作为一个OCR新手，我试图检测扫描文档中的所有矩形/框，如x1c 0d1x所示
然而，下面提供的代码片段的输出无法从图像中识别相当多的矩形。

import cv2
import imutils
import warnings
import numpy as np

warnings.filterwarnings('ignore')
import matplotlib.pyplot as plt

img = cv2.imread("example.jpg") 
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

threshold = cv2.adaptiveThreshold(
    gray.copy(), 
    255, # maximum value assigned to pixel values exceeding the threshold
    cv2.ADAPTIVE_THRESH_GAUSSIAN_C,  # gaussian weighted sum of neighborhood
    cv2.THRESH_BINARY_INV,  # thresholding type 
    301, # block size (5x5 window)
    21) # constant

font = cv2.FONT_HERSHEY_COMPLEX
keypoints = cv2.findContours(threshold.copy(), 
                             cv2.RETR_CCOMP, 
                             cv2.CHAIN_APPROX_SIMPLE)
contours = imutils.grab_contours(keypoints)
working_image = None
idx = 1
cropped_field_images = []

contour_list = list(contours)
contour_list.reverse()
rev_contours = tuple(contour_list)

for contour in rev_contours:   
    x,y,w,h = cv2.boundingRect(contour) 
    area = cv2.contourArea(contour)
    approx = cv2.approxPolyDP(contour, 10, True)
    location = None
    if len(approx) == 4 and area > 1500 : #if the shape size is rectangular
        working_image = cv2.rectangle(img,(x,y),(x+w,y+h),(0,255,0),2)   
        cv2.putText(img, str(idx), (x, y), font, 1, (0,0,255))
        
        location = approx
        mask = np.zeros(gray.shape, np.uint8) #Create a blank mask
        rect_img = cv2.drawContours(mask, [location], 0, 255, -1) 
        rect_img = cv2.bitwise_and(img, img, mask = mask) 
        
        (x, y) = np.where(mask==255)
        (x1, y1) = (np.min(x), np.min(y))
        (x2, y2) = (np.max(x), np.max(y))
        cropped_rect = gray[x1:x2+1, y1:y2+1]
        
        cropped_field_images.append(cropped_rect)
        
        idx += 1
    
plt.figure(figsize = (11.69*2,8.27*2))
plt.axis('off')
plt.imshow(cv2.cvtColor(working_image, cv2.COLOR_BGR2RGB));

上面的代码的结果是下面的图片。任何左上角没有数字和绿色边界的矩形都不能被上面的代码识别，并被标记为红色星星。我在上面的代码片段中尝试改变opencv 2自适应阈值的类型，块大小和常量，但这些红色星号的矩形总是从输出结果中被忽略。

我错过了什么？我可以考虑什么来确保这些框/区域不会在结果中被忽略？任何优化自适应阈值以确保所有红色星号矩形部分都包含在输出结果中的帮助都将不胜感激。