#include "opencv2/imgproc.hpp"
#include "opencv2/highgui.hpp"
#include <iostream>
using namespace cv;
using namespace std;

//第一個(gè)參數(shù)：輸入圖片名稱(chēng)；第二個(gè)參數(shù)：輸出圖片名稱(chēng)
void GetContoursPic(const char* pSrcFileName, const char* pDstFileName)
{
	Mat srcImg = imread(pSrcFileName);
	imshow("原始圖", srcImg);
	Mat gray, binImg;
	//灰度化
	cvtColor(srcImg, gray, COLOR_RGB2GRAY);
	imshow("灰度圖", gray);
	//二值化
	threshold(gray, binImg, 100, 200, CV_THRESH_BINARY);
	imshow("二值化", binImg);

	vector<vector<Point> > contours;
	vector<Rect> boundRect(contours.size());
	//注意第5個(gè)參數(shù)為CV_RETR_EXTERNAL，只檢索外框  
	findContours(binImg, contours, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_NONE); //找輪廓
	cout << contours.size() << endl;
	for (int i = 0; i < contours.size(); i++)
	{
		//需要獲取的坐標(biāo)  
		CvPoint2D32f rectpoint[4];
		CvBox2D rect =minAreaRect(Mat(contours[i]));

		cvBoxPoints(rect, rectpoint); //獲取4個(gè)頂點(diǎn)坐標(biāo)  
		//與水平線(xiàn)的角度  
		float angle = rect.angle;
		cout << angle << endl;

		int line1 = sqrt((rectpoint[1].y - rectpoint[0].y)*(rectpoint[1].y - rectpoint[0].y) + (rectpoint[1].x - rectpoint[0].x)*(rectpoint[1].x - rectpoint[0].x));
		int line2 = sqrt((rectpoint[3].y - rectpoint[0].y)*(rectpoint[3].y - rectpoint[0].y) + (rectpoint[3].x - rectpoint[0].x)*(rectpoint[3].x - rectpoint[0].x));
		//rectangle(binImg, rectpoint[0], rectpoint[3], Scalar(255), 2);
		//面積太小的直接pass
		if (line1 * line2 < 600)
		{
			continue;
		}

		//為了讓正方形橫著放，所以旋轉(zhuǎn)角度是不一樣的。豎放的，給他加90度，翻過(guò)來(lái)  
		if (line1 > line2) 
		{
			angle = 90 + angle;
		}

		//新建一個(gè)感興趣的區(qū)域圖，大小跟原圖一樣大  
		Mat RoiSrcImg(srcImg.rows, srcImg.cols, CV_8UC3); //注意這里必須選CV_8UC3
		RoiSrcImg.setTo(0); //顏色都設(shè)置為黑色  
		//imshow("新建的ROI", RoiSrcImg);
		//對(duì)得到的輪廓填充一下  
		drawContours(binImg, contours, -1, Scalar(255),CV_FILLED);

		//摳圖到RoiSrcImg
		srcImg.copyTo(RoiSrcImg, binImg);


		//再顯示一下看看，除了感興趣的區(qū)域，其他部分都是黑色的了  
		namedWindow("RoiSrcImg", 1);
		imshow("RoiSrcImg", RoiSrcImg);

		//創(chuàng)建一個(gè)旋轉(zhuǎn)后的圖像  
		Mat RatationedImg(RoiSrcImg.rows, RoiSrcImg.cols, CV_8UC1);
		RatationedImg.setTo(0);
		//對(duì)RoiSrcImg進(jìn)行旋轉(zhuǎn)  
		Point2f center = rect.center;  //中心點(diǎn)  
		Mat M2 = getRotationMatrix2D(center, angle, 1);//計(jì)算旋轉(zhuǎn)加縮放的變換矩陣 
		warpAffine(RoiSrcImg, RatationedImg, M2, RoiSrcImg.size(),1, 0, Scalar(0));//仿射變換 
		imshow("旋轉(zhuǎn)之后", RatationedImg);
		imwrite("r.jpg", RatationedImg); //將矯正后的圖片保存下來(lái)
	}

#if 1
	//對(duì)ROI區(qū)域進(jìn)行摳圖

	//對(duì)旋轉(zhuǎn)后的圖片進(jìn)行輪廓提取  
	vector<vector<Point> > contours2;
	Mat raw = imread("r.jpg");
	Mat SecondFindImg;
	//SecondFindImg.setTo(0);
	cvtColor(raw, SecondFindImg, COLOR_BGR2GRAY);  //灰度化  
	threshold(SecondFindImg, SecondFindImg, 80, 200, CV_THRESH_BINARY);
	findContours(SecondFindImg, contours2, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_NONE);
	//cout << "sec contour:" << contours2.size() << endl;

	for (int j = 0; j < contours2.size(); j++)
	{
		//這時(shí)候其實(shí)就是一個(gè)長(zhǎng)方形了，所以獲取rect  
		Rect rect = boundingRect(Mat(contours2[j]));
		//面積太小的輪廓直接pass,通過(guò)設(shè)置過(guò)濾面積大小，可以保證只拿到外框
		if (rect.area() < 600)
		{
			continue;
		}
		Mat dstImg = raw(rect);
		imshow("dst", dstImg);
		imwrite(pDstFileName, dstImg);
	}
#endif


}


void main()
{
	GetContoursPic("6.jpg", "FinalImage.jpg");
	waitKey();
}

#include "opencv2/imgproc.hpp"
#include "opencv2/highgui.hpp"
#include <iostream>
using namespace cv;
using namespace std;

#define ERROR 1234

//度數(shù)轉(zhuǎn)換
double DegreeTrans(double theta)
{
	double res = theta / CV_PI * 180;
	return res;
}


//逆時(shí)針旋轉(zhuǎn)圖像degree角度（原尺寸）    
void rotateImage(Mat src, Mat& img_rotate, double degree)
{
	//旋轉(zhuǎn)中心為圖像中心    
	Point2f center;
	center.x = float(src.cols / 2.0);
	center.y = float(src.rows / 2.0);
	int length = 0;
	length = sqrt(src.cols*src.cols + src.rows*src.rows);
	//計(jì)算二維旋轉(zhuǎn)的仿射變換矩陣  
	Mat M = getRotationMatrix2D(center, degree, 1);
	warpAffine(src, img_rotate, M, Size(length, length), 1, 0, Scalar(255,255,255));//仿射變換，背景色填充為白色  
}

//通過(guò)霍夫變換計(jì)算角度
double CalcDegree(const Mat &srcImage, Mat &dst)
{
	Mat midImage, dstImage;

	Canny(srcImage, midImage, 50, 200, 3);
	cvtColor(midImage, dstImage, CV_GRAY2BGR);

	//通過(guò)霍夫變換檢測(cè)直線(xiàn)
	vector<Vec2f> lines;
	HoughLines(midImage, lines, 1, CV_PI / 180, 300, 0, 0);//第5個(gè)參數(shù)就是閾值，閾值越大，檢測(cè)精度越高
	//cout << lines.size() << endl;

	//由于圖像不同，閾值不好設(shè)定，因?yàn)殚撝翟O(shè)定過(guò)高導(dǎo)致無(wú)法檢測(cè)直線(xiàn)，閾值過(guò)低直線(xiàn)太多，速度很慢
	//所以根據(jù)閾值由大到小設(shè)置了三個(gè)閾值，如果經(jīng)過(guò)大量試驗(yàn)后，可以固定一個(gè)適合的閾值。

	if (!lines.size())
	{
		HoughLines(midImage, lines, 1, CV_PI / 180, 200, 0, 0);
	}
	//cout << lines.size() << endl;

	if (!lines.size())
	{
		HoughLines(midImage, lines, 1, CV_PI / 180, 150, 0, 0);
	}
	//cout << lines.size() << endl;
	if (!lines.size())
	{
		cout << "沒(méi)有檢測(cè)到直線(xiàn)！" << endl;
		return ERROR;
	}

	float sum = 0;
	//依次畫(huà)出每條線(xiàn)段
	for (size_t i = 0; i < lines.size(); i++)
	{
		float rho = lines[i][0];
		float theta = lines[i][1];
		Point pt1, pt2;
		//cout << theta << endl;
		double a = cos(theta), b = sin(theta);
		double x0 = a*rho, y0 = b*rho;
		pt1.x = cvRound(x0 + 1000 * (-b));
		pt1.y = cvRound(y0 + 1000 * (a));
		pt2.x = cvRound(x0 - 1000 * (-b));
		pt2.y = cvRound(y0 - 1000 * (a));
		//只選角度最小的作為旋轉(zhuǎn)角度
		sum += theta;

		line(dstImage, pt1, pt2, Scalar(55, 100, 195), 1, LINE_AA); //Scalar函數(shù)用于調(diào)節(jié)線(xiàn)段顏色

		imshow("直線(xiàn)探測(cè)效果圖", dstImage);
	}
	float average = sum / lines.size(); //對(duì)所有角度求平均，這樣做旋轉(zhuǎn)效果會(huì)更好

	cout << "average theta:" << average << endl;

	double angle = DegreeTrans(average) - 90;

	rotateImage(dstImage, dst, angle);
	//imshow("直線(xiàn)探測(cè)效果圖2", dstImage);
	return angle;
}


void ImageRecify(const char* pInFileName, const char* pOutFileName)
{
	double degree;
	Mat src = imread(pInFileName);
	imshow("原始圖", src);
	Mat dst;
	//傾斜角度矯正
	degree = CalcDegree(src,dst);
	if (degree == ERROR)
	{
		cout << "矯正失??！" << endl;
		return;
	}
	rotateImage(src, dst, degree);
	cout << "angle:" << degree << endl;
	imshow("旋轉(zhuǎn)調(diào)整后", dst);

	Mat resulyImage = dst(Rect(0, 0, dst.cols, 500)); //根據(jù)先驗(yàn)知識(shí)，估計(jì)好文本的長(zhǎng)寬，再裁剪下來(lái)
	imshow("裁剪之后", resulyImage);
	imwrite("recified.jpg", resulyImage); 
}


int main()
{
	ImageRecify("correct2.jpg", "FinalImage.jpg");
	waitKey();
	return 0;
}