你是一个计算机网络方面的专家，ping ip地址，出现下面的错误，是什么问题？banma-1750 :: ~ » ping 172.20.243.149 ping: socktype: SOCK_RAW ping: socket: 不允许的操作 ping: => missing cap_net_raw+p capability or setuid?

根据您提供的错误信息，"ping: socktype: SOCK_RAW" 表示使用了错误的套接字类型。而 "ping: socket: 不允许的操作" 则表示执行了不允许的操作。最后的 "ping: => missing cap_net_raw+p capability or setuid?" 则是指缺少了 cap_net_raw+p 的权限或 setuid 设置。

这些错误提示表明您可能没有足够的权限来执行原始套接字（raw socket）操作，或者您的用户权限不正确。可以尝试以管理员权限运行该命令，或者联系系统管理员以获取更多帮助。

相关问题

FileNotFoundError: [WinError 3] 系统找不到指定的路径。: 'C:\\Users\\86152\\Desktop\\b\\banmati\\banma'要怎么解决

当出现路径错误时，可以尝试以下三种方法解决问题：

方法一：检查路径是否正确
首先，确保路径是正确的。在你提供的例子中，路径是'C:\\Users\\86152\\Desktop\\b\\banmati\\banma'。请确保该路径存在，并且没有拼写错误。你可以手动检查路径是否正确，或者使用`os.path.exists()`函数来验证路径是否存在。

方法二：使用绝对路径
如果你确定路径是正确的，但仍然出现错误，可以尝试使用绝对路径而不是相对路径。绝对路径是从根目录开始的完整路径，而相对路径是相对于当前工作目录的路径。使用绝对路径可以确保程序能够正确找到文件或目录。

方法三：检查文件权限
如果路径正确且使用绝对路径仍然出现错误，可能是由于文件权限问题导致的。请确保你有足够的权限来访问该文件或目录。你可以尝试以管理员身份运行程序，或者检查文件或目录的权限设置。

以下是三种解决路径错误的方法，请根据你的具体情况选择适合的方法进行尝试。

将此代码全部转换成python-opencv的形式，并且不删减任何部分，通俗易懂。

将 C++ 代码转换为 Python 代码涉及一些语法和库函数的调整。以下是完整的 Python 版本的代码，保留了原有的逻辑和功能：

import cv2
import numpy as np
import math

# 定义常量
jifen = 5
daodianju = 3
feichezhanbi = 0.73
yuanhuanyuzhi = 40
yuanhuanjingdu = 10
kuanzeng = 90
kuanzeng2 = 70
CAMERA_H = 60
CAMERA_W = 94
OUT_H = 60
OUT_W = 94

# 全局变量
shiziji = 0
banmasign = 0
imgSour = None

class Up:
    def __init__(self):
        self.dian = cv2.Point()
        self.que = 0

# 图片或视频二值化（动态阈值）
def er_zhi(imgxiu):
    imgCvt = cv2.cvtColor(imgxiu, cv2.COLOR_BGR2GRAY)
    imgTemp = cv2.GaussianBlur(imgCvt, (5, 5), 0)
    _, imgThr = cv2.threshold(imgTemp, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)
    cv2.imshow("二值化", imgThr)
    return imgThr

# 画出赛道两侧线和中线
def che_dao_xian(imgEr):
    global shiziji, banmasign, imgSour
    imgCan = imgDil = None
    shizipan = 0
    yuanhuanzuosign = 0
    yuanhuanyousign = 0
    yuanhuan = []
    banmapan = 0
    banmasign = 0
    banmadi = [0, 0, 0]
    banmashang = [0, 0, 0]
    high = int(imgEr.shape[0] * feichezhanbi)

    # 获取每一列白色点数据
    lieBais = [0] * imgEr.shape[1]
    for x in range(imgEr.shape[1]):
        for y in range(high - 1, -1, -1):
            if imgEr[y, x] != 0:
                lieBais[x] += 1
            else:
                break
        if x > 0 and abs(lieBais[x] - lieBais[x - 1]) >= 60:
            banmasign += 1
    if banmasign >= 6:
        banmapan = 1

    # 左右寻最长白条
    maxzuo = [0, 0]
    maxyou = [0, 0]
    for a in range(len(lieBais)):
        if lieBais[a] > maxzuo[1]:
            maxzuo[0] = a
            maxzuo[1] = lieBais[a]
    for a in range(len(lieBais) - 1, -1, -1):
        if lieBais[a] > maxyou[1]:
            maxyou[0] = a
            maxyou[1] = lieBais[a]

    # 找车道线
    chushi = 0
    chuju = 0
    shiziZuox = 0
    shiziZuoy = 0
    shiziYoux = 0
    zuoDao = []
    youDao = []
    zhongXian = []

    for y in range(high - 1, high - maxzuo[1], -1):
        zuox = maxzuo[0]
        for x in range(maxzuo[0], -1, -1):
            if imgEr[y, x] != 0 and imgEr[y, x - 1] == 0:
                if len(zuoDao) >= 1:
                    if abs(x - zuoDao[-1].dian.x) <= daodianju and abs(y - zuoDao[-1].dian.y) <= daodianju:
                        zuoDao.append(Up())
                        zuoDao[-1].dian = cv2.Point(x, y)
                        zuoDao[-1].que = 0
                        zuox = x
                        if banmapan == 1:
                            banmapan = 2
                        break
                else:
                    zuox = x
                    zuoDao.append(Up())
                    zuoDao[-1].dian = cv2.Point(x, y)
                    zuoDao[-1].que = 0
                    break
            elif imgEr[y, x] != 0 and imgEr[y, x - 1] != 0 and imgEr[y, x - 2] != 0:
                shiziZuox += 1
            if x - 3 == 0:
                break

        tempx = maxyou[0] - 4
        for x in range(maxyou[0] - 4, imgEr.shape[1]):
            if imgEr[y, x] != 0 and imgEr[y, x + 1] == 0:
                if len(youDao) >= 1:
                    if abs(x - youDao[-1].dian.x) <= daodianju and abs(y - youDao[-1].dian.y) <= daodianju:
                        youDao.append(Up())
                        youDao[-1].dian = cv2.Point(x, y)
                        youDao[-1].que = 0
                        tempx = x
                        break
                else:
                    tempx = x
                    youDao.append(Up())
                    youDao[-1].dian = cv2.Point(x, y)
                    youDao[-1].que = 0
                    break
            elif imgEr[y, x] != 0 and imgEr[y, x + 1] != 0 and imgEr[y, x + 2] != 0:
                shiziYoux += 1
            if x + 3 == imgEr.shape[1] - 1:
                break

        if imgEr.shape[1] - tempx >= 80:
            if banmapan == 2 and imgEr[y, tempx + 62] != 0 and imgEr[y, tempx + 63] != 0 and imgEr.shape[0] - maxzuo[1] <= 80:
                banmadi[0] = zuox
                banmadi[1] = tempx
                banmadi[2] = y
                banmapan = 3
        if chuju == 0:
            chuju = tempx - zuox
        if abs(shiziZuox - maxzuo[0]) <= 5 and abs(imgEr.shape[1] - maxyou[0] + 4 - shiziYoux) <= 5:
            shizipan = 1

    # 判断圆环存在否，及其位置
    if abs(len(zuoDao) - len(youDao)) >= yuanhuanyuzhi:
        ji1 = 0
        ji2 = 0
        signs = 0

        # 左圆环
        if len(zuoDao) < len(youDao):
            zuominx = 999999
            for n in range(len(zuoDao)):
                if zuominx > zuoDao[n].dian.x:
                    zuominx = zuoDao[n].dian.x
            for n in range(len(youDao)):
                signs = 0
                for x in range(youDao[n].dian.x, max(zuominx - 5, 1), -1):
                    if imgEr[youDao[n].dian.y, x] != 0 and imgEr[youDao[n].dian.y, x - 1] == 0:
                        if yuanhuanyousign == 1 and ji1 >= 5:
                            yuanhuanyousign = 2
                            yuanhuanweidian[1].x = youDao[n - 5].dian.x - kuanzeng
                            yuanhuanweidian[1].y = youDao[n - 5].dian.y
                            ji1 = 0
                        elif yuanhuanyousign == 3 and ji1 >= 5:
                            yuanhuanyousign = 4
                            ji1 = 0
                            break
                        signs = 1
                        ji1 += 1
                        ji2 = 0
                if signs == 0:
                    if yuanhuanyousign == 0 and ji2 >= 5:
                        yuanhuanyousign = 1
                        yuanhuanweidian[0].x = youDao[n - 5].dian.x - kuanzeng
                        yuanhuanweidian[0].y = youDao[n - 5].dian.y
                        ji2 = 0
                    elif yuanhuanyousign == 2 and ji2 >= 5:
                        yuanhuanyousign = 3
                        ji2 = 0
                    ji2 += 1
                    ji1 = 0

        # 右圆环
        else:
            youmaxx = 0
            for n in range(len(youDao)):
                if youmaxx < youDao[n].dian.x:
                    youmaxx = youDao[n].dian.x
            for n in range(len(zuoDao)):
                signs = 0
                for x in range(zuoDao[n].dian.x, youmaxx):
                    if imgEr[zuoDao[n].dian.y, x] != 0 and imgEr[zuoDao[n].dian.y, x + 1] == 0:
                        if yuanhuanzuosign == 1 and ji1 >= yuanhuanjingdu:
                            yuanhuanzuosign = 2
                            yuanhuanweidian[1].x = zuoDao[n - 5].dian.x + kuanzeng2
                            yuanhuanweidian[1].y = zuoDao[n - 5].dian.y
                            ji1 = 0
                        elif yuanhuanzuosign == 3 and ji1 >= yuanhuanjingdu:
                            yuanhuanzuosign = 4
                            ji1 = 0
                            break
                        signs = 1
                        ji1 += 1
                        ji2 = 0
                if signs == 0:
                    if yuanhuanzuosign == 0 and ji2 >= yuanhuanjingdu:
                        yuanhuanzuosign = 1
                        yuanhuanweidian[0].x = zuoDao[n - 5].dian.x + kuanzeng2 + 10
                        yuanhuanweidian[0].y = zuoDao[n - 5].dian.y
                        ji2 = 0
                    elif yuanhuanzuosign == 2 and ji2 >= yuanhuanjingdu:
                        yuanhuanzuosign = 3
                        ji2 = 0
                    ji2 += 1
                    ji1 = 0

    # 十字判断
    if shizipan:
        shiziji += 1
    if shiziji >= 3:
        shiziji = 0
        cv2.putText(imgSour, "CROSS", (10, 40), cv2.FONT_HERSHEY_COMPLEX, 0.7, (0, 0, 255), 2)

    # 斑马线判断
    if banmapan == 3:
        cv2.putText(imgSour, "BANMA_WIRES", (10, 40), cv2.FONT_HERSHEY_COMPLEX, 0.7, (0, 0, 255), 2)
        cv2.line(imgSour, (banmadi[0], banmadi[2]), (banmadi[1], banmadi[2]), (255, 0, 255), 3.5)

    # 圆环判断
    if yuanhuanzuosign == 4:
        cv2.putText(imgSour, "right circular", (10, 40), cv2.FONT_HERSHEY_COMPLEX, 0.7, (0, 0, 255), 2)
        for n in range(2):
            cv2.line(imgSour, (imgEr.shape[1] - 1, yuanhuanweidian[n].y), (yuanhuanweidian[n].x, yuanhuanweidian[n].y), (255, 0, 255), 3.5)
    elif yuanhuanyousign == 4:
        cv2.putText(imgSour, "left circular", (10, 40), cv2.FONT_HERSHEY_COMPLEX, 0.7, (0, 0, 255), 2)
        for n in range(2):
            cv2.line(imgSour, (0, yuanhuanweidian[n].y), (yuanhuanweidian[n].x, yuanhuanweidian[n].y), (255, 0, 255), 3.5)

    # 找中线
    sizes = min(len(zuoDao), len(youDao))
    bestZhongxian = []
    niheZhongxian = []
    kai = 0
    zhongx = 0
    zhongy = 0
    for n in range(sizes):
        if zuoDao[n].que == 0 and youDao[n].que == 0:
            zhongx = (zuoDao[n].dian.x + youDao[n].dian.x) // 2
            zhongy = (zuoDao[n].dian.y + youDao[n].dian.y) // 2
            if kai == 0:
                zhongXian.append(Up())
                zhongXian[-1].dian = cv2.Point(zhongx, zhongy)
                zhongXian[-1].que = 0
                kai = 1
            elif abs(zhongx - zhongXian[-1].dian.x) <= daodianju and abs(zhongy - zhongXian[-1].dian.y) >= 2:
                zhongXian.append(Up())
                zhongXian[-1].dian = cv2.Point(zhongx, zhongy)
                zhongXian[-1].que = 0

    # 最小二乘法拟合中线
    for c in range(0, len(zhongXian), jifen):
        if c + jifen >= len(zhongXian):
            break
        aa = bb = xx = yy = xy = xfangs = 0
        for n in range(c, c + jifen):
            xy += zhongXian[n].dian.x * zhongXian[n].dian.y
            xfangs += zhongXian[n].dian.x ** 2
            xx += zhongXian[n].dian.x
            yy += zhongXian[n].dian.y
        xx /= jifen
        yy /= jifen
        bb = (xy - jifen * xx * yy) / (xfangs - jifen * xx ** 2)
        aa = yy - bb * xx

        zuomin = 999999
        zuomax = 0
        youmin = 999999
        youmax = 0
        for n in range(c, c + jifen):
            if zuomin > zuoDao[n].dian.x:
                zuomin = zuoDao[n].dian.x
            if zuomax < zuoDao[n].dian.x:
                zuomax = zuoDao[n].dian.x
        for n in range(c, c + jifen):
            if youmin > youDao[n].dian.x:
                youmin = youDao[n].dian.x
            if youmax < youDao[n].dian.x:
                youmax = youDao[n].dian.x
        for x in range(zuomin, youmax + 1):
            y = int(bb * x + aa)
            if y <= zhongXian[c].dian.y and y >= zhongXian[c + jifen].dian.y and abs(x - (zuomin + youmax) / 2) <= 3:
                niheZhongxian.append(cv2.Point(x, y))

    # 拟合中线
    for n in range(len(niheZhongxian) - 1):
        cv2.line(imgSour, niheZhongxian[n], niheZhongxian[n + 1], (0, 255, 0), 4)

    # 原始中线
    for n in range(len(zhongXian) - 1):
        cv2.circle(imgSour, zhongXian[n].dian, 2, (0, 255, 0), -1)
        cv2.line(imgSour, zhongXian[n].dian, zhongXian[n + 1].dian, (0, 255, 0), 4)

    # 画出车道线
    for n in range(len(zuoDao)):
        cv2.circle(imgSour, zuoDao[n].dian, 2, (255, 0, 0), -1)
    for n in range(len(youDao)):
        cv2.circle(imgSour, youDao[n].dian, 2, (0, 0, 255), -1)

    return imgSour

# 逆透视
def ni_tou():
    angle = 0.8
    dep = 3.8
    prop_j = 1
    prop_i = 0
    j_large = 1.6
    i_abodon = 7
    hight = 50

    sin_a = math.sin(angle)
    cos_a = math.cos(angle)

    # 初始化摄像头坐标系
    map_square = np.zeros((CAMERA_H, CAMERA_W, 2), dtype=np.float32)
    for i in range(CAMERA_H):
        for j in range(CAMERA_W):
            map_square[i, j, 0] = (CAMERA_H / 2 - i + 0.5) / 10
            map_square[i, j, 1] = (j - CAMERA_W / 2 + 0.5) / 10

    # 横向拉伸
    for i in range(CAMERA_H):
        for j in range(CAMERA_W):
            map_square[i, j, 1] = map_square[i, j, 1] * (1 * (CAMERA_H - 1 - i) + (1 / prop_j) * i) / (CAMERA_H - 1)

    # 逆透视变换
    for i in range(CAMERA_H):
        for j in range(CAMERA_W):
            xg = map_square[i, j, 1]
            yg = map_square[i, j, 0]
            y0 = (yg * dep + hight * cos_a * yg + hight * dep * sin_a) / (dep * cos_a - yg * sin_a)
            zt = -y0 * sin_a - hight * cos_a
            x0 = xg * (dep - zt) / dep
            map_square[i, j, 1] = x0
            map_square[i, j, 0] = y0

    # 横坐标缩放
    prop_x = (OUT_W - 1) / (map_square[i_abodon, CAMERA_W - 1, 1] - map_square[i_abodon, 0, 1])
    for i in range(CAMERA_H):