总是出现AttributeError: 'NoneType' object has no attribute 'copy'这个报错是为什么

椰椰荔枝糖 2020-10-29 08:28:53

import cv2 as cv

import numpy as np

import math





def findColor(src, min, max):

    '''

    描述：用于判断颜色识别基于HSV模式

    :param src:

    :param min:

    :param max:

    :return:

    '''

    src_image = cv.GaussianBlur(src, (9, 9), 0)

    hsv_image = cv.cvtColor(src_image, cv.COLOR_BGR2HSV)

    thresholded = cv.inRange(hsv_image, (min, 90, 90), (max, 255, 255))

    return thresholded





def angle(pt1, pt2, pt0):

    '''

    描述：用于求证正方形

    :param pt1:

    :param pt2:

    :param pt0:

    :return:

    '''

    dx1 = pt1[0][0] - pt0[0][0]

    dy1 = pt1[0][1] - pt0[0][1]

    dx2 = pt2[0][0] - pt0[0][0]

    dy2 = pt2[0][1] - pt0[0][1]

    # 边长平方的比

    ratio = (dx1 * dx1 + dy1 * dy1) / (dx2 * dx2 + dy2 * dy2)

    a = (dx1 * dx2 + dy1 * dy2) / math.sqrt((dx1 * dx1 + dy1 * dy1) * (dx2 * dx2 + dy2 * dy2) + 1e-10)

    # 根据边长平方的比过小或过大提前淘汰这个四边形，如果淘汰过多，调整此比例数字

    if ratio < 0.8 or 1.2 < ratio:

        # 根据边长平方的比过小或过大提前淘汰这个四边形

        return 1.0

    return a





def Graphicdetection(srcImage, CLImage, outImage, str):

    '''

    描述：用于识别和统计形状数量

    :param srcImage:

    :param CLImage:

    :param outImage:

    :param str:

    :return:

    '''

    bjImage = srcImage.copy()

    # 模糊降噪

    cv.GaussianBlur(CLImage, (9, 9), 0, CLImage, 0)

    # 边缘检测

    outImage = cv.Canny(CLImage, 10, 100)

    # 定义一个正方形计数器

    zfcount = 0

    # 定义一个三角形计数器

    sjcount = 0

    # 查找轮廓

    cloneImage,contours, hierarchy = cv.findContours(outImage, cv.RETR_EXTERNAL, cv.CHAIN_APPROX_NONE)

    for i in range(len(contours)):

        # 计算轮廓矩

        mu = cv.moments(contours[i], False)

        # 计算轮廓的质心

        cx = mu['m10'] / mu['m00']

        cy = mu['m01'] / mu['m00']

        # 画出中心点

        cv.circle(bjImage, (np.int(cx), np.int(cy)), 5, (0, 0, 0), -1, 8, 0)

        # 绘出多边形

        approx = cv.approxPolyDP(contours[i], cv.arcLength(contours[i], True) * 0.02, True)

        if len(approx) == 4 & np.int(math.fabs(cv.contourArea(approx))) > 1000 & cv.isContourConvex(approx):

            MaxCosine = 0

            for j in range(2, 5):

                # 正方形

                cosine = math.fabs(angle(approx[j % 4], approx[j - 2], approx[j - 1]))

                MaxCosine = np.maximum(MaxCosine, cosine)

            if MaxCosine < 0.3:

                jx = approx

                # 绘制出正方形边框

                cv.line(bjImage, (jx[0][0][0], jx[0][0][1]), (jx[1][0][0], jx[1][0][1]), (0, 0, 0), 3)

                cv.line(bjImage, (jx[1][0][0], jx[1][0][1]), (jx[2][0][0], jx[2][0][1]), (0, 0, 0), 3)

                cv.line(bjImage, (jx[2][0][0], jx[2][0][1]), (jx[3][0][0], jx[3][0][1]), (0, 0, 0), 3)

                cv.line(bjImage, (jx[3][0][0], jx[3][0][1]), (jx[0][0][0], jx[0][0][1]), (0, 0, 0), 3)

                tam = "Square " + str

                cv.putText(bjImage, tam, (np.int(cx), np.int(cy) - 10), cv.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 0))

                zfcount += 1

        # 三边形

        if len(approx) == 3:

            sjx = approx

            # 绘制出三角形边框

            cv.line(bjImage, (sjx[0][0][0], sjx[0][0][1]), (sjx[1][0][0], sjx[1][0][1]), (0, 0, 0), 3)

            cv.line(bjImage, (sjx[1][0][0], sjx[1][0][1]), (sjx[2][0][0], sjx[2][0][1]), (0, 0, 0), 3)

            cv.line(bjImage, (sjx[2][0][0], sjx[2][0][1]), (sjx[0][0][0], sjx[0][0][1]), (0, 0, 0), 3)

            tam = "Triangle " + str

            cv.putText(bjImage, tam, (np.int(cx), np.int(cy) - 10), cv.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 0))

            sjcount += 1

    # 霍夫检测圆

    circles = None

    # 霍夫圆检测

    circles = cv.HoughCircles(CLImage, cv.HOUGH_GRADIENT, 1.5, 10, circles, 200, 100, 0, 0)

    circles = np.uint16(np.around(circles))

    for i in circles[0, :]:

        radius = (i[2]);

        tam = "Round " + str

        cv.putText(bjImage, tam, (i[0], i[1] - 10), cv.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 0))

        cv.circle(bjImage, (i[0], i[1]), 3, (0, 0, 0), -1, 8, 0)

        # 绘制圆轮廓

        cv.circle(bjImage, (i[0], i[1]), radius, (0, 0, 0), 3, 8, 0)



    if str == "R":

        str = "红色"

        print("%s 正方形 有 %d 个" % (str, zfcount))

        print("%s 三角形 有 %d 个" % (str, sjcount))

        print("%s 圆     有 %d 个" % (str, len(circles)))

    if str == "G":

        str = "绿色"

        print("%s 正方形 有 %d 个" % (str, zfcount))

        print("%s 三角形 有 %d 个" % (str, sjcount))

        print("%s 圆     有 %d 个" % (str, len(circles)))

    if str == "Y":

        str = "黄色"

        print("%s 正方形 有 %d 个" % (str, zfcount))

        print("%s 三角形 有 %d 个" % (str, sjcount))

        print("%s 圆     有 %d 个" % (str, len(circles)))



    return bjImage





src = cv.imread("1.jpg")

dst = src.copy()



Rdst = findColor(src, 0, 25)

Gdst = findColor(src, 60, 80)

Ydst = findColor(src, 30, 50)[code=python]

RdstImage = Graphicdetection(src, Rdst, dst, "R")
GdstImage = Graphicdetection(src, Gdst, dst, "G")
YdstImage = Graphicdetection(src, Ydst, dst, "Y")

cv.imshow("Rdst", RdstImage)
cv.imshow("Gdst", GdstImage)
cv.imshow("Ydst", YdstImage)

cv.waitKey(0)
cv.destroyAllWindows()[/code]