找挡板最终程序

快来打我* 2022-10-25 01:35 123阅读 0赞

/****************************************************************** 程序说明放置挡板，为了保证挡板不超过误差， 更新时间：8月19日18点 更新时间：8月20日16点 *******************************************************************/
    
    #include "Dangban.h"
    extern VideoCapture cap_up;
    extern VideoCapture cap_down;
    extern Mat imgOriginal_up, imgOriginal_down;//用于缓存图像
    
    extern int G_threshold_down;
    extern int G_threshold_up;
    
    //RGB转HSV
    void RGB2HSV(double red, double green, double blue, double& hue, double& saturation, double& intensity)
    { 
    
    	double r, g, b;
    	double h, s, i;
    
    	double sum;
    	double minRGB, maxRGB;
    	double theta;
    
    	r = red / 255.0;
    	g = green / 255.0;
    	b = blue / 255.0;
    
    	minRGB = ((r<g) ? (r) : (g));
    	minRGB = (minRGB<b) ? (minRGB) : (b);
    
    	maxRGB = ((r>g) ? (r) : (g));
    	maxRGB = (maxRGB>b) ? (maxRGB) : (b);
    
    	sum = r + g + b;
    	i = sum / 3.0;
    
    	if (i<0.001 || maxRGB - minRGB<0.001)
    	{ 
    		h = 0.0;
    		s = 0.0;
    	}
    	else
    	{ 
    		s = 1.0 - 3.0*minRGB / sum;
    		theta = sqrt((r - g)*(r - g) + (r - b)*(g - b));
    		theta = acos((r - g + r - b)*0.5 / theta);
    		if (b <= g)
    			h = theta;
    		else
    			h = 2 * 3.1415926 - theta;
    		if (s <= 0.01)
    			h = 0;
    	}
    
    	hue = (int)(h * 180 / 3.1415926);
    	saturation = (int)(s * 100);
    	intensity = (int)(i * 100);
    }
    //
    ///***** 求两点间距离*****/
    //float getDistance(CvPoint pointO, CvPoint pointA)
    //{ 
    // float distance;
    // distance = powf((pointO.x - pointA.x), 2) + powf((pointO.y - pointA.y), 2);
    // distance = sqrtf(distance);
    // return distance;
    //}
    
    //原点到直线的距离
    //输入一堆直线，返回直线到坐标原点的距离
    vector <float> get_0_distance(vector<Vec4i> lines)
    { 
    	vector <float> diatance;
    
    	for (unsigned int i = 0; i < lines.size(); i++)
    	{ 
    		double k = (double)(lines[i][1] - lines[i][3]) / (double)(lines[i][0] - lines[i][2]);//斜率
    		double b = (double)lines[i][1] - (double)(lines[i][0])* k; //截距
    		double diatance_temp = fabs(b / sqrt(1 + k*k));
    		diatance.push_back(diatance_temp);
    	}
    	return diatance;
    
    }
    
    /***** 点到直线的距离:P到AB的距离*****/
    //P为线外一点，AB为线段两个端点,有正负，点在左边为负，右边为正
    float getDist_P2L_zhengfu(CvPoint pointP, CvPoint pointA, CvPoint pointB)
    { 
    	//求直线方程
    	float A = 0, B = 0, C = 0;
    	A = pointA.y - pointB.y;
    	B = pointB.x - pointA.x;
    	C = pointA.x*pointB.y - pointA.y*pointB.x;
    	//代入点到直线距离公式
    	float distance = 0;
    
    
    	if (pointP.x>(-(B*pointP.y + C) / A))
    	{ //点在线右边
    		distance = ((float)abs(A*pointP.x + B*pointP.y + C)) / ((float)sqrtf(A*A + B*B));
    	}
    	else
    	{ //点在线左边
    		distance = -((float)abs(A*pointP.x + B*pointP.y + C)) / ((float)sqrtf(A*A + B*B));
    	}
    	return distance;
    }
    
    
    /***** 点到直线的距离:P到AB的距离*****/
    //P为线外一点，剩下三个参数为直线一般式参数，0为横挡板，1为竖挡板
    float getDist_P2L_zhengfu_2(CvPoint pointP, float Param_A1, float Param_A2, float Param_A3,int mode)
    { 
    	//求直线方程
    	float A = 0, B = 0, C = 0;
    	A = Param_A1;
    	B = Param_A2;
    	C = Param_A3;
    	//代入点到直线距离公式
    	float distance = 0;
    	if (mode == 0)//横挡板判断上下
    	{ 
    		if (pointP.y>(-(A*pointP.x + C) / B))
    		{ //点在线上面
    			distance = ((float)abs(A*pointP.x + B*pointP.y + C)) / ((float)sqrtf(A*A + B*B));
    		}
    		else
    		{ //点在线下面
    			distance = -((float)abs(A*pointP.x + B*pointP.y + C)) / ((float)sqrtf(A*A + B*B));
    		}
    	}
    	else  //竖挡板判断左右
    	{ 
    		if (pointP.x>(-(B*pointP.y + C) / A))
    		{ //点在线右边
    			distance = ((float)abs(A*pointP.x + B*pointP.y + C)) / ((float)sqrtf(A*A + B*B));
    		}
    		else
    		{ //点在线左边
    			distance = -((float)abs(A*pointP.x + B*pointP.y + C)) / ((float)sqrtf(A*A + B*B));
    		}
    
    	}
    
    	return distance;
    }
    
    
    //输入一堆直线，返回每条直线与水平直线的角度，为弧度
    vector <float> get_lines_arctan(vector<Vec4i> lines)
    { 
    	float k = 0; //直线斜率
    	vector <float> lines_arctan;//直线斜率的反正切值
    	for (unsigned int i = 0; i<lines.size(); i++)
    	{ 
    
    		k = (double)(lines[i][3] - lines[i][1]) / (double)(lines[i][2] - lines[i][0]); //求出直线的斜率
    		lines_arctan.push_back(atan(k));
    	}
    	return lines_arctan;
    }
    
    /***** 点到一堆直线的距离:P到lines的距离*****/
    vector <float> getDist_P2L_yibanshi(Point2f pointP, vector<Vec4i> lines)
    { 
    	//求直线方程
    	Point2f pointA, pointB;
    	vector <float>  distance;
    	for (unsigned int i = 0; i < lines.size(); i++)
    	{ 
    
    		pointA.x = (float)lines[i][0];
    		pointA.y = (float)lines[i][1];
    		pointB.x = (float)lines[i][2];
    		pointB.x = (float)lines[i][3];
    
    		float A = 0, B = 0, C = 0;
    		A = pointA.y - pointB.y;
    		B = pointB.x - pointA.x;
    		C = pointA.x*pointB.y - pointA.y*pointB.x;
    		//代入点到直线距离公式
    		float distance_temp;
    		distance_temp = ((float)abs(A*pointP.x + B*pointP.y + C)) / ((float)sqrtf(A*A + B*B));
    
    		distance.push_back(distance_temp);
    	}
    	return distance;
    }
    
    
    
    //输入一堆直线，返回每条直线的斜率和截距
    //Vec2f为2个点的float，参照存储直线的数据结构
    vector <Point2d> get_lines_fangcheng(vector<Vec4i> lines)
    { 
    	double k = 0; //直线斜率
    	double b = 0; //直线截距
    	vector <Point2d> lines_fangcheng;//
    
    	for (unsigned int i = 0; i<lines.size(); i++)
    	{ 
    
    		k = (double)(lines[i][3] - lines[i][1]) / (double)(lines[i][2] - lines[i][0]); //求出直线的斜率// -3.1415926/2-----+3.1415926/2
    		b = (double)lines[i][1] - k * (double)lines[i][0]; //求出直线的截距
    		lines_fangcheng.push_back(Point2d(k, b));
    	}
    
    	return lines_fangcheng;
    }
    
    
    //填充
    void fillHole(const Mat srcBw, Mat &dstBw)
    { 
    	Size m_Size = srcBw.size();
    	Mat Temp = Mat::zeros(m_Size.height + 2, m_Size.width + 2, srcBw.type());//延展图像
    	srcBw.copyTo(Temp(Range(1, m_Size.height + 1), Range(1, m_Size.width + 1)));
    
    	cv::floodFill(Temp, Point(0, 0), Scalar(255, 255, 255));//填充区域
    
    	Mat cutImg;//裁剪延展的图像
    	Temp(Range(1, m_Size.height + 1), Range(1, m_Size.width + 1)).copyTo(cutImg);
    
    	dstBw = srcBw | (~cutImg);
    }
    
    
    
    
    //输入一堆直线，返回每条直线的一般式方程
    //Vec2f为2个点的float，参照存储直线的数据结构
    vector <float> get_lines_yibanshi_fangcheng(vector<Vec4i> lines)
    { 
    	//1.分别求角点0、1与角点2、3所对应的两根直线
    	//vector <vector<float>> fangcheng_PARAM;
    	vector<float> fangcheng_temp;
    
    	for (unsigned int i = 0; i < lines.size(); i++)
    	{ 
    		float A0 = 0, B0 = 0, C0 = 0;
    		A0 = (float)(lines[i][1] - lines[i][3]);
    		if ((lines[i][1] - lines[i][3]) == 0)
    		{ 
    			A0 = 0.0001;
    		}
    		B0 = (float)(lines[i][2] - lines[i][0]);
    		if ((lines[i][2] - lines[i][0]) == 0)
    		{ 
    			B0 = 0.0001;
    		}
    		C0 = (float)(lines[i][0] * lines[i][3] - lines[i][1] * lines[i][2]);
    		if (C0 == 0)
    		{ 
    			C0 = 0.0001;
    		}
    		/* if ((lines[i][2] - lines[i][0]) == 0) { B0 =0.001; if (A0>0) { C0 =-fabs( (float)(lines[i][0] * lines[i][3] - lines[i][1] * lines[i][2])); } else { C0 = fabs((float)(lines[i][0] * lines[i][3] - lines[i][1] * lines[i][2])); } } else { B0 = (float)(lines[i][2] - lines[i][0]); C0 = (float)(lines[i][0] * lines[i][3] - lines[i][1] * lines[i][2]); } */
    
    		//A0 = (float)(Connor[0].y - Connor[1].y);
    		//B0 = (float)(Connor[1].x - Connor[0].x);
    		//C0 = (float)(Connor[0].x*Connor[1].y - Connor[0].y*Connor[1].x);
    		fangcheng_temp.push_back(A0);
    		fangcheng_temp.push_back(B0);
    		fangcheng_temp.push_back(C0);
    
    		// fangcheng_PARAM.push_back(fangcheng_temp);
    
    	}
    	return fangcheng_temp;
    }
    
    
    
    
    /******************************************************************************************* *函数功能 ： 输入两条直线（每条直线以斜率和截距确定），返回两直线夹角，0为弧度，1为角度（不能计算垂直直线） *输入参数 ： line_1_k为一条直线斜率，line_2_k为另一条直线斜率，aaa为0则为弧度，反之则为角度 *返 回 值 ： float型弧度或者角度,有正负，为直线2相对于直线1的角度 *编写时间 ： 2018.8.5 *作 者 ： 毛哥 ********************************************************************************************/
    float get_lines_arctan(float line_1_k, float line_2_k, int aaa)
    { 
    	if (aaa == 0)
    	{ 
    		float tan_k = 0; //直线夹角正切值
    		float lines_arctan;//直线斜率的反正切值
    		tan_k = (line_2_k - line_1_k) / (1 + line_2_k*line_1_k); //求直线夹角的公式
    		lines_arctan = atan(tan_k);
    		return lines_arctan;
    	}
    	else
    	{ 
    		float tan_k = 0; //直线夹角正切值
    		float lines_arctan;//直线斜率的反正切值
    		tan_k = (line_2_k - line_1_k) / (1 + line_2_k*line_1_k); //求直线夹角的公式
    		lines_arctan = atan(tan_k)* 180.0 / 3.1415926;
    
    		return lines_arctan;
    	}
    }
    
    
    /******************************************************************************************* *函数功能 ： 输入两条直线(输入一般式三个参数)，返回两直线夹角，0为弧度 *输入参数 ： Param_A1、Param_B1、Param_C1 \Param_2、Param_B2、Param_C2输入一般式三个参数 *返 回 值 ： double 型角度,有正负，为直线2相对于直线1的角度 *编写时间 ： 2018.8.6 *作 者 ： 毛哥 ********************************************************************************************/
    double get_lines_yibanshi_arctan(double Param_A1, double Param_B1, double Param_C1, double Param_A2, double Param_B2, double Param_C2)
    { 
    
    	double tan_k = 0; //直线夹角正切值
    	double lines_arctan;//直线斜率的反正切值
    	double line_1_k = 0;
    	double line_2_k = 0;
    
    	// tan_k = (line_2_k - line_1_k) / (1 + line_2_k*line_1_k); //求直线夹角的公式
    
    	if (fabs(Param_B1) > 0.00001 && fabs(Param_B2) > 0.00001)
    	{ 
    		line_1_k = -Param_A1 / Param_B1;
    		line_2_k = -Param_A2 / Param_B2;
    
    		//若两直线垂直，即k1k2 = －1，此时夹角为90°；
    		if (line_1_k*line_2_k != -1)
    		{ 
    			tan_k = (line_2_k - line_1_k) / (1 + line_2_k*line_1_k); //求直线夹角的公式
    			//tan_k = (Param_A1*Param_A2 + Param_B1*Param_B2) / (sqrt(Param_A1*Param_A1 + Param_B1*Param_B1)*sqrt(Param_A2*Param_A2 + Param_B2*Param_B2));
    			lines_arctan = atan(tan_k)* 180.0 / 3.1415926;;
    		}
    	}
    	else if (Param_B1 < 0.00001&& Param_B2>0.00001)
    	{ 
    
    		tan_k = -Param_A2 / Param_B2;
    		lines_arctan = atan(tan_k);
    		lines_arctan = (3.1415926 / 2 - lines_arctan)* 180.0 / 3.1415926;
    	}
    	else if (Param_B1 > 0.00001&&Param_B2 < 0.00001)
    	{ 
    
    		tan_k = -Param_A1 / Param_B1;
    		lines_arctan = atan(tan_k);
    		lines_arctan = (lines_arctan - 3.1415926 / 2)* 180.0 / 3.1415926;
    
    	}
    	else
    	{ 
    		lines_arctan = 0;
    	}
    	return lines_arctan;
    }
    
    
    
    
    
    
    //输入一直线的两个端点，返回该直线的一般式方程
    vector <float> get_lines_yibanshi_fangcheng_2(Point2f Point_A, Point2f Point_B)
    { 
    	//1.分别求角点0、1与角点2、3所对应的两根直线
    	//vector <vector<float>> fangcheng_PARAM;
    	vector<float> fangcheng_temp;
    	float A0 = 0, B0 = 0, C0 = 0;
    
    	//A0 = (float)(lines[i][1] - lines[i][3]);
    	//B0 = (float)(lines[i][2] - lines[i][0]);
    	//C0 = (float)(lines[i][0] * lines[i][3] - lines[i][1] * lines[i][2]);
    
    	A0 = (float)(Point_A.y - Point_B.y);
    	B0 = (float)(Point_B.x - Point_A.x);
    	C0 = (float)(Point_A.x*Point_B.y - Point_A.y*Point_B.x);
    	fangcheng_temp.push_back(A0);
    	fangcheng_temp.push_back(B0);
    	fangcheng_temp.push_back(C0);
    
    	//fangcheng_PARAM.push_back(fangcheng_temp);
    
    	return fangcheng_temp;
    }
    
    
    /***** 7、输入A，B，C,画出线在dstImage*****/
    void draw_line_1(float A, float B, float C, Mat dstImage)
    { 
    	//Ax+By+C=0
    	float y0, y1, x0, x1;
    	if (B == 0)
    	{ 
    		B = 0.001;
    	}
    	if (A == 0)
    	{ 
    		A = 0.001;
    	}
    	float k = 0, b = 0;
    	k = -A / B;
    	b = -C / B;
    	y0 = k * 0.0 + b;
    	y1 = k * 800.0 + b;
    	x0 = (0.0 - b) / k;
    	x1 = (600.0 - b) / k;
    
    	vector<Point> draw_point;
    	if (y0 >= 0 && y0 <= 600)
    	{ 
    		Point p;
    		p.x = 0;
    		p.y = y0;
    		draw_point.push_back(p);
    	}
    	if (y1 >= 0 && y1 <= 600)
    	{ 
    		Point p;
    		p.x = 800;
    		p.y = y1;
    		draw_point.push_back(p);
    	}
    	if (x0 >= 0 && x0 <= 800)
    	{ 
    		Point p;
    		p.x = x0;
    		p.y = 0;
    		draw_point.push_back(p);
    	}
    	if (x1 >= 0 && x1 <= 800)
    	{ 
    		Point p;
    		p.x = x1;
    		p.y = 600;
    		draw_point.push_back(p);
    	}
    	if (draw_point.size() >= 2)
    	{ 
    		line(dstImage, draw_point[0], draw_point[1], Scalar(0, 0, 255), 2, LINE_AA);
    	}
    }
    /******************************************************************************************* *函数功能 ： 找每个轮廓的中心坐标 *输入参数 ：轮廓或者凸包 *返 回 值 ： 点向量 *编写时间 ： 2018.8.9 *作 者 ： 毛哥 ********************************************************************************************/
    vector< Point2f> find_lunkuo_zhongxin(vector<vector<Point>> dangban_RectContours)
    { 
    
    	vector<Point2f> zhongxin_zuobiao;
    	/// 计算矩
    	vector<Moments> mu(dangban_RectContours.size());
    	for (int i = 0; i < dangban_RectContours.size(); i++)
    	{ 
    		mu[i] = moments(dangban_RectContours[i], false);
    	}
    	/// 计算中心矩:
    	vector<Point2f> mc(dangban_RectContours.size());
    	for (int i = 0; i < dangban_RectContours.size(); i++)
    	{ 
    		mc[i] = Point2f(mu[i].m10 / mu[i].m00, mu[i].m01 / mu[i].m00);
    		zhongxin_zuobiao.push_back(mc[i]);
    	}
    
    	return	zhongxin_zuobiao;
    
    }
    
    /*函数功能：求两条直线交点*/
    /*输入：两条Vec4i类型直线*/
    /*返回：Point2f类型的点*/
    Point2f getCrossPoint(Vec4i LineA, Vec4i LineB)
    { 
    	double ka, kb;
    	Point2f crossPoint;
    	if ((LineA[2] - LineA[0]) != 0)
    	{ 
    		ka = (double)(LineA[3] - LineA[1]) / (double)(LineA[2] - LineA[0]); //求出LineA斜率
    		kb = (double)(LineB[3] - LineB[1]) / (double)(LineB[2] - LineB[0]); //求出LineB斜率
    
    
    		crossPoint.x = (ka*LineA[0] - LineA[1] - kb*LineB[0] + LineB[1]) / (ka - kb);
    		crossPoint.y = (ka*kb*(LineA[0] - LineB[0]) + ka*LineB[1] - kb*LineA[1]) / (ka - kb);
    	}
    
    
    	return crossPoint;
    }
    //两点之间距离
    float getDistance_1(CvPoint pointO, CvPoint pointA)
    { 
    	float distance;
    	distance = powf((pointO.x - pointA.x), 2) + powf((pointO.y - pointA.y), 2);
    	distance = sqrtf(distance);
    	return distance;
    }
    
    
    /******************************************************************************************* *函数功能 ： 用于顶部摄像头拟合出横着或者竖着的直线（大体） *输入参数 ： 图片，0为横着，1为竖着 *返 回 值 ： 单条直线的ABC值， *编写时间 ： 2018.8.12 *作 者 ： 毛哥 ********************************************************************************************/
    vector <float> nihe_zhixian_dantiao(int flag)
    { 
    
    	vector <float> fangcheng_PARAM_1;
    	vector <float> fangcheng_PARAM_final;
    
    	double Param_A1[4] = {  0 };
    	double Param_B1[4] = {  0 };
    	double Param_C1[4] = {  0 };
    	int lvbo = 0;
    
    	Mat frame_2;
    	while (1)
    	{ 
    
    		frame_2 = imgOriginal_up;
    		Mat srcImg1, midImage, dstImage;//临时变量和目标图的定义
    
    		int width = frame_2.cols; //宽
    		int height = frame_2.rows;
    		Mat	image_copy_C3;
    
    	 if (flag == 0)//横着
    		{ 
    			Rect rect(0, frame_2.rows*0.3, frame_2.cols, frame_2.rows*(0.95 - 0.3));   //创建一个Rect框，属于cv中的类，四个参数代表x,y,width,height 
    
    			Mat	image_cut = Mat(frame_2, rect);
    			image_copy_C3 = image_cut.clone();   //clone函数创建新的图片 
    		}
    		else //竖着
    		{ 
    			Rect rect(frame_2.cols*0.075, frame_2.rows*0.2, frame_2.cols*(0.875 - 0.075), frame_2.rows*(0.83 - 0.2));   //创建一个Rect框，属于cv中的类，四个参数代表x,y,width,height 
    			Mat	image_cut = Mat(frame_2, rect);
    			image_copy_C3 = image_cut.clone();   //clone函数创建新的图片 
    
    		}
    		//从img中按照rect进行切割，此时修改image_cut时image中对应部分也会修改，因此需要copy 
    
    		midImage = Mat::zeros(image_copy_C3.size(), CV_8UC3);
    
    
    		//再次通过找轮廓，然后拟合出直线，通过斜率滤除剩下四条数线（或横线），然后通过长度滤除挡板的边缘直线，剩下白色过道的直线方程，一切问题得到解决。
    
    
    		cvtColor(image_copy_C3, srcImg1, CV_BGR2GRAY);//灰度化
    		//【3】srcImage取大于阈值119的那部分
    		srcImg1 = srcImg1 > G_threshold_up;
    
    		//namedWindow("二值化的图", 0);
    		//imshow("二值化的图", srcImg1);
    
    		// midImage=findMaxContouns(srcImg1);
    		/******* 检测直线优化 开始 ****************************************************************/
    
    
    
    		/*****************************用找轮廓代替边缘检测************************************************/
    		vector<vector<Point>>contours_1, RectContours; //轮廓
    		findContours(srcImg1, contours_1, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_NONE);//找轮廓
    
    		if (contours_1.size() == 0)
    		{ 
    			cout << "警告：没有在裁剪后的图片里找到轮廓（第二次找轮廓）" << endl;
    			continue;
    		}
    		if (contours_1.size() > 0)//如果没有找到轮廓退出
    		{ 
    			vector<float> length(contours_1.size());
    			for (int i = 0; i < contours_1.size(); i++)
    			{ //历遍所有的轮廓
    				length[i] = arcLength(contours_1[i], true);
    			}
    			if (contours_1.size() == 0)
    			{ 
    				cout << "警告：没有（第一次找轮廓）" << endl;
    				continue;
    			}
    			for (int i = 0; i < contours_1.size(); i++)
    			{ 
    				Scalar color = (255, 255, 255);//白色线画轮廓
    				drawContours(midImage, contours_1, i, color, 1, 8);//根据轮廓点集contours_poly和轮廓结构hierarchy画出轮廓
    			}
    		}
    
    
    		cvtColor(midImage, midImage, CV_BGR2GRAY);//灰度化
    		midImage = midImage>20;
    		vector<Vec4i> lines, lines_final;//定义一个矢量结构lines用于存放得到的线段矢量集合
    		HoughLinesP(midImage, lines, 1, CV_PI / 180, 95, 40, 60);
    		if (lines.size() == 0)
    		{ 
    			cout << "没有检测到直线" << endl;
    			continue;
    		}
    		/******* 检测直线优化 结束 ****************************************************************/
    		cvtColor(midImage, dstImage, COLOR_GRAY2BGR);//转化边缘检测后的图为灰度图
    		//画出挡板中轴线
    		//cout << "\n共检测到原始 直线" << lines.size() << "条" << endl;
    		//【4】依次计算出直线长度
    		float  zhixian_changdu;
    		float to_0_distance;
      	for (size_t i = 0; i < lines.size(); i++)
    	  	{ 
    
    			Vec4i l = lines[i];
    			to_0_distance = getDist_P2L_zhengfu(CvPoint(0, 0), Point(l[0], l[1]), Point(l[2], l[3]));
    			zhixian_changdu = getDistance_1(Point(l[0], l[1]), Point(l[2], l[3]));
    
    		// cout << "\n直线长度为" << zhixian_changdu << endl;
    		// cout << "到原点的距离" << to_0_distance << endl;
    			//画出原始直线
    			line(image_copy_C3, Point(l[0], l[1]), Point(l[2], l[3]), Scalar(0, 255, 0), 2, LINE_AA);
    			float line_k;
    			int a;
    			a = lines[i][2] - lines[i][0];
    			if (flag == 0)//横着
    			{ 
    				if (fabs((double)(lines[i][2] - lines[i][0])) > 0.0001)
    				{ 
    					line_k = (double)(lines[i][3] - lines[i][1]) / (double)(lines[i][2] - lines[i][0]); //求出直线的斜率
    				// cout << "\n直线的斜率为\n" << line_k << endl;
    					//斜率k以及b很接近的保留一条，两根直线应该是距离恒定的（一个比较稳定的范围）
    					//通过直线长度滤除，只剩下两条最长的,斜率要大于45度的直线
    					if (zhixian_changdu > 120 && fabs(line_k)<0.6&&fabs(to_0_distance)>20)
    					{ 
    						lines_final.push_back(lines[i]);
    
    					}
    
    				}
    
    			}
    			else //竖着
    			{ 
    				if (fabs((double)(lines[i][2] - lines[i][0])) != 0)
    				{ 
    					line_k = (double)(lines[i][3] - lines[i][1]) / (double)(lines[i][2] - lines[i][0]); //求出直线的斜率
    				// cout << "\n直线的斜率为\n" << line_k << endl;
    					//斜率k以及b很接近的保留一条，两根直线应该是距离恒定的（一个比较稳定的范围）
    					//通过直线长度滤除，只剩下两条最长的,斜率要大于45度的直线
    					if (zhixian_changdu >80 && fabs(to_0_distance)>30/* && (lines[i][1]<100 || lines[i][3]<100) */ && fabs(line_k)>1.7)
    					{ 
    						lines_final.push_back(lines[i]);
    
    					}
    					else if (fabs(line_k) > 30 && zhixian_changdu >60 && to_0_distance>110)
    					{ 
    						lines_final.push_back(lines[i]);
    
    					}
    				}
    				else
    				{ 
    					if (zhixian_changdu>60 && fabs(to_0_distance)>110 /*&& (lines[i][1] < 100 || lines[i][3] < 100)*/)
    					{ 
    						lines_final.push_back(lines[i]);
    					}
    				}
    
    			}
    		}
    		//namedWindow("直线未滤除前", 0);
    		//imshow("直线未滤除前", image_copy_C3);
    		//waitKey(1);
    		float A_Proportion, B_Proportion, C_Proportion;
    		//最终只能检测出两条直线
    		int zhixian_geshu = lines_final.size();
    		cout << "共有" << zhixian_geshu << "条直线进来了" << endl;
    		if (lines_final.size() >= 2)
    		{ 
    			//先求最终直线的方程的三个参数 A_top, B_bottom
    			fangcheng_PARAM_1 = get_lines_yibanshi_fangcheng(lines_final);
    			//将相同直线过滤为一条
    			if (lines_final.size() >= 3)
    			{ 
    				for (int j = 0; j <zhixian_geshu - 1; j++)
    				{ 
    					for (int k = j + 1; k <zhixian_geshu; k++)
    					{ 
    						A_Proportion = fangcheng_PARAM_1[j + 0] / fangcheng_PARAM_1[k + 0];
    						B_Proportion = fangcheng_PARAM_1[j + 1] / fangcheng_PARAM_1[k + 1];
    						C_Proportion = fangcheng_PARAM_1[j + 2] / fangcheng_PARAM_1[k + 2];
    
    						if ((A_Proportion > 0.75&&A_Proportion<1.3) && (B_Proportion>0.7 && B_Proportion<1.3) && (C_Proportion>0.7 && C_Proportion < 1.4))
    						{ 
    							cout << "第 " << j << "条直线" << "和" << k << "条直线相同" << endl;
    
    							fangcheng_PARAM_1[j + 0] = (fangcheng_PARAM_1[j + 0] + fangcheng_PARAM_1[k + 0]) / 2;
    							fangcheng_PARAM_1[j + 1] = (fangcheng_PARAM_1[j + 1] + fangcheng_PARAM_1[k + 0]) / 2;
    							fangcheng_PARAM_1[j + 2] = (fangcheng_PARAM_1[j + 2] + fangcheng_PARAM_1[k + 0]) / 2;
    
    						}
    					}
    				}
    			}
    
    			//【4】依次在图中绘制出每条线段
    			for (size_t i = 0; i < lines_final.size(); i++)
    			{ 
    				Vec4i l = lines_final[i];
    				line(dstImage, Point(l[0], l[1]), Point(l[2], l[3]), Scalar(0, 255, 0), 1, LINE_AA);
    			}
    
    
    	
    			// 滤波
    			Param_A1[3] = Param_A1[2];
    			Param_A1[2] = Param_A1[1];
    			Param_A1[1] = Param_A1[0];
    
    			Param_B1[3] = Param_B1[2];
    			Param_B1[2] = Param_B1[1];
    			Param_B1[1] = Param_B1[0];
    
    			Param_C1[3] = Param_C1[2];
    			Param_C1[2] = Param_C1[1];
    			Param_C1[1] = Param_C1[0];
    
    			Param_A1[0] = ((fabs(fangcheng_PARAM_1[0]) + fabs(fangcheng_PARAM_1[3])) / 2.0) * (fangcheng_PARAM_1[0] / fabs(fangcheng_PARAM_1[0]));
    			Param_B1[0] = ((fabs(fangcheng_PARAM_1[1]) + fabs(fangcheng_PARAM_1[4])) / 2.0) *(fangcheng_PARAM_1[1] / fabs(fangcheng_PARAM_1[1]));
    			Param_C1[0] = ((fabs(fangcheng_PARAM_1[2]) + fabs(fangcheng_PARAM_1[5])) / 2.0) *(fangcheng_PARAM_1[2] / fabs(fangcheng_PARAM_1[2]));
    
    
    			Param_A1[0] = 0.6* Param_A1[0] + 0.2* Param_A1[1] + 0.1* Param_A1[2] + 0.1* Param_A1[3];
    			Param_B1[0] = 0.6* Param_B1[0] + 0.2* Param_B1[1] + 0.1* Param_B1[2] + 0.1* Param_B1[3];
    			Param_C1[0] = 0.6* Param_C1[0] + 0.2* Param_C1[1] + 0.1* Param_C1[2] + 0.1* Param_C1[3];
    
    			float a1_bizhi;
    			if (Param_A1[0] != 0)
    			{ 
    				a1_bizhi = Param_A1[1] / Param_A1[0];
    			}
    			else
    			{ 
    				a1_bizhi = 1;
    			}
    
    			float a2_bizhi = Param_B1[1] / Param_B1[0];
    			float a3_bizhi = Param_C1[1] / Param_C1[0];
    
    			if ((a1_bizhi>0.9 || a1_bizhi<1.1) && (a2_bizhi>0.9 || a2_bizhi<1.1) && (a3_bizhi>0.9 || a3_bizhi<1.1))
    			{ 
    				lvbo++;
    
    			}
    			else /*if (lvbo>0)*/
    			{ 
    				lvbo=0;
    			}
    
    			if (lvbo>10)
    			{ 
    				fangcheng_PARAM_final.push_back(Param_A1[0]);
    				fangcheng_PARAM_final.push_back(Param_B1[0]);
    				fangcheng_PARAM_final.push_back(Param_C1[0]);
    				cout << "已拟合出直线方程" << endl;
    				draw_line_1(Param_A1[0], Param_B1[0], Param_C1[0], dstImage);
    				namedWindow("【检测直线效果图】", 0);//参数为零，则可以自由拖动
    				imshow("【检测直线效果图】", dstImage);
    				waitKey(1);
    
    				break;
    			}
    
    
    
    			/***** 7、输入A，B，C,画出线在dstImage*****/
    
    
    		}
    		else
    		{ 
    			//如果没有正确找到直线，就返回-1，函数外边再判断
    		// cout << "没有正确的找到最终的两条直线" << endl;
    			continue;
    
    		}
    	}
    
    	return fangcheng_PARAM_final;
    }
    
    
    /******************************************************************************************* *函数功能 ： 用于顶部摄像头找横竖两条直线交点 *输入参数 ： 图片 *返 回 值 ： 点向量,如果直线没有正确检测到，返回0，0点，方便后面判断 *编写时间 ： 2018.8.12 *作 者 ： 毛哥 ********************************************************************************************/
    Point2f nihe_jiaodian()
    { 
    	Point2f final_jiaodian;
    	vector <float>	fangcheng_PARAM_1, fangcheng_PARAM_2;
    	double Param_A1, Param_B1, Param_C1;//过道直线
    	double Param_A2, Param_B2, Param_C2;//挡板中轴线
    
    	fangcheng_PARAM_1 = nihe_zhixian_dantiao(0);
    
    	Param_A1 = fangcheng_PARAM_1[0];
    	Param_B1 = fangcheng_PARAM_1[1];
    	Param_C1 = fangcheng_PARAM_1[2];
    
    	fangcheng_PARAM_2 = nihe_zhixian_dantiao(1);
    	Param_A2 = fangcheng_PARAM_2[0];
    	Param_B2 = fangcheng_PARAM_2[1];
    	Param_C2 = fangcheng_PARAM_2[2];
    
    	final_jiaodian.y = (Param_A1*Param_C2 + Param_A2*Param_C1) / (Param_A2*Param_B1 - Param_A1*Param_B2);
    	final_jiaodian.x = (Param_C1 - Param_B1*final_jiaodian.y) / Param_A1;
    
    	//画出来
    	//circle(image, final_jiaodian, 2, Scalar(0, 0, 255), -1, 8);
    	return final_jiaodian;
    }
    
    
    
    /******************************************************************************************* *函数功能 ： 用于顶部摄像头放置横着的挡板,此时顶部摄像头已经找到 *输入参数 ：第一个参数是 0为横着，1为竖着，第一个参数是 1为第一块挡板，2为第二块挡板， *返 回 值 ： 单条直线的ABC值， *编写时间 ： 2018.8.12 *作 者 ： 毛哥 ********************************************************************************************/
    void Put_dangban(int hengshu, int yier)
    { 
    	double Param_A1, Param_B1, Param_C1;//过道直线
    	double Param_A2, Param_B2, Param_C2;//挡板中轴线
    	//vector <float> fangcheng_PARAM_1 = nihe_zhixian_dantiao(hengshu);
    	vector <float>	fangcheng_PARAM_1 = getVHlineParam(hengshu);
    
    	Param_A1 = fangcheng_PARAM_1[0];
    	Param_B1 = fangcheng_PARAM_1[1];
    	Param_C1 = fangcheng_PARAM_1[2];
    
    		if (yier == 1)
    		{ 
    			Send_to_K60(10, 0, 0);//将第一块挡板放在悬空位置（离地2cm）
    			Sleep(1200);
    
    		}
    		else
    		{ 
    			Send_to_K60(11, 0, 0);//将第二块挡板放在悬空位置（离地2cm）
    			Sleep(2000);
    		}
    
    
    
    
    
    	//实时找红色挡板
    	//printf("\n\n\t\t\t 实时找红色挡板开始\n");
    
    	int jiaodu_jishu = 0;
    	Mat frame_2;
    
    	while (1)
    	{ 
    
    		Mat srcImage0;
    
    
    		frame_2 = imgOriginal_up;
    
    		int width = frame_2.cols;
    		int height = frame_2.rows;
    
    		Mat image_cut;      //从img中按照rect进行切割，此时修改image_cut时image中对应部分也会修改，因此需要copy 
    		Mat image_copy_C3;   //clone函数创建新的图片 彩色
    
    		if (hengshu == 0)//横着
    		{ 
    			Rect rect(0, frame_2.rows*0.3, frame_2.cols, frame_2.rows*(0.95 - 0.3));   //创建一个Rect框，属于cv中的类，四个参数代表x,y,width,height 
    
    			Mat	image_cut = Mat(frame_2, rect);
    			image_copy_C3 = image_cut.clone();   //clone函数创建新的图片 
    		}
    		else //竖着
    		{ 
    			Rect rect(frame_2.cols*0.075, frame_2.rows*0.2, frame_2.cols*(0.875 - 0.075), frame_2.rows*(0.83 - 0.2));   //创建一个Rect框，属于cv中的类，四个参数代表x,y,width,height 
    			Mat	image_cut = Mat(frame_2, rect);
    			image_copy_C3 = image_cut.clone();   //clone函数创建新的图片 
    		}
    
    		int x, y;
    		double B = 0.0, G = 0.0, R = 0.0, H = 0.0, S = 0.0, V = 0.0;
    		int width1 = image_copy_C3.cols * 3;
    		int height1 = image_copy_C3.rows;
    		for (x = 0; x < height1; x++)
    		{ 
    			uchar* data = image_copy_C3.ptr<uchar>(x);//获取第i行的首地址
    			for (y = 0; y < width1; y += 3)
    			{ 
    				B = data[y];
    				G = data[y + 1];
    				R = data[y + 2];
    				RGB2HSV(R, G, B, H, S, V);
    				//红色范围，范围参考的网上。可以自己调
    			// if ((H >= 286 && H <= 360 || H >= 0 && H <= 20) && (S >= 0 && S <= 360) && (V>0 && V < 360))
    				if ((H >= 270 && H <= 360 || H >= 0 && H <= 20) && (S >= 0 && S <= 360) && (V>0 && V < 360))
    					data[y] = data[y + 1] = data[y + 2] = 255;
    				else data[y] = data[y + 1] = data[y + 2] = 0;
    			}
    		}
    		Mat vec_rgb;
    		cvtColor(image_copy_C3, vec_rgb, CV_BGR2GRAY);//灰度化
    		//【3】srcImage取大于阈值119的那部分
    		vec_rgb = vec_rgb > 120;
    
    
    		//namedWindow("hsv空间图像", 0);
    		//imshow("hsv空间图像", vec_rgb);
    		//waitKey(1);
    
    		//Mat element = getStructuringElement(MORPH_ELLIPSE, Size(2 * 1 + 1, 2 * 1 + 1), Point(1, 1));
    		Mat element1 = getStructuringElement(MORPH_ELLIPSE, Size(2 * 3 + 1, 2 * 3 + 1), Point(3, 3));
    		// Mat element1 = getStructuringElement(MORPH_RECT, Size(45, 45));
    		dilate(vec_rgb, vec_rgb, element1);//膨胀
    		/*namedWindow("膨胀", 0); imshow("膨胀", vec_rgb); waitKey(1);*/
    
    		erode(vec_rgb, vec_rgb, element1);//腐蚀
    		/*namedWindow("腐蚀", 0); imshow("腐蚀", vec_rgb); waitKey(1);*/
    
    		vector<vector<Point>>contours, max_contours; //轮廓
    		vector<Vec4i> hierarchy;//分层
    		Mat drawing_text = Mat::zeros(vec_rgb.size(), CV_8UC3);
    		findContours(vec_rgb, contours, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_NONE);//找轮廓
    		if (contours.size() == 0)
    		{ 
    			cout << "警告：没有红色挡板（第一次找轮廓）" << endl;
    
    			continue;
    		}
    		// cout << "第一次找轮廓结束，共找到轮廓：" << contours.size() << " 条" << endl;
    
    		vector<vector<Point>> hull(contours.size());//用于存放凸包
    		vector<float> length(contours.size());
    		vector<float> Area_contours(contours.size()), Area_hull(contours.size()), Rectangularity(contours.size()), circularity(contours.size());
    
    		vector< Point2f>  lunkuo_zhongxin_first;
    		lunkuo_zhongxin_first = find_lunkuo_zhongxin(contours);
    
    
    		int Xmin = (int)(vec_rgb.cols * 0);
    		int Xmax = (int)(vec_rgb.cols);
    		int Ymin = (int)(vec_rgb.rows * 0);
    		int Ymax = (int)(vec_rgb.rows);
    
    		for (int i = 0; i < contours.size(); i++)
    		{ //历遍所有的轮廓
    
    			length[i] = arcLength(contours[i], true);
    
    			//cout << "轮廓长度为" << length[i] << endl;
    
    			if (length[i] >5 && lunkuo_zhongxin_first[i].x>Xmin&&lunkuo_zhongxin_first[i].x<Xmax&&lunkuo_zhongxin_first[i].y>Ymin&&lunkuo_zhongxin_first[i].y<Ymax)
    			{ //通过长度匹配滤除小轮廓
    				convexHull(Mat(contours[i]), hull[i], false);//把凸包找出来
    				max_contours.push_back(hull[i]);//把提取出来的方框导入到新的轮廓组
    			}
    		}
    		if (max_contours.size() == 0)
    		{ 
    			cout << "警告：y有红色物体，但是可能没有红色挡板，或者红色挡板被遮挡严重" << endl;
    
    			continue;
    		}
    
    		//将线连接起来
    		vector<Point2f> zhongxin_zuobiao;
    		zhongxin_zuobiao = find_lunkuo_zhongxin(max_contours);
    		if (zhongxin_zuobiao.size() >= 2)
    		{ 
    			for (int i = 0; i < zhongxin_zuobiao.size() - 1; i++)
    			{ 
    				for (int j = i + 1; j < zhongxin_zuobiao.size(); j++)
    				{ 
    					float dis_juxin = getDistance_1(zhongxin_zuobiao[i], zhongxin_zuobiao[j]);
    					if (dis_juxin <65)
    					{ 
    						line(vec_rgb, zhongxin_zuobiao[i], zhongxin_zuobiao[j], Scalar(255), 4, LINE_AA);
    					}
    
    				}
    			}
    
    		}
    		//namedWindow("连接直线后", 0);
    		//imshow("连接直线后", vec_rgb);
    		//waitKey(1);
    
    
    		Mat vec_rgb1;
    
    		dilate(vec_rgb, vec_rgb1, element1);//膨胀
    		namedWindow("膨胀1", 0);
    		imshow("膨胀1", vec_rgb1);
    		waitKey(1);
    
    		erode(vec_rgb1, vec_rgb1, element1);//腐蚀
    		//namedWindow("腐蚀1", 0);
    		//imshow("腐蚀1", vec_rgb1);
    		//waitKey(1);
    
    		//第二次找轮廓
    		vector<vector<Point>>contours_1, RectContours; //轮廓
    		Mat drawing_1 = Mat(vec_rgb.size(), CV_8UC3, Scalar(0, 0, 0));
    		Mat  	dstImage = Mat(vec_rgb.size(), CV_8UC3, Scalar(0, 0, 0));   //clone函数创建新的图片 
    		findContours(vec_rgb, contours_1, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_NONE);//找轮廓
    
    		if (contours_1.size() == 0)
    		{ 
    			cout << "警告：没有在裁剪后的图片里找到轮廓（第二次找轮廓）" << endl;
    			continue;
    		}
    
    		//cout << "第二次找轮廓结束，共找到轮廓：" << contours_1.size() << " 条" << endl;
    		//cout << "第二次找轮廓结束" << endl;
    
    		vector< Point2f> lunkuo_zhongxin1, lunkuo_zhongxin_temp_first;
    
    		lunkuo_zhongxin_temp_first = find_lunkuo_zhongxin(contours_1);
    
    
    		if (contours_1.size() > 0)//如果没有找到轮廓退出
    		{ 
    			vector<vector<Point>> hull(contours_1.size());//用于存放凸包
    			vector<float> length(contours_1.size());
    
    			for (int i = 0; i < contours_1.size(); i++)
    			{ //历遍所有的轮廓
    
    				length[i] = arcLength(contours_1[i], true);
    
    				if (length[i] >170 && lunkuo_zhongxin_temp_first[i].x>120 && lunkuo_zhongxin_temp_first[i].x<190 && lunkuo_zhongxin_temp_first[i].y>20 && lunkuo_zhongxin_temp_first[i].y<130)
    				{ //通过长度匹配滤除小轮廓
    					convexHull(Mat(contours_1[i]), hull[i], false);//把凸包找出来
    
    					RectContours.push_back(hull[i]);//把提取出来的方框导入到新的轮廓组
    
    				}
    
    			}
    			// cout << "已找到裁剪后的新凸包" << endl;
    
    			if (RectContours.size() == 0)
    			{ 
    
    				cout << "警告：没有红色挡板（第一次找轮廓）" << endl;
    				continue;
    			}
    
    
    
    			lunkuo_zhongxin1 = find_lunkuo_zhongxin(RectContours);
    
    
    
    			for (int i = 0; i < RectContours.size(); i++)
    			{ 
    				Scalar color = (255, 255, 255);//白色线画轮廓
    				drawContours(drawing_1, RectContours, i, color, 1, 8, hierarchy, 0, Point());//根据轮廓点集contours_poly和轮廓结构hierarchy画出轮廓
    				drawContours(dstImage, RectContours, i, color, 1, 8, hierarchy, 0, Point());//根据轮廓点集contours_poly和轮廓结构hierarchy画出轮廓
    
    
    				//画圆形
    			}
    
    			cvtColor(drawing_1, drawing_1, CV_BGR2GRAY);//灰度化
    			//【3】srcImage取大于阈值119的那部分
    			drawing_1 = drawing_1 > 20;
    		}
    
    
    
    
    		/******* 检测直线优化 开始 ****************************************************************/
    
    
    		Mat vec_rgb2;
    		vector<Vec4i> lines1, lines_final;//定义一个矢量结构lines用于存放得到的线段矢量集合
    
    		// Canny(drawing_1, vec_rgb2, cannyThreshold, cannyThreshold * factor);
    		HoughLinesP(drawing_1, lines1, 1, CV_PI / 180, 35, 30, 30);
    
    		if (lines1.size() == 0)
    		{ 
    			cout << "红色挡板直线数量为零" << endl;
    			continue;
    		}
    
    		//【4】依次计算出直线长度
    		float  zhixian_changdu;
    		for (size_t i = 0; i < lines1.size(); i++)
    		{ 
    			Vec4i l = lines1[i];
    			zhixian_changdu = getDistance_1(Point(l[0], l[1]), Point(l[2], l[3]));
    
    			//cout << "\n红色挡板直线长度为" << zhixian_changdu << endl;
    
    			//画出原始直线
    			line(dstImage, Point(l[0], l[1]), Point(l[2], l[3]), Scalar(0, 255, 0), 1, LINE_AA);
    			float line_k = 0;
    			int a;
    			a = lines1[i][2] - lines1[i][0];
    
    			if (hengshu == 0)//横着
    			{ 
    				if (fabs((double)(lines1[i][2] - lines1[i][0])) > 0.001)
    				{ 
    					line_k = (double)(lines1[i][3] - lines1[i][1]) / (double)(lines1[i][2] - lines1[i][0]); //求出直线的斜率
    					//cout << "\n红色挡板直线的斜率为\n" << line_k << endl;
    					//斜率k以及b很接近的保留一条，两根直线应该是距离恒定的（一个比较稳定的范围）
    					//通过直线长度滤除，只剩下两条最长的,斜率要大于45度的直线
    					if (zhixian_changdu > 40 /*&& fabs(line_k)<1*/)
    					{ 
    						lines_final.push_back(lines1[i]);
    
    					}
    
    				}
    
    			}
    			else //竖着
    			{ 
    				if (fabs((double)(lines1[i][2] - lines1[i][0])) > 0.0001)
    				{ 
    					line_k = (double)(lines1[i][3] - lines1[i][1]) / (double)(lines1[i][2] - lines1[i][0]); //求出直线的斜率
    					//cout << "\n红色挡板直线的斜率为\n" << line_k << endl;
    					//斜率k以及b很接近的保留一条，两根直线应该是距离恒定的（一个比较稳定的范围）
    					//通过直线长度滤除，只剩下两条最长的,斜率要大于45度的直线
    					if (zhixian_changdu > 40 && fabs(line_k)>0.7)
    					{ 
    						lines_final.push_back(lines1[i]);
    
    					}
    
    				}
    				else
    				{ 
    					if (zhixian_changdu>40)
    					{ 
    						lines_final.push_back(lines1[i]);
    					}
    				}
    			}
    		}
    
    		//namedWindow("挡板直线", 0);
    		//imshow("挡板直线", drawing_1);
    		//waitKey(2);
    
    
    		vector <float> fangcheng_PARAM_1;
    
    
    		//最终只能检测出两条直线
    		int zhixian_geshu = lines_final.size();
    		// cout << "共有" << zhixian_geshu << "条直线进来了" << endl;
    		float line_k[4] = {  0 };
    		float line_b[4] = {  0 };
    		if (lines_final.size() == 0)
    		{ 
    			cout << "红色挡板最终直线数量为零" << endl;
    			continue;
    		}
    
    		if (lines_final.size() >= 1)
    		{ 
    			int a, b = 0;
    			for (size_t i = 0; i < lines_final.size(); i++)
    			{ 
    				float line_k_temp;
    
    				a = lines_final[i][2] - lines_final[i][0];
    				// cout << "参数为： " << a << endl;
    				if (fabs((double)(lines_final[i][2] - lines_final[i][0])) > 0.001)
    				{ 
    					b++;
    					line_k_temp = (double)(lines_final[i][3] - lines_final[i][1]) / (double)(lines_final[i][2] - lines_final[i][0]); //求出直线的斜率
    					// cout << "\n最终直线的斜率为\n" << line_k_temp << endl;
    					//斜率k以及b很接近的保留一条，两根直线应该是距离恒定的（一个比较稳定的范围）
    					//通过直线长度滤除，只剩下两条最长的,斜率要大于45度的直线
    
    					line_k[0] = line_k_temp + line_k[0];
    
    				}
    				else
    				{ 
    					line_k[0] = 1000;
    					//曹，直线是个直的
    					// line_k = 8000;
    
    
    				}
    
    
    			}
    			line_k[3] = line_k[2];
    			line_k[2] = line_k[1];
    			line_k[1] = line_k[0];
    
    			//line_b[3] = line_b[2];
    			//line_b[2] = line_b[1];
    			//line_b[1] = line_b[0];
    
    			line_k[0] = line_k[0] / b;
    			if (fabs(line_k[1] / line_k[0]) >10)//去抖动
    			{ 
    				line_k[0] = line_k[1];
    			}
    
    			line_k[0] = 0.6* line_k[0] + 0.2* line_k[1] + 0.1* line_k[2] + 0.1* line_k[3];
    
    			//line_b[0] = lunkuo_zhongxin1[0].y - lunkuo_zhongxin1[0].x*line_k[0];
    			//line_b[0] = 0.35* line_b[0] + 0.3* line_b[1] + 0.25* line_b[2] + 0.1* line_b[3];
    			//
    			if (fabs(line_k[0])<50)
    			{ 
    				Param_A2 = -line_k[0];
    				Param_B2 = 1;
    				Param_C2 = line_k[0] * lunkuo_zhongxin1[0].x - lunkuo_zhongxin1[0].y;
    			}
    			else
    			{ 
    				Param_A2 = -line_k[0];
    				Param_B2 = 0.0001;
    				Param_C2 = line_k[0] * lunkuo_zhongxin1[0].x - lunkuo_zhongxin1[0].y;
    			}
    
    
    
    			//Pt2.x = lunkuo_zhongxin1[0].x + 50;
    			//Pt2.y = 50 * line_k[0] + lunkuo_zhongxin1[0].y;
    			// line(drawing_1, lunkuo_zhongxin1[0], Pt2, Scalar(0, 0, 255), 4, LINE_AA);
    			draw_line_1(Param_A2, Param_B2, Param_C2, dstImage);
    			draw_line_1(Param_A1, Param_B1, Param_C1, dstImage);
    
    		}
    
    
    		float theta, shuiping_diatance;
    
    
    		//fangcheng_PARAM_2 = get_lines_yibanshi_fangcheng_2((Point2f)lunkuo_zhongxin1[0], (Point2f)Pt2);
    
    		//Param_A2 = fangcheng_PARAM_2[0];
    		//Param_B2 = fangcheng_PARAM_2[1];
    		//Param_C2 = fangcheng_PARAM_2[2];
    
    
    		/***** 7、输入A，B，C,画出线在dstImage*****/
    
    		//最终求夹角（旋转误差）和平移误差
    		//两直线夹角，挡板相对于白色过道的夹角，因此白色过道直线斜率为第一个参数
    		theta = get_lines_yibanshi_arctan(Param_A1, Param_B1, Param_C1, Param_A2, Param_B2, Param_C2);
    
    		//点到直线距离
    		//P为线外一点，AB为线段两个端点
    		shuiping_diatance = getDist_P2L_zhengfu_2(lunkuo_zhongxin1[0], Param_A1, Param_B1, Param_C1,1);
    
    
    		cout << "\n最终结果\n挡板中轴线和白色过道中轴线夹角为： " << theta << " 度" << endl;
    		cout << "挡板中点与白色过道中轴线误差为： " << shuiping_diatance << endl;
    
    		//namedWindow("直线未滤除前", 0);
    		//imshow("直线未滤除前", image_copy_C3);
    		//waitKey(1);
    
    		namedWindow("【挡板夹角和位移示意图】", 0);//参数为零，则可以自由拖动
    		imshow("【挡板夹角和位移示意图】", dstImage);
    		waitKey(1);
    		float error1 = 0, error2 = 0;
    		error1 = theta*1.3;
    		error2 = shuiping_diatance*1.4;//目标行数，291
    		error1 = error1 > 127 ? 127 : error1;
    		error1 = error1 < -127 ? -127 : error1;
    		error2 = error2 > 127 ? 127 : error2;
    		error2 = error2 < -127 ? -127 : error2;
    
    		if (fabs(error1) < 1 && fabs(error2) <1.5)
    		{ 
    			Send_to_K60(12 , 0 , 0);
    			jiaodu_jishu++;
    			if (jiaodu_jishu>6)
    			{ 
    				Send_to_K60(13, 0, 0);//将挡板放下并归右边位置
    				Sleep(1000);
    				cout << "\n放置挡板成功" << endl;
    				break;
    			}
    		}
    		else
    		{ 
    			Send_to_K60(12, (int)error1, (int)error2);
    			if (jiaodu_jishu>0)
    			jiaodu_jishu--;
    		}
    	
    	}
    
    }
    
    
    /******************************************************************************************* *函数功能 ： 用于顶部摄像头放置横着的挡板,此时顶部摄像头已经找到 *输入参数 ：第一个参数是 0为横着，1为竖着，第一个参数是 1为第一块挡板，2为第二块挡板， *返 回 值 ： 单条直线的ABC值， *编写时间 ： 2018.8.12 *作 者 ： 毛哥 ********************************************************************************************/
    void Put_dangban_heng(int hengshu, int yier)
    { 
    	double Param_A1, Param_B1, Param_C1;//过道直线
    	double Param_A2, Param_B2, Param_C2;//挡板中轴线
    	//vector <float> fangcheng_PARAM_1 = nihe_zhixian_dantiao(hengshu);
    	vector <float>	fangcheng_PARAM_1 = getVHlineParam(hengshu);
    
    	Param_A1 = fangcheng_PARAM_1[0];
    	Param_B1 = fangcheng_PARAM_1[1];
    	Param_C1 = fangcheng_PARAM_1[2];
    
    
    
    	Send_to_K60(14, 0, 0);//将横挡板第一块挡板放在悬空位置（离地2cm）
    	Sleep(2000);
    
    
    	//实时找红色挡板
    	//printf("\n\n\t\t\t 实时找红色挡板开始\n");
    
    	int jiaodu_jishu = 0;
    	Mat frame_2;
    	while (1)
    	{ 
    
    		Mat srcImage0;
    
    
    		frame_2 = imgOriginal_up;
    		int width = frame_2.cols;
    		int height = frame_2.rows;
    
    	  Mat image_copy_C3;   //clone函数创建新的图片 彩色
    
    		if (hengshu == 0)//横着
    		{ 
    			Rect rect(0, frame_2.rows*0.3, frame_2.cols, frame_2.rows*(0.95 - 0.3));   //创建一个Rect框，属于cv中的类，四个参数代表x,y,width,height 
    
    			Mat	image_cut = Mat(frame_2, rect);
    			image_copy_C3 = image_cut.clone();   //clone函数创建新的图片 
    		}
    		else //竖着
    		{ 
    			Rect rect(frame_2.cols*0.075, frame_2.rows*0.2, frame_2.cols*(0.875 - 0.075), frame_2.rows*(0.83 - 0.2));   //创建一个Rect框，属于cv中的类，四个参数代表x,y,width,height 
    			Mat	image_cut = Mat(frame_2, rect);
    			image_copy_C3 = image_cut.clone();   //clone函数创建新的图片 
    
    		}
    
          	int x=0, y=0;
    		double B = 0.0, G = 0.0, R = 0.0, H = 0.0, S = 0.0, V = 0.0;
    		int width1 = image_copy_C3.cols * 3;
    		int height1 = image_copy_C3.rows;
    		for (x = 0; x < height1; x++)
    		{ 
    			uchar* data = image_copy_C3.ptr<uchar>(x);//获取第i行的首地址
    			for (y = 0; y < width1; y += 3)
    			{ 
    				B = data[y];
    				G = data[y + 1];
    				R = data[y + 2];
    				RGB2HSV(R, G, B, H, S, V);
    				//红色范围，范围参考的网上。可以自己调
    				if ((H >= 286 && H <= 360 || H >= 0 && H <= 20) && (S >= 0 && S <= 360) && (V>0 && V < 360))
    					data[y] = data[y + 1] = data[y + 2] = 255;
    				else data[y] = data[y + 1] = data[y + 2] = 0;
    			}
    		}
    		Mat vec_rgb;
    		cvtColor(image_copy_C3, vec_rgb, CV_BGR2GRAY);//灰度化
    		//【3】srcImage取大于阈值119的那部分
    		vec_rgb = vec_rgb > 120;
    
    		Mat element1 = getStructuringElement(MORPH_ELLIPSE, Size(2 * 3 + 1, 2 * 3 + 1), Point(3, 3));
    		// Mat element1 = getStructuringElement(MORPH_RECT, Size(45, 45));
    		dilate(vec_rgb, vec_rgb, element1);//膨胀
    	
    		/*namedWindow("膨胀", 0); imshow("膨胀", vec_rgb); waitKey(1);*/
    
    		erode(vec_rgb, vec_rgb, element1);//腐蚀
    		/*namedWindow("腐蚀", 0); imshow("腐蚀", vec_rgb); waitKey(1);*/
    
    		vector<vector<Point>>contours, max_contours; //轮廓
    		vector<Vec4i> hierarchy;//分层
    		Mat drawing_text = Mat::zeros(vec_rgb.size(), CV_8UC3);
    		findContours(vec_rgb, contours, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_NONE);//找轮廓
    		if (contours.size() == 0)
    		{ 
    			cout << "警告：没有红色挡板（第一次找轮廓）" << endl;
    
    			continue;
    		}
    		// cout << "第一次找轮廓结束，共找到轮廓：" << contours.size() << " 条" << endl;
    
    		vector<vector<Point>> hull(contours.size());//用于存放凸包
    		vector<float> length(contours.size());
    		vector<float> Area_contours(contours.size()), Area_hull(contours.size()), Rectangularity(contours.size()), circularity(contours.size());
    
    		vector< Point2f>  lunkuo_zhongxin_first;
    		lunkuo_zhongxin_first = find_lunkuo_zhongxin(contours);
    
    
    		int Xmin = (int)(vec_rgb.cols * 0);
    		int Xmax = (int)(vec_rgb.cols);
    		int Ymin = (int)(vec_rgb.rows * 0);
    		int Ymax = (int)(vec_rgb.rows);
    
    		for (int i = 0; i < contours.size(); i++)
    		{ //历遍所有的轮廓
    
    			length[i] = arcLength(contours[i], true);
    
    			//cout << "轮廓长度为" << length[i] << endl;
    
    			if (length[i] >5 && lunkuo_zhongxin_first[i].x>Xmin&&lunkuo_zhongxin_first[i].x<Xmax&&lunkuo_zhongxin_first[i].y>Ymin&&lunkuo_zhongxin_first[i].y<Ymax)
    			{ //通过长度匹配滤除小轮廓
    				convexHull(Mat(contours[i]), hull[i], false);//把凸包找出来
    				max_contours.push_back(hull[i]);//把提取出来的方框导入到新的轮廓组
    			}
    		}
    		if (max_contours.size() == 0)
    		{ 
    			cout << "警告：y有红色物体，但是可能没有红色挡板，或者红色挡板被遮挡严重" << endl;
    
    			continue;
    		}
    
    		//将线连接起来
    		vector<Point2f> zhongxin_zuobiao;
    		zhongxin_zuobiao = find_lunkuo_zhongxin(max_contours);
    		if (zhongxin_zuobiao.size() >= 2)
    		{ 
    			for (int i = 0; i < zhongxin_zuobiao.size() - 1; i++)
    			{ 
    				for (int j = i + 1; j < zhongxin_zuobiao.size(); j++)
    				{ 
    					float dis_juxin = getDistance_1(zhongxin_zuobiao[i], zhongxin_zuobiao[j]);
    					if (dis_juxin <65)
    					{ 
    						line(vec_rgb, zhongxin_zuobiao[i], zhongxin_zuobiao[j], Scalar(255), 4, LINE_AA);
    					}
    
    				}
    			}
    
    		}
    		//namedWindow("连接直线后", 0);
    		//imshow("连接直线后", vec_rgb);
    		//waitKey(1);
    
    
    		Mat vec_rgb1;
    
    		dilate(vec_rgb, vec_rgb1, element1);//膨胀
    		namedWindow("膨胀1", 0);
    		imshow("膨胀1", vec_rgb1);
    		waitKey(1);
    
    		erode(vec_rgb1, vec_rgb1, element1);//腐蚀
    		//namedWindow("腐蚀1", 0);
    		//imshow("腐蚀1", vec_rgb1);
    		//waitKey(1);
    
    		//第二次找轮廓
    		vector<vector<Point>>contours_1, RectContours; //轮廓
    		Mat drawing_1 = Mat(vec_rgb.size(), CV_8UC3, Scalar(0, 0, 0));
    		Mat  	dstImage = Mat(vec_rgb.size(), CV_8UC3, Scalar(0, 0, 0));   //clone函数创建新的图片 
    		findContours(vec_rgb, contours_1, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_NONE);//找轮廓
    
    		if (contours_1.size() == 0)
    		{ 
    			cout << "警告：没有在裁剪后的图片里找到轮廓（第二次找轮廓）" << endl;
    			continue;
    		}
    
    		//cout << "第二次找轮廓结束，共找到轮廓：" << contours_1.size() << " 条" << endl;
    		//cout << "第二次找轮廓结束" << endl;
    
    		vector< Point2f> lunkuo_zhongxin1, lunkuo_zhongxin_temp_first;
    
    		lunkuo_zhongxin_temp_first = find_lunkuo_zhongxin(contours_1);
    
    
    
    		if (contours_1.size() > 0)//如果没有找到轮廓退出
    		{ 
    			vector<vector<Point>> hull(contours_1.size());//用于存放凸包
    			vector<float> length(contours_1.size());
    
    			for (int i = 0; i < contours_1.size(); i++)
    			{ //历遍所有的轮廓
    
    				length[i] = arcLength(contours_1[i], true);
    
    				if (length[i] >170 && lunkuo_zhongxin_temp_first[i].x>0 && lunkuo_zhongxin_temp_first[i].x<140)
    				{ //通过长度匹配滤除小轮廓
    					convexHull(Mat(contours_1[i]), hull[i], false);//把凸包找出来
    
    					RectContours.push_back(hull[i]);//把提取出来的方框导入到新的轮廓组
    
    				}
    
    			}
    			// cout << "已找到裁剪后的新凸包" << endl;
    
    			if (RectContours.size() == 0)
    			{ 
    
    				cout << "警告：没有红色挡板（第一次找轮廓）" << endl;
    				continue;
    			}
    
    
    			lunkuo_zhongxin1 = find_lunkuo_zhongxin(RectContours);
    
    			if (lunkuo_zhongxin1.size() != 1)
    			{ 
    
    				cout << "警告：有两个红色挡板" << endl;
    				continue;
    			}
    
    
    			for (int i = 0; i < RectContours.size(); i++)
    			{ 
    				Scalar color = (255, 255, 255);//白色线画轮廓
    				drawContours(drawing_1, RectContours, i, color, 1, 8, hierarchy, 0, Point());//根据轮廓点集contours_poly和轮廓结构hierarchy画出轮廓
    				drawContours(dstImage, RectContours, i, color, 1, 8, hierarchy, 0, Point());//根据轮廓点集contours_poly和轮廓结构hierarchy画出轮廓
    
    
    				//画圆形
    			}
    
    			cvtColor(drawing_1, drawing_1, CV_BGR2GRAY);//灰度化
    			//【3】srcImage取大于阈值119的那部分
    			drawing_1 = drawing_1 > 20;
    		}
    
    
    
    
    		/******* 检测直线优化 开始 ****************************************************************/
    
    
    		Mat vec_rgb2;
    		vector<Vec4i> lines1, lines_final;//定义一个矢量结构lines用于存放得到的线段矢量集合
    
    		// Canny(drawing_1, vec_rgb2, cannyThreshold, cannyThreshold * factor);
    		HoughLinesP(drawing_1, lines1, 1, CV_PI / 180, 35, 30, 30);
    
    		if (lines1.size() == 0)
    		{ 
    			cout << "直线数量为零" << endl;
    			continue;
    		}
    
    		//【4】依次计算出直线长度
    		float  zhixian_changdu;
    		for (size_t i = 0; i < lines1.size(); i++)
    		{ 
    			Vec4i l = lines1[i];
    			zhixian_changdu = getDistance_1(Point(l[0], l[1]), Point(l[2], l[3]));
    
    			//cout << "\n直线长度为" << zhixian_changdu << endl;
    
    			//画出原始直线
    			line(dstImage, Point(l[0], l[1]), Point(l[2], l[3]), Scalar(0, 255, 0), 1, LINE_AA);
    			float line_k = 0;
    			int a;
    			a = lines1[i][2] - lines1[i][0];
    			if (hengshu == 0)//横着
    			{ 
    				if (fabs((double)(lines1[i][2] - lines1[i][0])) > 0.001)
    				{ 
    					line_k = (double)(lines1[i][3] - lines1[i][1]) / (double)(lines1[i][2] - lines1[i][0]); //求出直线的斜率
    					//cout << "\n直线的斜率为\n" << line_k << endl;
    					//斜率k以及b很接近的保留一条，两根直线应该是距离恒定的（一个比较稳定的范围）
    					//通过直线长度滤除，只剩下两条最长的,斜率要大于45度的直线
    					if (zhixian_changdu > 40 /*&& fabs(line_k)<1*/)
    					{ 
    						lines_final.push_back(lines1[i]);
    					}
    				}
    			}
    			else //竖着
    			{ 
    				if (fabs((double)(lines1[i][2] - lines1[i][0])) > 0.001)
    				{ 
    					line_k = (double)(lines1[i][3] - lines1[i][1]) / (double)(lines1[i][2] - lines1[i][0]); //求出直线的斜率
    					cout << "\n直线的斜率为\n" << line_k << endl;
    					//斜率k以及b很接近的保留一条，两根直线应该是距离恒定的（一个比较稳定的范围）
    					//通过直线长度滤除，只剩下两条最长的,斜率要大于45度的直线
    					if (zhixian_changdu > 40 && fabs(line_k)>0.7)
    					{ 
    						lines_final.push_back(lines1[i]);
    					}
    				}
    				else
    				{ 
    					if (zhixian_changdu>40)
    					{ 
    						lines_final.push_back(lines1[i]);
    					}
    				}
    			}
    		}
    		vector <float> fangcheng_PARAM_1;
    		//最终只能检测出两条直线
    		int zhixian_geshu = lines_final.size();
    		float line_k[4] = {  0 };
    		float line_b[4] = {  0 };
    		if (lines_final.size() == 0)
    		{ 
    			cout << "最终直线数量为零" << endl;
    			continue;
    		}
    
    		if (lines_final.size() >= 1)
    		{ 
    			int a, b = 0;
    			for (size_t i = 0; i < lines_final.size(); i++)
    			{ 
    				float line_k_temp;
    
    				a = lines_final[i][2] - lines_final[i][0];
    			
    				if (fabs((double)(lines_final[i][2] - lines_final[i][0])) > 0.001)
    				{ 
    					b++;
    					line_k_temp = (double)(lines_final[i][3] - lines_final[i][1]) / (double)(lines_final[i][2] - lines_final[i][0]); //求出直线的斜率
    					// cout << "\n最终直线的斜率为\n" << line_k_temp << endl;
    					//斜率k以及b很接近的保留一条，两根直线应该是距离恒定的（一个比较稳定的范围）
    					//通过直线长度滤除，只剩下两条最长的,斜率要大于45度的直线
    					line_k[0] = line_k_temp + line_k[0];
    
    				}
    				else
    				{ 
    					line_k[0] = 1000;
    					//曹，直线是个直的
    					// line_k = 8000;
    				}
    			}
    			line_k[3] = line_k[2];
    			line_k[2] = line_k[1];
    			line_k[1] = line_k[0];
    
    			line_k[0] = line_k[0] / (float)b;
    			if (fabs(line_k[1] / line_k[0]) >8)//去抖动
    			{ 
    				line_k[0] = line_k[1];
    			}
    
    			line_k[0] = 0.6* line_k[0] + 0.2* line_k[1] + 0.1* line_k[2] + 0.1* line_k[3];
    			Param_A2 = -line_k[0];
    			Param_B2 = 1;
    			Param_C2 = line_k[0] * lunkuo_zhongxin1[0].x - lunkuo_zhongxin1[0].y;	
    			draw_line_1(Param_A2, Param_B2, Param_C2, dstImage);
    			draw_line_1(Param_A1, Param_B1, Param_C1, dstImage);
    
    		}
    
    
    		float theta=0.0, shuiping_diatance=0.0;
    
    		/***** 7、输入A，B，C,画出线在dstImage******/
    		//最终求夹角（旋转误差）和平移误差
    		//两直线夹角，挡板相对于白色过道的夹角，因此白色过道直线斜率为第一个参数
    		theta = get_lines_yibanshi_arctan(Param_A1, Param_B1, Param_C1, Param_A2, Param_B2, Param_C2);
    
    		//点到直线距离
    		//P为线外一点，AB为线段两个端点
    		shuiping_diatance = getDist_P2L_zhengfu_2(lunkuo_zhongxin1[0], Param_A1, Param_B1, Param_C1,0);
    
    
    		cout << "\n最终结果\n挡板中轴线和白色过道中轴线夹角为： " << theta << " 度" << endl;
    		cout << "挡板中点与白色过道中轴线误差为： " << -shuiping_diatance << endl;
    
    		namedWindow("【挡板夹角和位移示意图】", 0);//参数为零，则可以自由拖动
    		imshow("【挡板夹角和位移示意图】", dstImage);
    		waitKey(1);
    		float error1, error2;
    		error1 = theta;
    		error2 =-shuiping_diatance*1.5;//目标行数，291
    	
    		error1 = error1 > 127 ? 127 : error1;
    		error1 = error1 < -127 ? -127 : error1;
    		error2 = error2 > 127 ? 127 : error2;
    		error2 = error2 < -127 ? -127 : error2;
    
    
    
    		if (fabs(error1) < 1.1 && fabs(error2) <1.5)
    		{ 
    			jiaodu_jishu++;
    			if (jiaodu_jishu>5)
    			{ 
    				Send_to_K60(13, 0, 0);//将挡板放下并归右边位置
    				Sleep(2000);
    				cout << "\n放置第一块挡板成功" << endl;
    				break;
    			}
    
    		}
    		else if (jiaodu_jishu>0)
    		{ 
    			jiaodu_jishu--;
    		}
    		
    		Send_to_K60(12, (int)error1, (int)error2);
    	}
    
    	Sleep(1000);
    
    	Send_to_K60(15, 0, 0);//将将横挡板第二块挡板放在悬空位置（离地2cm）
    	Sleep(2000);
    	Sleep(1000);
    	jiaodu_jishu = 0;
    	while (1)
    	{ 
    
    		Mat srcImage0;
    
    
    		Mat	frame_2 = imgOriginal_up;
    		int width = frame_2.cols;
    		int height = frame_2.rows;
    
    		Mat image_cut;      //从img中按照rect进行切割，此时修改image_cut时image中对应部分也会修改，因此需要copy 
    		Mat image_copy_C3;   //clone函数创建新的图片 彩色
    
    		if (hengshu == 0)//横着
    		{ 
    			Rect rect(0, frame_2.rows*0.3, frame_2.cols, frame_2.rows*(0.95 - 0.3));   //创建一个Rect框，属于cv中的类，四个参数代表x,y,width,height 
    
    			Mat	image_cut = Mat(frame_2, rect);
    			image_copy_C3 = image_cut.clone();   //clone函数创建新的图片 
    		}
    		else //竖着
    		{ 
    			Rect rect(frame_2.cols*0.075, frame_2.rows*0.2, frame_2.cols*(0.875 - 0.075), frame_2.rows*(0.83 - 0.2));   //创建一个Rect框，属于cv中的类，四个参数代表x,y,width,height 
    			Mat	image_cut = Mat(frame_2, rect);
    			image_copy_C3 = image_cut.clone();   //clone函数创建新的图片 
    
    		}
    		int x, y;
    		double B = 0.0, G = 0.0, R = 0.0, H = 0.0, S = 0.0, V = 0.0;
    		int width1 = image_copy_C3.cols * 3;
    		int height1 = image_copy_C3.rows;
    		for (x = 0; x < height1; x++)
    		{ 
    			uchar* data = image_copy_C3.ptr<uchar>(x);//获取第i行的首地址
    			for (y = 0; y < width1; y += 3)
    			{ 
    				B = data[y];
    				G = data[y + 1];
    				R = data[y + 2];
    				RGB2HSV(R, G, B, H, S, V);
    				//红色范围，范围参考的网上。可以自己调
    				if ((H >= 286 && H <= 360 || H >= 0 && H <= 20) && (S >= 0 && S <= 360) && (V>0 && V < 360))
    					data[y] = data[y + 1] = data[y + 2] = 255;
    				else data[y] = data[y + 1] = data[y + 2] = 0;
    			}
    		}
    		Mat vec_rgb;
    		cvtColor(image_copy_C3, vec_rgb, CV_BGR2GRAY);//灰度化
    		//【3】srcImage取大于阈值119的那部分
    		vec_rgb = vec_rgb > 120;
    
    
    		//Mat element = getStructuringElement(MORPH_ELLIPSE, Size(2 * 1 + 1, 2 * 1 + 1), Point(1, 1));
    		Mat element1 = getStructuringElement(MORPH_ELLIPSE, Size(2 * 3 + 1, 2 * 3 + 1), Point(3, 3));
    		// Mat element1 = getStructuringElement(MORPH_RECT, Size(45, 45));
    		dilate(vec_rgb, vec_rgb, element1);//膨胀
    		/*namedWindow("膨胀", 0); imshow("膨胀", vec_rgb); waitKey(1);*/
    
    		erode(vec_rgb, vec_rgb, element1);//腐蚀
    		/*namedWindow("腐蚀", 0); imshow("腐蚀", vec_rgb); waitKey(1);*/
    
    		vector<vector<Point>>contours, max_contours; //轮廓
    		vector<Vec4i> hierarchy;//分层
    		Mat drawing_text = Mat::zeros(vec_rgb.size(), CV_8UC3);
    		findContours(vec_rgb, contours, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_NONE);//找轮廓
    		if (contours.size() == 0)
    		{ 
    			cout << "警告：没有红色挡板（第一次找轮廓）" << endl;
    
    			continue;
    		}
    		vector<vector<Point>> hull(contours.size());//用于存放凸包
    		vector<float> length(contours.size());
    		vector<float> Area_contours(contours.size()), Area_hull(contours.size()), Rectangularity(contours.size()), circularity(contours.size());
    
    // vector< Point2f> lunkuo_zhongxin_first;
    	// lunkuo_zhongxin_first = find_lunkuo_zhongxin(contours);
    
    
    		//int Xmin = (int)(vec_rgb.cols * 0);
    		//int Xmax = (int)(vec_rgb.cols);
    		//int Ymin = (int)(vec_rgb.rows * 0);
    		//int Ymax = (int)(vec_rgb.rows);
    
    		for (int i = 0; i < contours.size(); i++)
    		{ //历遍所有的轮廓
    
    			length[i] = arcLength(contours[i], true);
    
    			//cout << "轮廓长度为" << length[i] << endl;
    
    			if (length[i] >5 /*&& lunkuo_zhongxin_first[i].x>Xmin&&lunkuo_zhongxin_first[i].x<Xmax&&lunkuo_zhongxin_first[i].y>Ymin&&lunkuo_zhongxin_first[i].y<Ymax*/)
    			{ //通过长度匹配滤除小轮廓
    				convexHull(Mat(contours[i]), hull[i], false);//把凸包找出来 
    				max_contours.push_back(hull[i]);//把提取出来的方框导入到新的轮廓组
    			}
    		}
    		if (max_contours.size() == 0)
    		{ 
    			cout << "警告：y有红色物体，但是可能没有红色挡板，或者红色挡板被遮挡严重" << endl;
    
    			continue;
    		}
    
    		//将线连接起来
    		vector<Point2f> zhongxin_zuobiao;
    		zhongxin_zuobiao = find_lunkuo_zhongxin(max_contours);
    		if (zhongxin_zuobiao.size() >= 2)
    		{ 
    			for (int i = 0; i < zhongxin_zuobiao.size() - 1; i++)
    			{ 
    				for (int j = i + 1; j < zhongxin_zuobiao.size(); j++)
    				{ 
    					float dis_juxin = getDistance_1(zhongxin_zuobiao[i], zhongxin_zuobiao[j]);
    					if (dis_juxin < 65)
    					{ 
    						line(vec_rgb, zhongxin_zuobiao[i], zhongxin_zuobiao[j], Scalar(255), 4, LINE_AA);
    					}
    
    				}
    			}
    
    		}
    		//namedWindow("连接直线后", 0);
    		//imshow("连接直线后", vec_rgb);
    		//waitKey(1);
    
    
    		Mat vec_rgb1;
    
    		dilate(vec_rgb, vec_rgb1, element1);//膨胀
    		namedWindow("膨胀1", 0);
    		imshow("膨胀1", vec_rgb1);
    		waitKey(1);
    
    		erode(vec_rgb1, vec_rgb1, element1);//腐蚀
    		//namedWindow("腐蚀1", 0);
    		//imshow("腐蚀1", vec_rgb1);
    		//waitKey(1);
    
    		//第二次找轮廓
    		vector<vector<Point>>contours_1, RectContours; //轮廓
    		Mat drawing_1 = Mat(vec_rgb.size(), CV_8UC3, Scalar(0, 0, 0));
    		Mat  	dstImage = Mat(vec_rgb.size(), CV_8UC3, Scalar(0, 0, 0));   //clone函数创建新的图片 
    		findContours(vec_rgb, contours_1, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_NONE);//找轮廓
    
    		if (contours_1.size() == 0)
    		{ 
    			cout << "警告：没有在裁剪后的图片里找到轮廓（第二次找轮廓）" << endl;
    			continue;
    		}
    
    		vector< Point2f> lunkuo_zhongxin_temp, lunkuo_zhongxin1;
    		lunkuo_zhongxin_temp = find_lunkuo_zhongxin(contours_1);
    		if (contours_1.size() > 0)//如果没有找到轮廓退出
    		{ 
    			vector<vector<Point>> hull(contours_1.size());//用于存放凸包
    			vector<float> length(contours_1.size());
    
    			for (int i = 0; i < contours_1.size(); i++)
    			{ //历遍所有的轮廓
    
    				length[i] = arcLength(contours_1[i], true);
    
    				if (length[i] >170 && lunkuo_zhongxin_temp[i].x>190 && lunkuo_zhongxin_temp[i].x<305)
    				{ //通过长度匹配滤除小轮廓
    					convexHull(Mat(contours_1[i]), hull[i], false);//把凸包找出来
    					RectContours.push_back(hull[i]);//把提取出来的方框导入到新的轮廓组
    				}
    			}
    			// cout << "已找到裁剪后的新凸包" << endl;
    
    			if (RectContours.size() == 0)
    			{ 
    				cout << "警告：没有红色挡板（第一次找轮廓）" << endl;
    				continue;
    			}
    
    			lunkuo_zhongxin1 = find_lunkuo_zhongxin(RectContours);
    			if (lunkuo_zhongxin1.size() != 1)
    			{ 
    				cout << "警告：有两个红色挡板" << endl;
    				continue;
    			}
    
    			for (int i = 0; i < RectContours.size(); i++)
    			{ 
    				Scalar color = (255, 255, 255);//白色线画轮廓
    				drawContours(drawing_1, RectContours, i, color, 1, 8, hierarchy, 0, Point());//根据轮廓点集contours_poly和轮廓结构hierarchy画出轮廓
    				drawContours(dstImage, RectContours, i, color, 1, 8, hierarchy, 0, Point());//根据轮廓点集contours_poly和轮廓结构hierarchy画出轮廓
    				//画圆形
    			}
    
    			cvtColor(drawing_1, drawing_1, CV_BGR2GRAY);//灰度化
    			//【3】srcImage取大于阈值119的那部分
    			drawing_1 = drawing_1 > 20;
    		}
    
    		/******* 检测直线优化 开始 ****************************************************************/
    
    		Mat vec_rgb2;
    		vector<Vec4i> lines1, lines_final;//定义一个矢量结构lines用于存放得到的线段矢量集合
    
    		// Canny(drawing_1, vec_rgb2, cannyThreshold, cannyThreshold * factor);
    		HoughLinesP(drawing_1, lines1, 1, CV_PI / 180, 35, 30, 30);
    
    		if (lines1.size() == 0)
    		{ 
    			cout << "直线数量为零" << endl;
    			continue;
    		}
    
    		// cout << "canny边缘检测阈值为:" << cannyThreshold << endl;
    
    		/******* 检测直线优化 结束 ****************************************************************/
    
    		// cout << "\n共检测到原始 直线" << lines1.size() << "条" << endl;
    
    
    		//【4】依次计算出直线长度
    		float  zhixian_changdu;
    		for (size_t i = 0; i < lines1.size(); i++)
    		{ 
    			Vec4i l = lines1[i];
    			zhixian_changdu = getDistance_1(Point(l[0], l[1]), Point(l[2], l[3]));
    
    			//cout << "\n直线长度为" << zhixian_changdu << endl;
    
    			//画出原始直线
    			line(dstImage, Point(l[0], l[1]), Point(l[2], l[3]), Scalar(0, 255, 0), 1, LINE_AA);
    			float line_k = 0;
    			int a;
    			a = lines1[i][2] - lines1[i][0];
    			// cout << "参数为： " << a << endl;
    
    
    
    
    			if (hengshu == 0)//横着
    			{ 
    				if (fabs((double)(lines1[i][2] - lines1[i][0])) > 0.001)
    				{ 
    					line_k = (double)(lines1[i][3] - lines1[i][1]) / (double)(lines1[i][2] - lines1[i][0]); //求出直线的斜率
    					//cout << "\n直线的斜率为\n" << line_k << endl;
    					//斜率k以及b很接近的保留一条，两根直线应该是距离恒定的（一个比较稳定的范围）
    					//通过直线长度滤除，只剩下两条最长的,斜率要大于45度的直线
    					if (zhixian_changdu > 40 /*&& fabs(line_k)<1*/)
    					{ 
    						lines_final.push_back(lines1[i]);
    
    					}
    
    				}
    
    			}
    			else //竖着
    			{ 
    				if (fabs((double)(lines1[i][2] - lines1[i][0])) > 0.001)
    				{ 
    					line_k = (double)(lines1[i][3] - lines1[i][1]) / (double)(lines1[i][2] - lines1[i][0]); //求出直线的斜率
    					//cout << "\n直线的斜率为\n" << line_k << endl;
    					//斜率k以及b很接近的保留一条，两根直线应该是距离恒定的（一个比较稳定的范围）
    					//通过直线长度滤除，只剩下两条最长的,斜率要大于45度的直线
    					if (zhixian_changdu > 40 && fabs(line_k)>0.7)
    					{ 
    						lines_final.push_back(lines1[i]);
    
    					}
    
    				}
    				else
    				{ 
    					if (zhixian_changdu>40)
    					{ 
    						lines_final.push_back(lines1[i]);
    					}
    				}
    			}
    		}
    
    		//namedWindow("挡板直线", 0);
    		//imshow("挡板直线", drawing_1);
    		//waitKey(2);
    
    
    		vector <float> fangcheng_PARAM_1;
    
    
    		//最终只能检测出两条直线
    		int zhixian_geshu = lines_final.size();
    		// cout << "共有" << zhixian_geshu << "条直线进来了" << endl;
    		float line_k[4] = {  0 };
    		float line_b[4] = {  0 };
    		if (lines_final.size() == 0)
    		{ 
    			cout << "最终直线数量为零" << endl;
    			continue;
    		}
    
    		if (lines_final.size() >= 2)
    		{ 
    			int a, b = 0;
    			for (size_t i = 0; i < lines_final.size(); i++)
    			{ 
    				float line_k_temp;
    
    				//a = lines_final[i][2] - lines_final[i][0];
    				// cout << "参数为： " << a << endl;
    				if (fabs((double)(lines_final[i][2] - lines_final[i][0])) > 0.001)
    				{ 
    					b++;
    					line_k_temp = (double)(lines_final[i][3] - lines_final[i][1]) / (double)(lines_final[i][2] - lines_final[i][0]); //求出直线的斜率
    					// cout << "\n最终直线的斜率为\n" << line_k_temp << endl;
    					//斜率k以及b很接近的保留一条，两根直线应该是距离恒定的（一个比较稳定的范围）
    					//通过直线长度滤除，只剩下两条最长的,斜率要大于45度的直线
    					line_k[0] = line_k_temp + line_k[0];
    
    				}
    				else
    				{ 
    					line_k[0] = 70;
    					//曹，直线是个直的
    					// line_k = 8000;
    				}
    
    
    			}
    			line_k[3] = line_k[2];
    			line_k[2] = line_k[1];
    			line_k[1] = line_k[0];
    
    			line_k[0] = line_k[0] / b;
    			line_k[0] = 0.6* line_k[0] + 0.2* line_k[1] + 0.1* line_k[2] + 0.1* line_k[3];
    
    			Param_A2 = -line_k[0];
    			Param_B2 = 1;
    			Param_C2 = line_k[0] * lunkuo_zhongxin1[0].x - lunkuo_zhongxin1[0].y;
    
    			draw_line_1(Param_A2, Param_B2, Param_C2, dstImage);
    			draw_line_1(Param_A1, Param_B1, Param_C1, dstImage);
    
    		}
    
    
    		float theta, shuiping_diatance;
    
    
    		/***** 7、输入A，B，C,画出线在dstImage*****/
    
    		//最终求夹角（旋转误差）和平移误差
    		//两直线夹角，挡板相对于白色过道的夹角，因此白色过道直线斜率为第一个参数
    		theta = get_lines_yibanshi_arctan(Param_A1, Param_B1, Param_C1, Param_A2, Param_B2, Param_C2);
    
    		//点到直线距离
    		//P为线外一点，AB为线段两个端点
    		shuiping_diatance = getDist_P2L_zhengfu_2(lunkuo_zhongxin1[0], Param_A1, Param_B1, Param_C1,0);
    
    
    		cout << "\n最终结果\n挡板中轴线和白色过道中轴线夹角为： " << theta << " 度" << endl;
    		cout << "挡板中点与白色过道中轴线误差为： " << shuiping_diatance << endl;
    
    		//namedWindow("直线未滤除前", 0);
    		//imshow("直线未滤除前", image_copy_C3);
    		//waitKey(1);
    
    		namedWindow("【挡板夹角和位移示意图】", 0);//参数为零，则可以自由拖动
    		imshow("【挡板夹角和位移示意图】", dstImage);
    
    		//waitKey(1);
    		int error1 = 0, error2 = 0;
    		error1 = theta;
    
    		error2 = shuiping_diatance;//目标行数，291
    
    		// error2 = 0;//目标行数，291
    		error1 = error1 > 127 ? 127 : error1;
    		error1 = error1 < -127 ? -127 : error1;
    		error2 = error2 > 127 ? 127 : error2;
    		error2 = error2 < -127 ? -127 : error2;
    
    
    		Send_to_K60(12, error1, error2);
    
    		if (fabs((double)error1) < 1 && fabs((double)error2) <1.5)
    		{ 
    			jiaodu_jishu++;
    			if (jiaodu_jishu>5)
    			{ 
    				Send_to_K60(13, 0, 0);//将挡板放下并归右边位置 
    				cout << "\n放置挡板成功" << endl;
    				Sleep(1000);
    				break;
    			}
    		}
    		else if (jiaodu_jishu>0)
    		{ 
    			jiaodu_jishu--;
    		}
    	}
    
    }
    
    
    /******************************************************************************************* *函数功能 ： 用于顶部摄像头放置横着或者竖着的挡板前的定位 *输入参数 ： 第一个参数为目标数字第二个参数是 0为横着，1为竖着，第三个参数是 1为第一块挡板，2为第二块挡板， *返 回 值 ： 单条直线的ABC值，如果没有正确找到直线，就返回-1，函数外边再判断 *编写时间 ： 2018.8.13 *作 者 ： 毛哥（参考叶少及姚总） ********************************************************************************************/
    void Dangban_dingwei(int num_obj, int mode, int cishu)
    { 
    	//if (num_obj<10)
    	//{ 
    	// Dangban_DingWei_Single_Num(num_obj, mode, cishu);
    	//}
    	//else
    	//{ 
    	// Dangban_DingWei_Double_Num(num_obj, mode, cishu);
    	//}
    
    }
    /******************************************************************************************* *函数功能 ： 输入二值化图像，提取横竖线并拟合求出交点 *输入参数 ： 二值化图像 *返 回 值 ： 交点坐标 *编写时间 ： 2018.8.15 *作 者 ： Biger姚 ********************************************************************************************/
    Point findCrossPoint(Mat img)
    { 
    	Point CrossPoint;
    	vector<vector<Point>> contours;
    	vector<Vec4i>hierarchy;
    	Mat midImage, dstImage;
    	dstImage = findMaxContouns(img);
    	cvtColor(dstImage, midImage, COLOR_BGR2GRAY);
    	midImage = midImage > 2;
    	vector<Vec2f> lines;//定义一个矢量结构lines用于存放得到的线段矢量集合
    	HoughLines(midImage, lines, 1, CV_PI / 180, 50);
    	if (lines.size() > 0)
    	{ //横竖线分类 求出两条横竖线后求交点
    		vector<Vec2f> lines_h;//定义一个矢量结构lines用于存放得到的线段矢量集合
    		vector<Vec2f> lines_v;//定义一个矢量结构lines用于存放得到的线段矢量集合
    		float rho_min_h = 10000, rho_max_h = -10000, rho_min_v = 10000, rho_max_v = -10000;
    		float theta_sum_v = 0, theta_sum_h = 0;
    		float theta;
    		float rho_h, theta_h, rho_v, theta_v;
    		Point pt1, pt2, pt3, pt4;
    		double a, b;
    		double x0, y0;
    		//#pragma omp parallel for
    		for (int i = 0; i < lines.size(); i++)
    		{ 
    			theta = lines[i][1];
    			if (theta >= 2.355 || theta <= 0.785)lines_v.push_back(lines[i]);//shu
    			else if (theta >= 0.785&&theta <= 2.355)lines_h.push_back(lines[i]);//heng
    		}
    		/*heng*/
    		for (size_t i = 0; i < lines_h.size(); i++)
    		{ 
    			rho_h = lines_h[i][0], theta_h = lines_h[i][1];
    			theta_sum_h += theta_h;
    			/*a = cos(theta_h), b = sin(theta_h); x0 = a*rho_h, y0 = b*rho_h; pt1.x = cvRound(x0 + 1000 * (-b)); pt1.y = cvRound(y0 + 1000 * (a)); pt2.x = cvRound(x0 - 1000 * (-b)); pt2.y = cvRound(y0 - 1000 * (a)); line(src, pt1, pt2, Scalar(0, 0, 0), 2, LINE_AA);*/
    			if (rho_h >= rho_max_h)rho_max_h = rho_h;
    			if (rho_h <= rho_min_h)rho_min_h = rho_h;
    		}
    		rho_h = (rho_max_h + rho_min_h) / 2;
    		theta_h = theta_sum_h / lines_h.size();
    		a = cos(theta_h), b = sin(theta_h);
    		x0 = a*rho_h, y0 = b*rho_h;
    		pt1.x = cvRound(x0 + 1000 * (-b));
    		pt1.y = cvRound(y0 + 1000 * (a));
    		pt2.x = cvRound(x0 - 1000 * (-b));
    		pt2.y = cvRound(y0 - 1000 * (a));
    		//line(src, pt1, pt2, Scalar(0, 0, 255), 2, LINE_AA);
    
    		//shu
    		for (size_t i = 0; i < lines_v.size(); i++)
    		{ 
    			rho_v = lines_v[i][0], theta_v = lines_v[i][1];
    			if (theta_v<0.6)
    			{ 
    				theta_sum_v += theta_v;
    				theta_sum_v += CV_PI;
    			}
    			else  theta_sum_v += theta_v;
    			/*a = cos(theta_v), b = sin(theta_v); x0 = a*rho_v, y0 = b*rho_v; pt3.x = cvRound(x0 + 1000 * (-b)); pt3.y = cvRound(y0 + 1000 * (a)); pt4.x = cvRound(x0 - 1000 * (-b)); pt4.y = cvRound(y0 - 1000 * (a)); line(src, pt3, pt4, Scalar(0, 0, 0), 2, LINE_AA);*/
    			if (rho_v < 0)rho_v = -rho_v;
    			if (rho_v >= rho_max_v)rho_max_v = rho_v;
    			if (rho_v <= rho_min_v)rho_min_v = rho_v;
    		}
    		rho_v = (rho_max_v + rho_min_v) / 2;
    		theta_v = theta_sum_v / lines_v.size();
    		if (theta_v > CV_PI)theta_v -= CV_PI;
    		else rho_v = -rho_v;
    		a = cos(theta_v), b = sin(theta_v);
    		x0 = a*rho_v, y0 = b*rho_v;
    		pt3.x = cvRound(x0 + 1000 * (-b));
    		pt3.y = cvRound(y0 + 1000 * (a));
    		pt4.x = cvRound(x0 - 1000 * (-b));
    		pt4.y = cvRound(y0 - 1000 * (a));
    		//line(src, pt3, pt4, Scalar(0, 0, 255), 2, LINE_AA);
    
    		/*求直线交点*/
    		if (lines_v.size()>0 && lines_h.size() && lines_v.size())
    		{ 
    			float a1, b1, a2, b2;
    
    			if (pt1.x != pt2.x)a1 = (float)(pt1.y - pt2.y) / (float)(pt1.x - pt2.x);
    			else a1 = 1000;
    			b1 = (float)pt1.y - a1*(float)pt1.x;
    
    			if (pt3.x != pt4.x)a2 = (float)(pt3.y - pt4.y) / (float)(pt3.x - pt4.x);
    			else a2 = 1000;
    			b2 = (float)pt3.y - a2*(float)pt3.x;
    			CrossPoint.x = (b1 - b2) / (a2 - a1);
    			CrossPoint.y = a1 * (float)CrossPoint.x + b1;
    		}
    	}
    	return CrossPoint;
    }
    /******************************************************************************************* *函数功能 ： 用于顶部摄像头放置横着或者竖着的挡板前的定位 *输入参数 ： 第一个参数 0为横着，1为竖着 *返 回 值 ： 无 *编写时间 ： 2018.8.15 *作 者 ： Biger姚 ********************************************************************************************/
    void  CrossLocate(int mode)
    { 
    	Mat srcImage = Mat::zeros(240, 320, CV_8UC1);
    	Rect rect(80, 50, 160, 190);//前两个参数：原图中开始裁剪的坐标 后两个参数:矩形的列和行
    	Mat src, img;
    	Point center, target;
    	if (mode == 0)
    	{ 
    		target.x = 88;   //88
    		target.y = 104;  //104
    	}
    	else
    	{ 
    		target.x = 84;
    		target.y = 149;
    	}
    	int error_x, error_y;
    	error_x = 0;
    	error_y = 0;
    	while (true)
    	{ 
    		Forward_flag = 3;
    		img = imgOriginal_up;
    		img = img(rect);
    		img.copyTo(src);//复制原图用于显示
    		Mat imgHSV;
    		cvtColor(img, imgHSV, COLOR_BGR2HSV);
    		int iLowH_1 = 0;//红色的H：0-20,160-180
    		int iHighH_1 = 20;
    		int iLowH_2 = 140;//红色的H：0-20,160-180
    		int iHighH_2 = 180;
    		int iLowS = 0;
    		int iHighS = 255;
    		int iLowV = 0;
    		int iHighV = 255;
    		Mat imgThresholded1(img.size(), CV_8UC1, cv::Scalar(0));
    		Mat imgThresholded2(img.size(), CV_8UC1, cv::Scalar(0));
    		inRange(imgHSV, Scalar(iLowH_1, iLowS, iLowV), Scalar(iHighH_1, iHighS, iHighV), imgThresholded1); //Threshold the image
    		inRange(imgHSV, Scalar(iLowH_2, iLowS, iLowV), Scalar(iHighH_2, iHighS, iHighV), imgThresholded2); //Threshold the image
    		Mat imgThresholded_add;
    		addWeighted(imgThresholded1, 1, imgThresholded2, 1, 0, imgThresholded_add);
    		cvtColor(img, srcImage, CV_BGR2GRAY);
    		addWeighted(imgThresholded_add, 1, srcImage, 1, 0, srcImage);
    		srcImage = srcImage > 120;//改为全局变量
    		//输入二值化原图 找十字交点
    		center = findCrossPoint(srcImage);
    		//画出中心
    		circle(src, center, 10, Scalar(0, 0, 255), FILLED);
    		/*namedWindow("【结果】", 0); imshow("【结果】", src); waitKey(1);*/
    		error_x = -(target.x - center.x) / 2.8;//让右边数字移到右边
    		error_y = (target.y - center.y) / 2.8;
    		if (error_x > 10 || error_x<-10)
    		{ 
    			error_y = 0;
    		}
    		error_x = error_x > 120 ? 120 : error_x;
    		error_x = error_x < -120 ? -120 : error_x;
    		error_y = error_y > 120 ? 120 : error_y;
    		error_y = error_y < -120 ? -120 : error_y;
    		static int break_cnt = 0;
    		if (error_x>-3 && error_x<3 && error_y>-2 && error_y<2)
    		{ 
    			break_cnt++;
    			Send_to_K60(16, 0, 0);
    			Sleep(10);
    			if (break_cnt>8)
    			{ 
    				break_cnt = 0;
    				break;
    			}
    		}
    		else 
    		{ 
    			Send_to_K60(Forward_flag, error_x, error_y);
    			if (break_cnt > 0)
    			{ 
    				break_cnt--;
    			}
    		
    		}
    
    	
    	}
    	Send_to_K60(16, 0, 0);
    }
    
    /******************************************************************************************* *函数功能 ： 放置挡板前目标数字为个位数的定位，有横竖和第一块第二块之分 *输入参数 ： 第一个参数为目标数字，第二个参数是 0为横着，1为竖着，第三个参数是 1为第一块挡板，2为第二块挡板， *返 回 值 ： 空 *编写时间 ： 2018.8.13 *作 者 ： 毛哥（参考叶少及姚总） ********************************************************************************************/
    void Dangban_DingWei_Single_Num(int num_obj, int mode, int cishu)
    { 
    
    	int flag_finish = 0;
    
    	Forward_flag = 3;
    	int Finish_cnt = 0;
    	int error1 = 0, error2 = 0, text = 0;
    	//目标数字及目标数字隔壁的
    	int num_obj_units = num_obj;//个位
    	int num_obj_1 = num_obj + 1;//必须是两位数
    	int num_obj_units_1 = num_obj_1;//个位
    
    	//int pic_name = 0;
    	//char str1[2000];
    	Mat srcImage0;
    	for (int i = 0; i < 6; i++)
    	{ //取几帧图像缓冲
    		cap_up >> srcImage0;
    	}
    	Mat srcImage = Mat::zeros(600, 800, CV_8UC3);
    	Point Put_obj;
    	if (mode == PUT_CHESS)
    	{ 
    		Put_obj.x = 386;
    		Put_obj.y = 347;
    	}
    	else if (mode == PUT_BLOCK_H)
    	{ 
    		Put_obj.x = 386;
    		Put_obj.y = 140;
    	}
    	else if (mode == PUT_BLOCK_V)
    	{ 
    		Put_obj.x = 175;
    		Put_obj.y = 369;
    	}
    	while (1)
    	{ 
    		Point center_obj;
    		//clock_t start = clock();
    
    		Forward_flag = 3;
    		//cap_up >> srcImage0;
    		srcImage0 = imgOriginal_up;
    		if (!srcImage0.empty())
    		{ 
    			//imshow("原图0", srcImage0);
    			Mat drawing(srcImage.size(), CV_8UC3, cv::Scalar(0));
    			resize(srcImage0, srcImage, srcImage.size());
    			cvtColor(srcImage, srcImage, CV_BGR2GRAY);
    			srcImage = srcImage > G_threshold_up;//二值化
    
    			vector<Vec2f>lines = findHoughLines(srcImage);
    			vector<float> V_line = find_V_Lines(lines);
    			float angle = 0;
    			draw_line(V_line[0], V_line[1], V_line[2], drawing);
    			if (lines.size()>0)
    			{ 
    				angle = cvFastArctan(V_line[1], V_line[0]);
    			}
    			if (angle>90)
    			{ 
    				angle = angle - 180;
    			}
    			angle = angle * 2;
    			srcImage = Spin_Img(srcImage, angle);//车身倾斜旋转图像以识别数字
    
    			vector<Min_Rect> Doubt_num_decade, Doubt_num_units;
    			vector<Min_Rect> Doubt_num_decade_1, Doubt_num_units_1;
    
    			vector<Min_Rect>Doubt_numRect = Find_Doubt_NumRect(srcImage);//各种滤波找怀疑是数字框的矩形框
    
    			if (Doubt_numRect.size()>0)
    			{ 
    				for (int i = 0; i < Doubt_numRect.size(); i++)
    				{ 
    					int num = number_identify(Doubt_numRect[i].Pic, SVM_params_UP);
    
    					if (num == num_obj_units)
    					{ //识别数字滤波(个位)
    						Doubt_num_units.push_back(Doubt_numRect[i]);
    					}
    
    					if (num == num_obj_units_1)
    					{ //识别隔壁数字(个位)
    						Doubt_num_units_1.push_back(Doubt_numRect[i]);
    					}
    				}
    			}
    			int flag_1 = 0;
    			if (Doubt_num_units.size()>0)
    			{ //在怀疑是数字的方框里找最可能是需要的,得到目标坐标
    				float dis_min = 100000, dis = 0;
    				for (size_t i = 0; i < Doubt_num_units.size(); i++)
    				{ 
    					Point temp_center;
    					temp_center = Doubt_num_units[i].center;
    					dis = getDistance(Point(386, 401), temp_center);
    					if (dis<dis_min&&dis<400)
    					{ 
    						dis_min = dis;
    						center_obj = temp_center;
    						flag_1 = 1;
    						计算是否符合机械臂可抓取的范围
    						//float holder_Dis = getDistance(center_obj, holder_center);
    						//int theta = cvFastArctan((float)(holder_center.x - center_obj.x), (float)(holder_center.y - center_obj.y));
    						//if (holder_Dis>holder_radius - dia&&holder_radius + dia)
    						//{//可以抓取
    						// Send_to_K60(0, 0, 0);
    						// Sleep(50);
    						// Send_to_K60(7, -theta, 0);
    						// flag_finish++;
    						//}
    						//else
    						//{//计算运动目标
    						// Put_obj.x = holder_center.x - (float)(holder_radius)*sin(theta*0.0174);
    						// Put_obj.y = holder_center.y - (float)(holder_radius)*cos(theta*0.0174);
    						//}
    						circle(drawing, center_obj, 5, Scalar(0, 255, 0), FILLED, LINE_AA);
    					}
    				}
    				if (flag_finish>10)
    				{ //如果判断可以放，break出while1
    					break;
    				}
    				error1 = (Put_obj.x - center_obj.x);//让右边数字移到右边
    				error2 = (Put_obj.y - center_obj.y);
    				error1 = error1 > 120 ? 120 : error1;
    				error1 = error1 < -120 ? -120 : error1;
    				error2 = error2 > 120 ? 120 : error2;
    				error2 = error2 < -120 ? -120 : error2;
    			}
    			if (flag_1 == 0 && Doubt_num_units_1.size()>0)
    			{ //在怀疑是数字的方框里找最可能是需要的,得到目标坐标(隔壁数字)
    				float dis_min = 100000, dis = 0;
    				for (size_t i = 0; i < Doubt_num_units_1.size(); i++)
    				{ 
    					Point temp_center;
    					temp_center = Doubt_num_units_1[i].center;
    					dis = getDistance(Point(386, 401), temp_center);
    					if (dis<dis_min&&dis<400)
    					{ 
    						dis_min = dis;
    						center_obj = temp_center;
    						circle(drawing, center_obj, 5, Scalar(0, 0, 255), FILLED, LINE_AA);
    					}
    				}
    				error1 = -(800 - center_obj.x);//让右边数字移到右边
    				error2 = (401 - center_obj.y);
    				error1 = error1 > 120 ? 120 : error1;
    				error1 = error1 < -120 ? -120 : error1;
    				error2 = error2 > 120 ? 120 : error2;
    				error2 = error2 < -120 ? -120 : error2;
    			}
    
    			cout << "放置挡板定位error1为：" << error1 << endl;
    			cout << "放置挡板定位error2为：" << error2 << endl;
    			cout << "Forward_flag为：" << (int)Forward_flag << endl;
    
    
    			if (error1>30 || error1<-30)
    			{ 
    				error2 = 0;
    			}
    			if (center_obj.x == 0 && center_obj.y == 0)
    			{ 
    				error1 = -10;
    				error2 = -10;
    			}
    			Send_to_K60(Forward_flag, error1, error2);
    			//imshow("drawing1", drawing);
    			//imshow("原图", srcImage);
    			waitKey(1);
    		}
    	}
    
    	cout << "放置挡板定位成功" << endl;
    }
    
    
    //放挡板，必须是两位数
    //第一个参数是数字，第二个参数是竖着还是横着0为横着，1为竖着
    //*flag 4 爪子直立起来的，且有磁性，此时手动往机械臂上放置挡板
    // * flag - 4 爪子到了位置，开始放置，发送一次即可
    
    /*******************************************************************************************
    *函数功能 ： 放置挡板前目标数字为双数的定位，有横竖和第一块第二块之分
    *输入参数 ： 第一个参数为目标数字，第二个参数是 0为横着，1为竖着，第三个参数是 1为第一块挡板，2为第二块挡板，
    *返 回 值 ： 单条直线的ABC值，如果没有正确找到直线，就返回-1，函数外边再判断
    *编写时间 ： 2018.8.13
    *作    者 ： 毛哥（参考叶少及姚总）
    ********************************************************************************************/
    void Dangban_DingWei_Double_Num(int num_obj, int mode, int cishu)
    { 
    	int flag_finish = 0;//跳出计数，稳定性
    	Forward_flag = 3;
    	int Finish_cnt = 0;
    	int error1 = 0, error2 = 0, text = 0;
    	//目标数字及目标数字隔壁的
    	int num_obj_decade = num_obj / 10;//十位
    	int num_obj_units = num_obj % 10;//个位
    
    	int num_obj_1 = num_obj + 1;//必须是两位数
    	int num_obj_decade_1 = num_obj_1 / 10;//十位
    	int num_obj_units_1 = num_obj_1 % 10;//个位
    
    	Mat srcImage0;
    	Mat srcImage = Mat::zeros(600, 800, CV_8UC3);
    	Point Put_obj;
    
    	if (mode == PUT_CHESS)
    	{ 
    		Put_obj.x = 386;
    		Put_obj.y = 347;
    	}
    	else if (mode == PUT_BLOCK_H)//0为水平，已经调好（8月14日）
    	{ 
    		Put_obj.x = 198;
    		Put_obj.y = 158;
    	}
    	else if (mode == PUT_BLOCK_V)//1为竖直，已经调好（8月13日）
    	{ 
    		Put_obj.x = 200;
    		Put_obj.y = 270;
    	}
    
    	while (1)
    	{ 
    		Point center_obj;
    		//clock_t start = clock();
    
    		Forward_flag = 3;
    		srcImage0 = imgOriginal_up;
    		if (!srcImage0.empty())
    		{ 
    			//imshow("原图0", srcImage0);
    
    			Mat drawing(srcImage.size(), CV_8UC3, cv::Scalar(0));
    			resize(srcImage0, srcImage, srcImage.size());
    			cvtColor(srcImage, srcImage, CV_BGR2GRAY);
    			srcImage = srcImage > G_threshold_up;//二值化
    
    			vector<Vec2f>lines = findHoughLines(srcImage);
    			vector<float> V_line = find_V_Lines(lines);
    			float angle = 0;
    			draw_line(V_line[0], V_line[1], V_line[2], drawing);
    			if (lines.size() > 0)
    			{ 
    				angle = cvFastArctan(V_line[1], V_line[0]);
    			}
    			if (angle > 90)
    			{ 
    				angle = angle - 180;
    			}
    			angle = angle * 2;
    			//计算出角度后旋转图片
    			srcImage = Spin_Img(srcImage, angle);
    
    			vector<Min_Rect> Doubt_num_decade, Doubt_num_units;
    			vector<Min_Rect> Doubt_num_decade_1, Doubt_num_units_1;
    
    			//bug1，如果当前数字位置有
    			vector<Min_Rect>Doubt_numRect = Find_Doubt_NumRect(srcImage);//各种滤波找怀疑是数字框的矩形框
    
    			if (Doubt_numRect.size()>0)
    			{ 
    				for (int i = 0; i < Doubt_numRect.size(); i++)
    				{ 
    					int num = number_identify(Doubt_numRect[i].Pic, SVM_params_UP);
    					if (num == num_obj_decade)
    					{ //识别数字滤波(十位)
    						Doubt_num_decade.push_back(Doubt_numRect[i]);
    					}
    					if (num == num_obj_units)
    					{ //识别数字滤波(个位)
    						Doubt_num_units.push_back(Doubt_numRect[i]);
    					}
    					if (num == num_obj_decade_1)
    					{ //识别隔壁数字(十位)
    						Doubt_num_decade_1.push_back(Doubt_numRect[i]);
    					}
    					if (num == num_obj_units_1)
    					{ //识别隔壁数字(个位)
    						Doubt_num_units_1.push_back(Doubt_numRect[i]);
    					}
    				}
    			}
    			int flag_1 = 0;
    			if (Doubt_num_decade.size()>0 && Doubt_num_units.size()>0)
    			{ //在怀疑是数字的方框里找最可能是需要的,得到目标坐标
    				vector<Min_Rect>Doubt_num_obj(2);
    				float dis_min = 100000, dis = 0;
    				for (int i = 0; i < Doubt_num_decade.size(); i++)
    				{ 
    					for (int j = 0; j < Doubt_num_units.size(); j++)
    					{ 
    						if (Doubt_num_decade[i].center.x<Doubt_num_units[j].center.x)
    						{ //dis为两中心点距离，center与目标点的距离加权
    							Point temp_center;
    							temp_center.x = (Doubt_num_decade[i].center.x + Doubt_num_units[j].center.x) / 2;
    							temp_center.y = (Doubt_num_decade[i].center.y + Doubt_num_units[j].center.y) / 2;
    							dis = getDistance(Doubt_num_decade[i].center, Doubt_num_units[j].center)
    								+ getDistance(Point(386, 347), temp_center);
    							if (dis<dis_min&&dis<400)
    							{ //如果可以找到目标数字中心
    								dis_min = dis;
    								Doubt_num_obj[0] = Doubt_num_decade[i];
    								Doubt_num_obj[1] = Doubt_num_units[j];
    								center_obj = temp_center; //数字中心
    								flag_1 = 1;
    								circle(drawing, center_obj, 5, Scalar(255, 0, 0), FILLED, LINE_AA);
    								//计算是否符合机械臂可抓取的范围
    								//float holder_Dis = getDistance(center_obj, holder_center);
    								//int theta = cvFastArctan((float)(holder_center.x - center_obj.x), (float)(holder_center.y - center_obj.y));
    								//if (holder_Dis>holder_radius - dia&&holder_radius + dia)
    								//{//可以抓取
    								// Send_to_K60(0, 0, 0);
    								// Sleep(50);
    								// Send_to_K60(7, -theta, 0);
    								// flag_finish++;
    								//}
    								//else
    								//{//计算运动目标
    								// Put_obj.x = holder_center.x - (float)(holder_radius)*sin(theta*0.0174);
    								// Put_obj.y = holder_center.y - (float)(holder_radius)*cos(theta*0.0174);
    								//}
    							}
    						}
    					}
    				}
    
    				//error1 = (int)((365.0 - (float)center_obj.x) / 1.6);//1.6这个系数刚好，电压8.2V左右
    				//error2 = (int)((136.0 - (float)center_obj.y) / 1.0);//1.0这个系数刚好
    
    				error1 = -(float)(Put_obj.x - center_obj.x) / 8.0;//让右边数字移到右边
    				error2 = (float)(Put_obj.y - center_obj.y) / 8.0;
    				error1 = error1 > 120 ? 120 : error1;
    				error1 = error1 < -120 ? -120 : error1;
    				error2 = error2 > 120 ? 120 : error2;
    				error2 = error2 < -120 ? -120 : error2;
    			}
    			if (flag_1 == 0 && Doubt_num_decade_1.size()>0 && Doubt_num_units_1.size()>0)
    			{ //在怀疑是数字的方框里找最可能是需要的,得到目标坐标(隔壁数字)
    				vector<Min_Rect>Doubt_num_obj(2);
    				float dis_min = 100000, dis = 0;
    				for (int i = 0; i < Doubt_num_decade_1.size(); i++)
    				{ 
    					for (int j = 0; j < Doubt_num_units_1.size(); j++)
    					{ 
    						if (Doubt_num_decade_1[i].center.x<Doubt_num_units_1[j].center.x)
    						{ //dis为两中心点距离，center与目标点的距离加权
    							Point temp_center;
    							temp_center.x = (Doubt_num_decade_1[i].center.x + Doubt_num_units_1[j].center.x) / 2;
    							temp_center.y = (Doubt_num_decade_1[i].center.y + Doubt_num_units_1[j].center.y) / 2;
    							dis = getDistance(Doubt_num_decade_1[i].center, Doubt_num_units_1[j].center)
    								+ getDistance(Point(386, 347), temp_center);
    							if (dis<dis_min&&dis<400)
    							{ 
    								dis_min = dis;
    								Doubt_num_obj[0] = Doubt_num_decade_1[i];
    								Doubt_num_obj[1] = Doubt_num_units_1[j];
    								center_obj = temp_center;
    								circle(drawing, center_obj, 5, Scalar(255, 0, 0), FILLED, LINE_AA);
    							}
    						}
    					}
    				}
    				error1 = -(800 - center_obj.x);//让右边数字移到右边
    				error2 = (Put_obj.y - center_obj.y);
    				error1 = error1 > 120 ? 120 : error1;
    				error1 = error1 < -120 ? -120 : error1;
    				error2 = error2 > 120 ? 120 : error2;
    				error2 = error2 < -120 ? -120 : error2;
    
    				//目标 放棋子：center:x=386,y=347
    				//目标 放挡板：center:x=386,y=149
    			}
    			//cout << "放置挡板定位error1为：" << error1 << endl;
    			//cout << "放置挡板定位error2为：" << error2 << endl;
    			//cout << "Forward_flag为：" << (int)Forward_flag << endl;
    
    
    			if (error1>30 || error1<-30)
    			{ 
    				error2 = 0;
    			}
    			if (center_obj.x == 0 && center_obj.y == 0)
    			{ 
    				error1 = -25;
    				error2 = -25;
    			}
    			if (error1<7 && error2<7 && error1>-7 && error2>-7)
    			{ 
    				Forward_flag = 16;
    				flag_finish++;
    				// cout << "Finish_cnt为：" << Finish_cnt << endl;
    				if (flag_finish>5)
    				{ 
    					break;
    				}
    			}
    			else
    			{ 
    				flag_finish = 0;
    
    			}
    
    
    			Send_to_K60(Forward_flag, error1, error2);
    			//imshow("drawing1", drawing);
    			//imshow("原图", srcImage);
    			waitKey(1);
    		}
    	}
    	//放下
    	cout << "放置挡板定位成功" << endl;
    }
    
    
    
    /*找最大的轮廓*/
    Mat findMaxContouns(Mat img)
    { 
    	vector<vector<Point>> contours;
    	vector<Vec4i>hierarchy;
    	int row_i, col_i;
    	float row_max = 0.0, col_min = 3.3;
    	findContours(img, contours, hierarchy, CV_RETR_CCOMP, CV_CHAIN_APPROX_SIMPLE);
    	Mat dstImage = Mat::zeros(img.size(), CV_8UC3);
    	long int max_l = 0;
    	int max_i = 0;
    	if (contours.size() > 0)
    	{ 
    		vector<float> length(contours.size());
    		//找最大的轮廓
    #pragma omp parallel for
    		for (int i = 0; i < contours.size(); i++)
    		{ 
    			length[i] = arcLength(contours[i], true);
    		}
    		for (int i = 0; i < contours.size(); i++)
    		{ 
    			if (length[i] > max_l)
    			{ 
    				max_l = length[i];
    				max_i = i;
    			}
    		}
    		drawContours(dstImage, contours, max_i, (0, 0, 255), 1, 8, hierarchy);
    		//imshow("轮廓图", dstImage);
    	}
    	//center = findContunsCenter(contours, max_i);
    	return dstImage;
    }
    /******************************************************************************************* *函数功能 ： 获取横线或竖线一般式方程参数 *输入参数 ： mode,0横1竖 *返 回 值 ： PARAM 一般式ABC三个参数 *编写时间 ： 2018.8.15 *作 者 ： 姚 ********************************************************************************************/
    vector <float> getVHlineParam(int mode)
    { 
    	int cnt = 0;
    	//vector <float> PARAM;
    	float A = 0, B = 0, C = 0;
    	float filter_A[4] = {  0 }, filter_B[4] = {  0 }, filter_C[4] = {  0 };
    	vector<vector<Point>> contours;
    	vector<Vec4i>hierarchy;
    	Mat midImage, dstImage, img, src, img0;
    	int break_cnt = 0;
    	Point pt1, pt2, pt3, pt4;
    	while (true)
    	{ 
    		img = imgOriginal_up;
    		if (mode == 0)//横着
    		{ 
    			Rect rect(0, img.rows*0.3, img.cols, img.rows*(0.95 - 0.3));   //创建一个Rect框，属于cv中的类，四个参数代表x,y,width,height 
    			img = img(rect);
    		}
    		else //竖着
    		{ 
    			Rect rect(img.cols*0.075, img.rows*0.2, img.cols*(0.875 - 0.075), img.rows*(0.83 - 0.2));   //创建一个Rect框，属于cv中的类，四个参数代表x,y,width,height 
    			img = img(rect);
    		}
    		img.copyTo(src);
    		cvtColor(img, img0, COLOR_BGR2GRAY);
    		img0 = img0 > 110;
    		dstImage = findMaxContouns(img0);
    		cvtColor(dstImage, midImage, COLOR_BGR2GRAY);
    		midImage = midImage > 2;
    		vector<Vec2f> lines;//定义一个矢量结构lines用于存放得到的线段矢量集合
    		HoughLines(midImage, lines, 1, CV_PI / 180, 60);
    		if (lines.size() > 0)
    		{ //横竖线分类 求出两条横竖线后求交点
    			vector<Vec2f> lines_h;//定义一个矢量结构lines用于存放得到的线段矢量集合
    			vector<Vec2f> lines_v;//定义一个矢量结构lines用于存放得到的线段矢量集合
    			float rho_min_h = 10000, rho_max_h = -10000, rho_min_v = 10000, rho_max_v = -10000;
    			float theta_sum_v = 0, theta_sum_h = 0;
    			float theta;
    			float rho_h, theta_h, rho_v, theta_v;
    			double a, b;
    			double x0, y0;
    			for (int i = 0; i < lines.size(); i++)
    			{ 
    				theta = lines[i][1];
    				if (theta >= 2.355 || theta <= 0.785)lines_v.push_back(lines[i]);//shu
    				else if (theta >= 0.785&&theta <= 2.355)lines_h.push_back(lines[i]);//heng
    			}
    			/*heng*/
    			if (mode == 0)
    			{ 
    				for (size_t i = 0; i < lines_h.size(); i++)
    				{ 
    					rho_h = lines_h[i][0], theta_h = lines_h[i][1];
    					theta_sum_h += theta_h;
    					/*a = cos(theta_h), b = sin(theta_h); x0 = a*rho_h, y0 = b*rho_h; pt1.x = cvRound(x0 + 1000 * (-b)); pt1.y = cvRound(y0 + 1000 * (a)); pt2.x = cvRound(x0 - 1000 * (-b)); pt2.y = cvRound(y0 - 1000 * (a)); line(src, pt1, pt2, Scalar(0, 0, 0), 1, LINE_AA);*/
    					if (rho_h >= rho_max_h)rho_max_h = rho_h;
    					if (rho_h <= rho_min_h)rho_min_h = rho_h;
    				}
    				rho_h = (rho_max_h + rho_min_h) / 2;
    				theta_h = theta_sum_h / lines_h.size();
    				a = cos(theta_h), b = sin(theta_h);
    				x0 = a*rho_h, y0 = b*rho_h;
    				pt1.x = cvRound(x0 + 1000 * (-b));
    				pt1.y = cvRound(y0 + 1000 * (a));
    				pt2.x = cvRound(x0 - 1000 * (-b));
    				pt2.y = cvRound(y0 - 1000 * (a));
    				line(src, pt1, pt2, Scalar(0, 0, 255), 2, LINE_AA);
    
    				filter_A[3] = filter_A[2];
    				filter_B[3] = filter_B[2];
    				filter_C[3] = filter_C[2];
    
    				filter_A[2] = filter_A[1];
    				filter_B[2] = filter_B[1];
    				filter_C[2] = filter_C[1];
    
    				filter_A[1] = filter_A[0];
    				filter_B[1] = filter_B[0];
    				filter_C[1] = filter_C[0];
    
    				filter_A[0] = pt2.y - pt1.y;
    				filter_B[0] = pt1.x - pt2.x;
    				filter_C[0] = pt1.y*(pt2.y - pt1.y) - pt1.x*(pt2.y - pt1.y);
    				if (fabs(filter_A[0] - filter_A[1])<2)
    				{ 
    					cnt++;
    					A = 0.4*filter_A[0] + 0.3*filter_A[1] + 0.2*filter_A[2] + 0.1*filter_A[3];
    					B = 0.4*filter_B[0] + 0.3*filter_B[1] + 0.2*filter_B[2] + 0.1*filter_B[3];
    					C = 0.4*filter_C[0] + 0.3*filter_C[1] + 0.2*filter_C[2] + 0.1*filter_C[3];
    					if (cnt>8)
    					{ 
    						break;
    					}
    				}
    				else
    				{ 
    					if (cnt>0)cnt--;
    				}
    			}
    			else
    			{ 
    				//shu
    				for (size_t i = 0; i < lines_v.size(); i++)
    				{ 
    					rho_v = lines_v[i][0], theta_v = lines_v[i][1];
    					if (theta_v<0.6)
    					{ 
    						theta_sum_v += theta_v;
    						theta_sum_v += CV_PI;
    					}
    					else  theta_sum_v += theta_v;
    					/*a = cos(theta_v), b = sin(theta_v); x0 = a*rho_v, y0 = b*rho_v; pt3.x = cvRound(x0 + 1000 * (-b)); pt3.y = cvRound(y0 + 1000 * (a)); pt4.x = cvRound(x0 - 1000 * (-b)); pt4.y = cvRound(y0 - 1000 * (a)); line(src, pt3, pt4, Scalar(0, 0, 0), 1, LINE_AA);*/
    					if (rho_v < 0)rho_v = -rho_v;
    					if (rho_v >= rho_max_v)rho_max_v = rho_v;
    					if (rho_v <= rho_min_v)rho_min_v = rho_v;
    				}
    				rho_v = (rho_max_v + rho_min_v) / 2;
    				theta_v = theta_sum_v / lines_v.size();
    				if (theta_v > CV_PI)theta_v -= CV_PI;
    				else rho_v = -rho_v;
    				a = cos(theta_v), b = sin(theta_v);
    				x0 = a*rho_v, y0 = b*rho_v;
    				pt3.x = cvRound(x0 + 1000 * (-b));
    				pt3.y = cvRound(y0 + 1000 * (a));
    				pt4.x = cvRound(x0 - 1000 * (-b));
    				pt4.y = cvRound(y0 - 1000 * (a));
    				line(src, pt3, pt4, Scalar(0, 0, 255), 2, LINE_AA);
    				filter_A[3] = filter_A[2];
    				filter_B[3] = filter_B[2];
    				filter_C[3] = filter_C[2];
    
    				filter_A[2] = filter_A[1];
    				filter_B[2] = filter_B[1];
    				filter_C[2] = filter_C[1];
    
    				filter_A[1] = filter_A[0];
    				filter_B[1] = filter_B[0];
    				filter_C[1] = filter_C[0];
    
    				filter_A[0] = pt4.y - pt3.y;
    				filter_B[0] = pt3.x - pt4.x;
    				filter_C[0] = pt3.y*(pt4.y - pt3.y) - pt3.x*(pt4.y - pt3.y);
    				if (fabs(filter_A[0] - filter_A[1])<2)
    				{ 
    					cnt++;
    					A = 0.4*filter_A[0] + 0.3*filter_A[1] + 0.2*filter_A[2] + 0.1*filter_A[3];
    					B = 0.4*filter_B[0] + 0.3*filter_B[1] + 0.2*filter_B[2] + 0.1*filter_B[3];
    					C = 0.4*filter_C[0] + 0.3*filter_C[1] + 0.2*filter_C[2] + 0.1*filter_C[3];
    					if (cnt>8)
    					{ 
    						break;
    					}
    				}
    				else
    				{ 
    					if (cnt>0)cnt--;
    				}
    			}
    			namedWindow("图像", 0);
    			imshow("图像", src);
    			waitKey(1);
    		}
    	}
    	vector<float> fangcheng_PARAM;
    	if (mode == 0)
    	{ 
    		fangcheng_PARAM = get_lines_yibanshi_fangcheng_2(pt1, pt2);
    	}
    	else
    	{ 
    		fangcheng_PARAM = get_lines_yibanshi_fangcheng_2(pt3, pt4);
    	}
    	return fangcheng_PARAM;
    	//PARAM.push_back(A);
    	//PARAM.push_back(B);
    	//PARAM.push_back(C);
    	//return PARAM;
    }