你的方法有一些小缺陷，下面的代码将有所帮助。

代码：import numpy as np

import cv2

image = cv2.imread('C:/Users/Jackson/Desktop/score.jpg')

#--- Resized the image to half its dimension maintaining the aspect ratio ---

image = cv2.resize(image, (0, 0), fx = 0.5, fy = 0.5)

draw = np.zeros_like(image)

gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

#--- I found the inverse binary image, because contours are found for objects in white. Since the border of the page is in black you have to invert the binary image. This is where it went wrong.

ret, thresh = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY_INV|cv2.THRESH_OTSU)

#--- I did not perform any morphological operation ---

im, cnts, hier = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

max_area = -1

max_c = 0

for i in range(len(cnts)):

contour = cnts[i]

area = cv2.contourArea(contour)

if (area > max_area):

max_area = area

max_c = i

contour = cnts[max_c]

rect = cv2.minAreaRect(contour)

box = cv2.boxPoints(rect)

box = np.int0(box)

cv2.drawContours(image, [box],-1, (0, 255, 0), 2)

cv2.imshow('Sheet', image)

cv2.waitKey(0)

cv2.destroyAllWindows()

结果：

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