效果图
/**************************************************************************************
该程序功能：放置挡板
* flag 1 前进
* flag -1 后退
* flag 2 横走右
* flag -2 横走左
* flag 3 找中心
Forward_flag = -2;//发送开环左走指令
* 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
* flag 9 右转90度
* flag -9 左转90度
* flag 18 右转180度
* flag -18 左转180度
* flag 18 右转180度
* flag -100 放下棋子
方向dir： 0.从下往上看
1.从左往右看
2.从上往下看
3.从右往左看
3 开启找棋子中心模式
4 代表先打开电磁铁 -4放下 针对于障碍
****************************************************************************************/
#include<opencv2/opencv.hpp>
#include <opencv.hpp>
#include <iostream>
#include<time.h>
#include<math.h>
#include<thread>
//#include "UART.h"
#include "findline.h"
//#include "Number.h"
//#include "Process.h"
//#include "Locate.h"
//#include "Manipulator_positioning.h"
using namespace cv;
using namespace std;
#define PI 3.1415926
RNG g_rng(12345);
//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 * PI - theta;
if (s <= 0.01)
h = 0;
}
hue = (int)(h * 180 / PI);
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
float getDist_P2L_zhengfu_2(CvPoint pointP, float Param_A1, float Param_A2, float Param_A3)
{
//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 (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 <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;
// float A0 = 0, B0 = 0, C0 = 0;
// for (unsigned int i = 0; i<lines.size(); i++)
// {
// 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)(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_PARAM;
//}
//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]);
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
*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) > 0.001 && fabs(Param_B2) > 0.001)
{
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 < 0.0001&& Param_B2>0.0001)
{
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 > 0.0001&&Param_B2 < 0.0001)
{
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;
}
Mat frame1; //全局变量前方摄像头图像
Mat frame2; //全局变量顶部摄像头图像
VideoCapture capcap_1(1); //前方摄像头
VideoCapture capcap_2(0); //顶部 摄像头
int main()
{
capcap_2.set(CAP_PROP_FRAME_WIDTH, 1280.0);//设置摄像头采集图像分辨率
capcap_2.set(CAP_PROP_FRAME_HEIGHT, 720.0);
capcap_1.set(CAP_PROP_FRAME_WIDTH, 1280.0);//设置摄像头采集图像分辨率
capcap_1.set(CAP_PROP_FRAME_HEIGHT, 720.0);
if (!capcap_2.isOpened())return 0;
if (!capcap_1.isOpened())return 0;
for (int i = 0; i < 5; i++)
{
capcap_2 >> frame2;
}
while (1)
{
printf("\n\n\t\t\t 当前使用的OpenCV版本为" CV_VERSION"\n");
Mat srcImage0;
capcap_2 >> frame2;
//载入原图，并找到红色挡板
// Mat srcImage = imread("13.jpg", 1);
Mat srcImg;
resize(frame2, srcImg, Size(800, 600));//重定义图片大小
//namedWindow("原图", 0);
//imshow("原图", srcImg);
//waitKey(1);
int width = srcImg.cols;
int height = srcImg.rows;
int x, y;
double B = 0.0, G = 0.0, R = 0.0, H = 0.0, S = 0.0, V = 0.0;
Mat vec_rgb = Mat::zeros(srcImg.size(), CV_8UC1);
for (x = 0; x < height; x++)
{
for (y = 0; y < width; y++)
{
B = srcImg.at<Vec3b>(x, y)[0];
G = srcImg.at<Vec3b>(x, y)[1];
R = srcImg.at<Vec3b>(x, 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 >= 312 && H <= 360 || H >= 0 && H <= 20) && (S >= 17 && S <= 100) && (V>18 && V < 100))
vec_rgb.at<uchar>(x, y) = 255;
}
}
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));
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_LIST, 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());
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] >285 && length[i] < 2300)
{//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;
}
/*************************************************************************
2、切割出红色挡板附近的区域
*************************************************************************/
//多边形逼近轮廓 + 获取矩形和圆形边界框
vector<vector<Point> > contours_poly(max_contours.size());
vector<Rect> boundRect(max_contours.size());
vector<Point2f>center(max_contours.size());
vector<float>radius(max_contours.size());
//一个循环，遍历所有部分，进行本程序最核心的操作
for (unsigned int i = 0; i < max_contours.size(); i++)
{
approxPolyDP(Mat(max_contours[i]), contours_poly[i], 3, true);//用指定精度逼近多边形曲线
boundRect[i] = boundingRect(Mat(contours_poly[i]));//计算点集的最外面（up-right）矩形边界
minEnclosingCircle(contours_poly[i], center[i], radius[i]);//对给定的 2D点集，寻找最小面积的包围圆形
}
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
Mat image_copy_C1; //clone函数创建新的图片 黑白
int width1 = abs(boundRect[0].tl().x - boundRect[0].br().x);
int height1 = abs(boundRect[0].tl().y - boundRect[0].br().y);
//Rect rect(boundRect[0].tl().x - 50, boundRect[0].tl().y - 120, width1 + 110, height1 + 200); //创建一个Rect框，属于cv中的类，四个参数代表x,y,width,height
Rect rect(boundRect[0].tl().x - 50, 90, width1 + 110, vec_rgb.rows-130); //创建一个Rect框，属于cv中的类，四个参数代表x,y,width,height
image_cut = Mat(srcImg, rect); //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
image_copy_C3 = image_cut.clone(); //clone函数创建新的图片
image_cut = Mat(vec_rgb, rect); //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
image_copy_C1 = image_cut.clone(); //clone函数创建新的图片
namedWindow("裁剪后彩色", 0);
imshow("裁剪后彩色", image_copy_C3);
waitKey(1);
namedWindow("裁剪后黑白", 0);
imshow("裁剪后黑白", image_copy_C1);
waitKey(1);
cout << "已裁剪" << endl;
vector<vector<Point>>contours_1, RectContours; //轮廓
Mat drawing_1 = Mat(image_copy_C1.size(), CV_8UC3, Scalar(0, 0, 0));
findContours(image_copy_C1, contours_1, CV_RETR_LIST, 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;
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
int i = 0;
vector<float> length(contours_1.size());
vector<float> Area_contours(contours_1.size()), Area_hull(contours_1.size()), Rectangularity(contours_1.size()), circularity(contours_1.size());
for (i = 0; i < contours_1.size(); i++)
{//历遍所有的轮廓
length[i] = arcLength(contours_1[i], true);
if (length[i] >100 && length[i] < 3500)
{//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;
for (int i = 0; i < RectContours.size(); i++)
{
Scalar color = (255, 255, 255);//蓝色线画轮廓
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
//画圆形
}
fillHole(drawing_1, drawing_1);//填充
namedWindow("填充", 0);
imshow("填充", drawing_1);
waitKey(1);
dilate(drawing_1, drawing_1, element1);//膨胀
namedWindow("膨胀1", 0);
imshow("膨胀1", drawing_1);
waitKey(1);
erode(drawing_1, drawing_1, element1);//腐蚀
namedWindow("腐蚀1", 0);
imshow("腐蚀1", drawing_1);
waitKey(1);
}
namedWindow("红色挡板凸包", 0);
imshow("红色挡板凸包", drawing_1);
waitKey(1);
/********再次找轮廓******************************************************************************************/
cvtColor(drawing_1, drawing_1, CV_BGR2GRAY);
/* namedWindow("灰度化", 0);
imshow("灰度化", drawing_1);
waitKey(1);
*/
drawing_1 = drawing_1 >160;//二值化
/* namedWindow("二值化", 0);
imshow("二值化", drawing_1);
waitKey(1);*/
vector<vector<Point>>contours_2, RectContours_2; //轮廓
Mat drawing_2 = Mat(image_copy_C1.size(), CV_8UC3, Scalar(0, 0, 0));
findContours(drawing_1, contours_2, CV_RETR_LIST, CV_CHAIN_APPROX_NONE);//找轮廓
if (contours_2.size() == 0)
{
cout << "警告：没有在膨胀处理后的的图片里找到轮廓（第三次找轮廓）" << endl;
continue;
}
cout << "第三次找轮廓结束，共找到轮廓：" << contours_2.size() << " 条" << endl;
if (contours_2.size() > 0)//如果没有找到轮廓退出
{
vector<vector<Point>> hull(contours_2.size());//用于存放凸包
int i = 0;
vector<float> length(contours_2.size());
vector<float> Area_contours(contours_2.size()), Area_hull(contours_2.size()), Rectangularity(contours_2.size()), circularity(contours_2.size());
for (i = 0; i < contours_2.size(); i++)
{//历遍所有的轮廓
length[i] = arcLength(contours_2[i], true);
if (length[i] >100 && length[i] < 3500)
{//通过长度匹配滤除小轮廓
convexHull(Mat(contours_2[i]), hull[i], false);//把凸包找出来
RectContours_2.push_back(hull[i]);//把提取出来的方框导入到新的轮廓组
}
}
for (int i = 0; i < RectContours_2.size(); i++)
{
Scalar color = (0, 255, 255);//蓝色线画轮廓
drawContours(drawing_2, RectContours_2, 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
}
/**************************************************************************************************/
}
namedWindow("哈哈哈", 0);
imshow("哈哈哈", drawing_2);
waitKey(1);
/***** 4、ConnorPoint_Output 把所有排好序的角点输出，0号是左上角，顺时针输出(综合1、2、3)*****/
vector<Index_Point> ConnorPoint(4);
vector<Point> ConnorPoint_ordered(4);
vector<vector<Point>> ConnorPoint_Output(4);
for (int i = 0; i < RectContours_2.size(); i++)
{
ConnorPoint = FindConnor(RectContours_2[i]);
ConnorPoint_ordered = FindFirstPoint(ConnorPoint);
ConnorPoint_Output[0].push_back(ConnorPoint_ordered[2]);
ConnorPoint_Output[1].push_back(ConnorPoint_ordered[1]);
ConnorPoint_Output[2].push_back(ConnorPoint_ordered[0]);
ConnorPoint_Output[3].push_back(ConnorPoint_ordered[3]);
}
Point A_top, B_bottom; //红色挡板顶部中点，红色挡板底部中点
A_top.x = (ConnorPoint_Output[0][0].x + ConnorPoint_Output[1][0].x) / 2;
A_top.y = (ConnorPoint_Output[0][0].y + ConnorPoint_Output[1][0].y) / 2;
B_bottom.x = (ConnorPoint_Output[3][0].x + ConnorPoint_Output[2][0].x) / 2;
B_bottom.y = (ConnorPoint_Output[3][0].y + ConnorPoint_Output[2][0].y) / 2;
//上面没什么大问题，
//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。
Mat midImage, dstImage;//临时变量和目标图的定义
Mat image_copy_C3_1;
cvtColor(image_copy_C3, image_copy_C3_1, CV_BGR2GRAY);//灰度化
//【3】srcImage取大于阈值119的那部分
image_copy_C3_1 = image_copy_C3_1 > 150;
namedWindow("取阈值后的图", 0);
imshow("取阈值后的图", image_copy_C3_1);
//blur(image_copy_C3_1, image_copy_C3_1, Size(3, 3));//进行模糊
/******* 检测直线优化 开始 ****************************************************************/
int cannyThreshold = 80;
float factor = 2.5;
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, 320, 240, 30);
Canny(image_copy_C3_1, midImage, cannyThreshold, cannyThreshold * factor);
HoughLinesP(midImage, lines, 1, CV_PI / 180, 70, 40, 80);
最多的直线
//while (lines.size() >= 10)
//{
// cout << "正在循环，直线数大于10条" << endl;
// //cannyThreshold += 2;
// //Canny(image_copy_C3_1, midImage, cannyThreshold, cannyThreshold * factor);
// HoughLinesP(midImage, lines, 1, CV_PI / 180, 50, 20, 50);
//}
最少的直线
//while (lines.size() <= 2)
//{
// cout << "正在循环，直线数小于2条" << endl;
// //cannyThreshold -= 2;
// //Canny(image_copy_C3_1, midImage, cannyThreshold, cannyThreshold * factor);
// HoughLinesP(midImage, lines, 1, CV_PI / 180, 50, 20, 50);
//}
cout << "canny边缘检测阈值为:" << cannyThreshold << endl;
/*Canny(image_copy_C3_1, midImage, cannyThreshold, cannyThreshold * factor);
HoughLinesP(midImage, lines, 1, CV_PI / 180, 60, 50, 250);*/
/******* 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
line(dstImage, A_top, B_bottom, Scalar(0, 255, 0), 1, LINE_AA);//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;
//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_distance1;
/***** 点到一堆直线的距离:P到lines的距离*****/
// vector <float> getDist_P2L_yibanshi(Point pointP, vector<Vec4i> lines)
get_0_distance1 = getDist_P2L_yibanshi(Point2f(0.0, 0.0), lines);
for (size_t i = 0; i < lines.size(); i++)
{
Vec4i l = lines[i];
zhixian_changdu = getDistance(Point(l[0], l[1]), Point(l[2], l[3]));
cout << "\n直线长度为" << zhixian_changdu << endl;
cout << "\n直线到原点距离为" << get_0_distance1[i] << endl;
line(image_copy_C3, Point(l[0], l[1]), Point(l[2], l[3]), Scalar(g_rng.uniform(0, 255), g_rng.uniform(0, 255), g_rng.uniform(0, 255)), 2, LINE_AA);
float line_k;
int a;
a = lines[i][2] - lines[i][0];
cout << "\n直线斜率的参数" << a << endl;
if (fabs((double)(lines[i][2] - lines[i][0]))>0.001)
{
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" << 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>70 && (lines[i][1]<60 || lines[i][3]<60) &&fabs(line_k)>1.414)
{
lines_final.push_back(lines[i]);
}
}
else
{
if (zhixian_changdu>70 && (lines[i][1] < 60 || lines[i][3] < 60))
{
lines_final.push_back(lines[i]);
}
}
}
//Scalar color = Scalar(g_rng.uniform(0, 255), g_rng.uniform(0, 255), g_rng.uniform(0, 255));//随机设置颜色
Point pt1, pt2;
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, fangcheng_PARAM_2;
float theta, A_top_diatance, B_bottom_diatance;
//最终只能检测出两条直线
if (lines_final.size() == 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(g_rng.uniform(0, 255), g_rng.uniform(0, 255), g_rng.uniform(0, 255)), 2, LINE_AA);
}
//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);
fangcheng_PARAM_2 = get_lines_yibanshi_fangcheng_2((Point2f)A_top, (Point2f)B_bottom);
Param_A1 = (fangcheng_PARAM_1[0] + fangcheng_PARAM_1[3]) / 2.0;
Param_B1 = (fangcheng_PARAM_1[1] + fangcheng_PARAM_1[4]) / 2.0;
Param_C1 = (fangcheng_PARAM_1[2] + fangcheng_PARAM_1[5]) / 2.0;
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*****/
draw_line(Param_A1, Param_B1, Param_C1, 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
A_top_diatance = getDist_P2L_zhengfu_2(A_top, Param_A1, Param_B1, Param_C1);
B_bottom_diatance = getDist_P2L_zhengfu_2(B_bottom, Param_A1, Param_B1, Param_C1);
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 << "挡板顶部中点与白色过道中轴线误差为： " << A_top_diatance << endl;
cout << "挡板底部中点与白色过道中轴线误差为： " << B_bottom_diatance << endl;
}
else
{
cout << "没有正确的找到最终的两条直线" << endl;
continue;
}
//【6】边缘检测后的图
//namedWindow("【边缘检测后的图】", 0);//参数为零，则可以自由拖动
//imshow("【边缘检测后的图】", midImage);
namedWindow("直线未滤除前", 0);
imshow("直线未滤除前", image_copy_C3);
waitKey(1);
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(10);
}
}
//
//void Open_dicitie(void)
//{
// char Forward_flag = 4;//打开电磁铁
// int error1 = 0, error2 = 0, text = 0;
// text = error1 + error2 + Forward_flag;
// char g_UartRxBuffer[8] = { 123, -122, -121, 120, Forward_flag, (char)error1, (char)error2, (char)text };//针头（4），1个数据，一个验证
// WriteChar(g_UartRxBuffer, 8);//可以自行设置分部发送
//}
//
//
//
//
//Mat frame1; //全局变量前方摄像头图像
//Mat frame2; //全局变量顶部摄像头图像
//
//
//VideoCapture capcap_2(2); //顶部 摄像头
//VideoCapture capcap_1(1); //前方摄像头
//
//int main()
//{
//
// capcap_2.set(CAP_PROP_FRAME_WIDTH, 1280.0);//设置摄像头采集图像分辨率
// capcap_2.set(CAP_PROP_FRAME_HEIGHT, 720.0);
//
//
//
// capcap_1.set(CAP_PROP_FRAME_WIDTH, 1280.0);//设置摄像头采集图像分辨率
// capcap_1.set(CAP_PROP_FRAME_HEIGHT, 720.0);
//
// if (!capcap_2.isOpened())return 0;
// if (!capcap_1.isOpened())return 0;
//
//
// Ready_Pic();
//
//
// //Catch_chess();
// //Go_to_Number(27);
// //Put_chess(35);
//
// //第一块挡板
// Open_dicitie();
// Sleep(1200); //程序挂起两秒
// Sleep(1200); //程序挂起两秒
// Go_to_Number(35, 0);
// cout << "开始放置第一块挡板" << endl;
// Put_Dangban(35, 0);
// cout << "第一块挡板放置成功" << endl;
// Sleep(2200); //程序挂起两秒
//
// Go_to_Home();
//
//
//
// //第二块挡板
// Go_to_Number(35, 1);
// cout << "开始放置第二块挡板" << endl;
// Put_Dangban(35, 1);
// cout << "第二块挡板放置成功" << endl;
// //Sleep(2200); //程序挂起两秒
// Sleep(2200); //程序挂起两秒
// //Sleep(1200); //程序挂起两秒
// Go_to_Home();
//
// 第三块挡板
// Go_to_Number(28, 0);
// cout << "开始放置第三块挡板" << endl;
// Put_Dangban(28, 0);
// cout << "第三块挡板放置成功" << endl;
// Sleep(2200); //程序挂起两秒
// Sleep(2200); //程序挂起两秒
// Sleep(1200); //程序挂起两秒
// Go_to_Home();
//
// //第四块挡板
//
// Go_to_Number(36, 1);
// cout << "开始放置第四块挡板" << endl;
// Put_Dangban(36, 1);
// cout << "第四块挡板放置成功" << endl;
// Sleep(2200); //程序挂起两秒
// Sleep(2200); //程序挂起两秒
// Sleep(1200); //程序挂起两秒
// Go_to_Home();
//
//
// //第五块 挡板
// Go_to_Number(37, 0);
// cout << "开始放置第五块挡板" << endl;
// Put_Dangban(37, 0);
// cout << "第五块挡板放置成功" << endl;
// Sleep(2200); //程序挂起两秒
// Sleep(2200); //程序挂起两秒
// Sleep(1200); //程序挂起两秒
//
//
//
//
// //最终退场
// //1、后退20cm左右，
// for (int i = 0; i <2; i++)
// {
// char Forward_flag2 = -1;//发送开环后退指令
// char g_UartRxBuffer1[8] = { 123, -122, -121, 120, Forward_flag2, (char)(0), (char)(0), (char)Forward_flag2 };//针头（4），1个数据，一个验证
// WriteChar(g_UartRxBuffer1, 8);
// }
// Sleep(1200); //程序挂起两秒
// Sleep(1200); //程序挂起两秒
// Sleep(1200); //程序挂起两秒
//
// //3、转向180度
// for (int i = 0; i <2; i++)
// {
// char Forward_flag2 = 18;//发送开环后退指令
// char g_UartRxBuffer1[8] = { 123, -122, -121, 120, Forward_flag2, (char)(0), (char)(0), (char)Forward_flag2 };//针头（4），1个数据，一个验证
// WriteChar(g_UartRxBuffer1, 8);
// }
// Sleep(1200); //程序挂起两秒
// Sleep(2200); //程序挂起两秒
// Sleep(2200); //程序挂起两秒
// //3、前进
// for (int i = 0; i <4; i++)
// {
// char Forward_flag2 = 1;//发送开环后退指令
// char g_UartRxBuffer1[8] = { 123, -122, -121, 120, Forward_flag2, (char)(0), (char)(0), (char)Forward_flag2 };//针头（4），1个数据，一个验证
// WriteChar(g_UartRxBuffer1, 8);
// }
// Sleep(1200); //程序挂起两秒
// Sleep(1200); //程序挂起两秒
// Sleep(1200); //程序挂起两秒
//
// //3、停止
// for (int i = 0; i <4; i++)
// {
// char Forward_flag2 = 0;//发送开环后退指令
// char g_UartRxBuffer1[8] = { 123, -122, -121, 120, Forward_flag2, (char)(0), (char)(0), (char)Forward_flag2 };//针头（4），1个数据，一个验证
// WriteChar(g_UartRxBuffer1, 8);
// }
// Sleep(1200); //程序挂起两秒
// Sleep(1200); //程序挂起两秒
// Sleep(1200); //程序挂起两秒
//
// printf("Finish!");
// waitKey(0);
// return 0;
//}
