minAreaRect()提供中心点、矩形的大小和Angular 。
你可以只增加矩形的短边长度，这样你就有了一个“更宽的矩形”的描述，然后你可以对它做任何你想做的事情，比如在它上面调用boxPoints()。

padding = 42

rect = cv.minAreaRect(input_to_min_area)

(center, (w,h), angle) = rect # take it apart

if w < h: # we don't know which side is longer, add to shorter side
    w += padding
else:
    h += padding

rect = (center, (w,h), angle) # rebuild

一个方框围绕着你的两个端点，加宽了：

我们可以在垂直于“minAreaRect”的Angular 的轴上添加填充。

• 获取Angular ，并转换为弧度

angle = np.deg2rad(rect[2])  # Angle of minAreaRect

• 每个方向上的填充都垂直于minAreaRect的Angular

pad_x = 20*np.sin(angle)
 pad_y = 20*np.cos(angle)

• 在两个轴上添加填充：

假设盒子中的点的顺序是根据rect的Angular 排序的（我不知道它是否总是正确的--可能需要对点进行排序）。

box[[0, 3], 0] -= pad_x
 box[[1, 2], 0] += pad_x
 box[[0, 3], 1] += pad_y
 box[[1, 2], 1] -= pad_y
 box = np.int0(box)

代码示例：

import cv2
import numpy as np

img = cv2.imread('sketch.png')

#input_to_min_area = np.array([[584, 147], [587, 502]]) # this works instead of contour as an input to minAreaRect
#input_to_min_area = np.array([[109, 515], [585, 144]]) # this works instead of contour as an input to minAreaRect
input_to_min_area = np.array([[80, 103], [590, 502]]) # this works instead of contour as an input to minAreaRect

rect = cv2.minAreaRect(input_to_min_area)
box = cv2.boxPoints(rect)

angle = np.deg2rad(rect[2])  # Angle of minAreaRect

# Padding in each direction is perpendicular to the angle of minAreaRect
pad_x = 20*np.sin(angle)
pad_y = 20*np.cos(angle)

box[[0, 3], 0] -= pad_x
box[[1, 2], 0] += pad_x
box[[0, 3], 1] += pad_y
box[[1, 2], 1] -= pad_y
box = np.int0(box)

cv2.drawContours(img, [box], 0, (0, 255, 255), 2)

cv2.imshow('img', img)
cv2.waitKey()
cv2.destroyAllWindows()

示例输出：

我们可能还想在平行方向上展开长方体。
我还是不确定那些迹象...
在这种情况下，更新input_to_min_area会更简单：

import cv2
import numpy as np

img = cv2.imread('sketch.png')

#input_to_min_area = np.array([[584, 147], [587, 502]]) # this works instead of contour as an input to minAreaRect
#input_to_min_area = np.array([[109, 515], [585, 144]]) # this works instead of contour as an input to minAreaRect
input_to_min_area = np.array([[80, 103], [590, 502]]) # this works instead of contour as an input to minAreaRect

rect = cv2.minAreaRect(input_to_min_area)

angle = np.deg2rad(rect[2])  # Angle of minAreaRect
pad_x = int(round(20*np.cos(angle)))
pad_y = int(round(20*np.sin(angle)))
tmp_to_min_area = np.array([[input_to_min_area[0, 0]+pad_x, input_to_min_area[0, 1]+pad_y], [input_to_min_area[1, 0]-pad_x, input_to_min_area[1, 1]-pad_y]])
rect = cv2.minAreaRect(tmp_to_min_area)

box = cv2.boxPoints(rect)

angle = np.deg2rad(rect[2])  # Angle of minAreaRect

# Padding in each direction is perpendicular to the angle of minAreaRect
pad_x = 20*np.sin(angle)
pad_y = 20*np.cos(angle)

box[[0, 3], 0] -= pad_x
box[[1, 2], 0] += pad_x
box[[0, 3], 1] += pad_y
box[[1, 2], 1] -= pad_y

box = np.int0(box)

cv2.drawContours(img, [box], 0, (0, 255, 255), 2)

cv2.line(img, (tmp_to_min_area[0, 0], tmp_to_min_area[0, 1]), (tmp_to_min_area[1, 0], tmp_to_min_area[1, 1]), (255, 0, 0), 2)

cv2.imshow('img', img)
cv2.waitKey()
cv2.destroyAllWindows()

输出量：