main2.py

import cv2
import numpy as np

image_file = 'D:\REP\projects\drawing_text_recognition\images\sxema65-1.jpg'
img = cv2.imread(image_file)
crop_img = img[img.shape[0] - 1200:img.shape[0] - 470, img.shape[1] - 1200:img.shape[1]-200] #Вырезать определенную область
gray = cv2.cvtColor(crop_img, cv2.COLOR_BGR2GRAY)
ret, thresh = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY)
img_erode = cv2.erode(thresh, np.ones((3, 3), np.uint8), iterations=1)

# Get contours
contours, hierarchy = cv2.findContours(img_erode, cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)

output = crop_img.copy()

for idx, contour in enumerate(contours):
    (x, y, w, h) = cv2.boundingRect(contour)
    print("R", idx, x, y, w, h, cv2.contourArea(contour), hierarchy[0][idx])
    # hierarchy[i][0]: the index of the next contour of the same level
    # hierarchy[i][1]: the index of the previous contour of the same level
    # hierarchy[i][2]: the index of the first child
    # hierarchy[i][3]: the index of the parent
    if hierarchy[0][idx][3] == 0:
        cv2.rectangle(output, (x, y), (x + w, y + h), (0, 0, 255), 1)


cv2.imshow("Input", crop_img)
cv2.imshow("Enlarged", img_erode)
cv2.imshow("Output", output)
cv2.waitKey(0)