visual Studio 2015\\Projects\\opencvtest\\opencvtest\\data\\%d\\%d.jpg", i, j);

			Mat testdata = imread(ad);

			testdata = testdata.reshape(1, 1);

			testdata.convertTo(testdata, CV_32F);

			Mat result;

			int  response = knn->predict(testdata, result);

			if (response == i)

			{

				truenum++;

			}

			cout << "result:" << response << endl;

		}

	}

	cout << "测试总数" << testnum << endl;

	cout << "正确分类数" << truenum << endl;

	cout << "准确率：" << (float)truenum / testnum * 100 << "%" << endl;

	return 0;

}

巴特西

opencv-识别手写数字

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