opencv矩形轮廓顶点的具体位置确定的两种实现方法

#cnt:输入轮廓，angle:返回角度
(x,y),(MA,ma),angle = cv2.fitEllipse(cnt)

#找轮廓最小矩 cnt:轮廓  box:4个点无规律
rect = cv2.minAreaRect(cnt)
box = cv2.boxPoints(rect)

import numpy as np
import cv2
def get4points(img: np.ndarray, thed, n):
    """
    :param img  the color image which shape is [height, width, depth]
    :return 4 point locations in list or tuple, for example: [[x1, y1], [x2, y2], [x3, y3], [x4, y4]]
    """

    #灰度和二值化
    gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
    ret, binary = cv2.threshold(gray,thed,255,cv2.THRESH_BINARY)

    # 搜索轮廓
    contours, hierarchy = cv2.findContours(
        binary,
        cv2.RETR_LIST,
        cv2.CHAIN_APPROX_SIMPLE)

    #按轮廓长度选取需要轮廓
    len_list = []
    for i in range(len(contours)):
        len_list.append(len(contours[i]))

    #选第二长的
    sy = np.argsort(np.array(len_list))[-n]

    #寻找顶点
    sum_list = []
    dif_list = []
    for i in contours[sy]:
        sum = i[0][0]+i[0][1]
        sum_list.append(sum)
        dif_list.append(i[0][0]-i[0][1])

    id_lb = np.argsort(np.array(sum_list))
    id_lb2 = np.argsort(np.array(dif_list))
    lu_id , rd_id = id_lb[0] , id_lb[-1]
    ld_id , ru_id = id_lb2[0] , id_lb2[-1]

    points = np.array([contours[sy][lu_id][0],contours[sy][rd_id][0],contours[sy][ld_id][0],contours[sy][ru_id][0]])

    return points , contours , sy

def getpoints(binary: np.ndarray  , num: int ):
    # 搜索轮廓
    contours, hierarchy = cv2.findContours(
        binary,
        cv2.RETR_LIST,
        cv2.CHAIN_APPROX_SIMPLE)

    #按轮廓位置最左（x最小）选取
    x_list = []
    for i in contours:
        x_sum = 0
        for kk in i:
            x_sum += kk[0][0]
        x_av = x_sum/len(i)
        x_list.append(x_av)

    sy = np.argsort(np.array(x_list))[num]
    cnt = contours[sy]
    
    #找轮廓最小矩
    rect = cv2.minAreaRect(cnt)
    box = cv2.boxPoints(rect)

    return box , contours , sy

def findpoints(points):
    #区分矩形顶点位置
    point_y=sorted(points,key=lambda t:t[1])
    lu, ru =sorted(point_y[:2],key=lambda t:t[0])
    ld, rd =sorted(point_y[2:],key=lambda t:t[0])

    return [list(lu), list(ld), list(ru),list(rd)]

#展示顶点
def show_points(img , points):
    point_size = 8
    point_color = (0, 0, 255) # BGR
    thickness = 4 # 可以为 0 、4、8
    points_list = [tuple(i) for i in np.int32(points).reshape(-1,2)]
    for point in points_list:
        cv2.circle(img, point, point_size, point_color, thickness)
    img = cv2.resize(img,(808,808))
    cv2.imshow('img',img)
    cv2.waitKey(0)
    cv2.destroyAllWindows()
    # cv2.imwrite('dd.jpg',img)

#展示轮廓
def show_Contour(img , contours , sy):
    cv2.drawContours(img, contours , sy , (25, 254, 0), 4)
    img = cv2.resize(img,(808,808))
    cv2.imshow('img',img)
    cv2.waitKey(0)
    cv2.destroyAllWindows()
    # cv2.imwrite('mm.jpg',img)