1.minAreaRect(points)

官方解釋：

minAreaRect(points) -> retval
.   @brief Finds a rotated rectangle of the minimum area enclosing the input 2D point set.
.   
.   The function calculates and returns the minimum-area bounding rectangle (possibly rotated) for a
.   specified point set. Developer should keep in mind that the returned RotatedRect can contain negative
.   indices when data is close to the containing Mat element boundary.
.   
.   @param points Input vector of 2D points, stored in std::vector\<\> or Mat
 

輸入時2D點集，返回該點集區域的最小旋轉矩陣

角度是[-90,0)當矩形是水平或者垂直的時候都返回-90.矩形的長和寬並不是按照長度定義的，而是與水平夾角小於90度為width，另一條邊為height。 逆時針為負，順時針為正

2.boxPoints

根據minAreaRect的返回值計算矩形的四個點

import cv2 as cv
import numpy as np
img = cv.imread("./data/minAreaRect.png",0)

# 這裡型別做了轉換 要注意
coords = np.column_stack(np.where(img < 100))  # np.where返回下標，np.colunm_stack類似做了轉制(這裡沒有按順序做zip,所以是x,y)
coords=coords[:,[-1,-2]]  # 轉換成(x,y)

# b=tuple(map(tuple, coords))  # 檢視獲得座標是否正確
# for i in range(len(b)):
#     cv.circle(img,b[i],1,[0,255,0])

rect = cv.minAreaRect(coords)  # 獲得中心，長寬，角度
box = cv.boxPoints(rect)

center = rect[0]
center = (int(rect[0][0]),int(rect[0][1]))
cv.circle(img,center,3,[0,255,0])  # 繪製中心

a = tuple(map(tuple, box))  # 轉元組的方法
for i in range(len(a)):  # 繪製四個頂點
    cv.circle(img,a[i],3,[0,255,0])

cv.imshow("1",img)
k = cv.waitKey(0)  # 無限等待一個鍵擊，將此鍵擊存在k變數中
if k == 27:         # 27代表esc，可以檢視ascii碼錶
    cv.destroyAllWindows()  # 退出視窗