img1[hull[0, 0][1]:hull[0, 1][1], hull[0, 0][0]:hull[0, 3][0]] = dst IndexError: index 1 is out of bounds for axis 1 with size 1

这个错误通常是由于你要访问的数组中某个轴的大小小于你试图访问的索引值引起的。在这种情况下，你正在尝试访问一个大小为 1 的轴的第二个元素，这显然是不可能的。

可能的原因是你正在处理的数组形状不正确或者你正在使用的索引值有误。建议你检查一下数组和索引的形状是否符合你的预期，并且确保索引值是正确的。如果可以的话，你可以提供更多的代码和上下文，这样我可以更好地理解问题的本质，并提供更具体的建议。

相关问题

import cv2 import math def cal_ang(start, center, end): point_1 = start point_2 = center point_3 = end a = math.sqrt( (point_2[0] - point_3[0]) * (point_2[0] - point_3[0]) + (point_2[1] - point_3[1]) * (point_2[1] - point_3[1])) b = math.sqrt( (point_1[0] - point_3[0]) * (point_1[0] - point_3[0]) + (point_1[1] - point_3[1]) * (point_1[1] - point_3[1])) c = math.sqrt( (point_1[0] - point_2[0]) * (point_1[0] - point_2[0]) + (point_1[1] - point_2[1]) * (point_1[1] - point_2[1])) A = math.degrees(math.acos((a * a - b * b - c * c) / (-2 * b * c))) B = math.degrees(math.acos((b * b - a * a - c * c) / (-2 * a * c))) C = math.degrees(math.acos((c * c - a * a - b * b) / (-2 * a * b))) return B img = cv2.imread('46.png') gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY) ret,thresh = cv2.threshold(gray, 70, 255, cv2.THRESH_BINARY) contours,hierarchy=cv2.findContours(thresh,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_NONE) hull = cv2.convexHull(contours[0],returnPoints=False) defects = cv2.convexityDefects(contours[0],hull) start = end = (0,0) for i in range(0,defects.shape[0]): s,e,f,d = defects[i,0] start = tuple(contours[0][s][0]) end = tuple(contours[0][e][0]) far = tuple(contours[0][f][0]) if d > 5000: cv2.line(img,start,end,[0,255,0],2) cv2.circle(img,end,5,[0,0,255],-1) cv2.circle(img,start,5,[0,0,255],-1) break cv2.imshow('find', img) center,radius = cv2.minEnclosingCircle(contours[0]) cv2.circle(img,(int(center[0]),int(center[1])),8,(255,0,255),-1) cv2.circle(img,end,8,[255,0,0],-1) cv2.circle(img,start,8,[255,0,0],-1) cv2.line(img,start,(int(center[0]),int(center[1])),[0,0,255],2) cv2.line(img,end,(int(center[0]),int(center[1])),[0,0,255],2) angle = cal_ang(start,center,end) print('angle = %0.2f' % angle) length = (1 - angle / 360.0) * math.pi * radius * 2 print((angle / 360.0)) print('radius = %0.2f' % radius) strL = 'length=%0.2f' % length cv2.putText(img,strL,(int(center[0]-40),int(center[1]+40)),0,0.8,(0,255,0),2) cv2.imshow('result', img) angle_1 = cal_ang(start, center, ((center[0]+100),(center[1]))) angle_2 = cal_ang(end, center, ((center[0]+100),(center[1]))) cv2.ellipse(img,(int(center[0]),int(center[1])),(int(radius),int(radius)),0,-angle_1,0,(255,0,255),2, cv2.LINE_AA) cv2.ellipse(img,(int(center[0]),int(center[1])),(int(radius),int(radius)),0,0,angle_2,(255,0,255),2,cv2.LINE_AA) cv2.imshow('result', img) cv2.imwrite('result.png',img) cv2.waitKey(0) cv2.destroyAllWindows(),将这段代码转换为c++

以下是将Python代码转换为C++的结果。注意，由于数据类型和库函数的区别，代码可能需要进行微调才能正常运行。

#include <iostream>
#include <opencv2/opencv.hpp>
#include <math.h>

using namespace std;
using namespace cv;

double cal_ang(Point start, Point center, Point end) {
    Point2f point_1 = start;
    Point2f point_2 = center;
    Point2f point_3 = end;
    double a = sqrt(pow(point_2.x - point_3.x, 2) + pow(point_2.y - point_3.y, 2));
    double b = sqrt(pow(point_1.x - point_3.x, 2) + pow(point_1.y - point_3.y, 2));
    double c = sqrt(pow(point_1.x - point_2.x, 2) + pow(point_1.y - point_2.y, 2));
    double A = acos((a * a - b * b - c * c) / (-2 * b * c)) * 180 / CV_PI;
    double B = acos((b * b - a * a - c * c) / (-2 * a * c)) * 180 / CV_PI;
    double C = acos((c * c - a * a - b * b) / (-2 * a * b)) * 180 / CV_PI;
    return B;
}

int main() {
    Mat img = imread("46.png");
    Mat gray;
    cvtColor(img, gray, COLOR_BGR2GRAY);
    threshold(gray, gray, 70, 255, THRESH_BINARY);
    vector<vector<Point>> contours;
    vector<Vec4i> hierarchy;
    findContours(gray, contours, hierarchy, RETR_EXTERNAL, CHAIN_APPROX_NONE);
    vector<vector<Point>> hull(contours.size());
    vector<vector<int>> hullsI(contours.size());
    vector<vector<Vec4i>> defects(contours.size());
    convexHull(contours[0], hull[0], false);
    convexHull(contours[0], hullsI[0], false);
    if (hullsI[0].size() > 0) {
        Point2f* pts = new Point2f[hullsI[0].size()];
        for (size_t i = 0; i < hullsI[0].size(); i++) {
            pts[i] = contours[0][hullsI[0][i]];
        }
        int n = hullsI[0].size();
        convexityDefects(pts, n, hullsI[0], defects[0]);
        delete[] pts;
    }
    Point start, end;
    for (int i = 0; i < defects[0].size(); i++) {
        Vec4i& v = defects[0][i];
        int startidx = v[0];
        Point ptStart(contours[0][startidx]);
        int endidx = v[1];
        Point ptEnd(contours[0][endidx]);
        int faridx = v[2];
        Point ptFar(contours[0][faridx]);
        if (v[3] > 5000) {
            line(img, ptStart, ptEnd, Scalar(0, 255, 0), 2);
            circle(img, ptEnd, 5, Scalar(0, 0, 255), -1);
            circle(img, ptStart, 5, Scalar(0, 0, 255), -1);
            start = ptStart;
            end = ptEnd;
            break;
        }
    }
    Point2f center;
    float radius = 0;
    minEnclosingCircle(contours[0], center, radius);
    circle(img, center, 8, Scalar(255, 0, 255), -1);
    circle(img, end, 8, Scalar(255, 0, 0), -1);
    circle(img, start, 8, Scalar(255, 0, 0), -1);
    line(img, start, Point(center), Scalar(0, 0, 255), 2);
    line(img, end, Point(center), Scalar(0, 0, 255), 2);
    double angle = cal_ang(start, center, end);
    cout << "angle = " << angle << endl;
    double length = (1 - angle / 360.0) * CV_PI * radius * 2;
    cout << angle / 360.0 << endl;
    cout << "radius = " << radius << endl;
    stringstream ss;
    ss << "length=" << fixed << setprecision(2) << length;
    String strL = ss.str();
    putText(img, strL, Point(center.x - 40, center.y + 40), 0, 0.8, Scalar(0, 255, 0), 2);
    double angle_1 = cal_ang(start, center, Point(center.x + 100, center.y));
    double angle_2 = cal_ang(end, center, Point(center.x + 100, center.y));
    ellipse(img, center, Size(radius, radius), 0, -angle_1, 0, Scalar(255, 0, 255), 2, LINE_AA);
    ellipse(img, center, Size(radius, radius), 0, 0, angle_2, Scalar(255, 0, 255), 2, LINE_AA);
    imshow("result", img);
    imwrite("result.png", img);
    waitKey(0);
    destroyAllWindows();
    return 0;
}

cv2.line(img,tuple(hull[i][0]),tuple(hull[(i+1) % length][0]),(0,0,255),2)这段代码是什么意思

这段代码是使用OpenCV的cv2库在图像img上绘制一条红色的线段。具体来说，它使用了Convex Hull算法计算出一组点hull，然后将这些点按顺序两两相连，形成一个多边形，并在多边形的每条边上绘制红色线段。其中参数解释如下：

- tuple(hull[i][0])和tuple(hull[(i+1) % length][0])分别表示多边形的相邻两个顶点的坐标；
- (0,0,255)表示红色线段的颜色，由于OpenCV使用BGR而非RGB表示颜色，因此(0,0,255)表示红色，(255,0,0)表示蓝色，(0,255,0)表示绿色等；
- 2表示线段的宽度，即绘制的线段像素的宽度。