Python code for marking regions of interest in an image for OCR

Marking_ROI.py

# use this command to install open cv2
# pip install opencv-python

# use this command to install PIL
# pip install Pillow

import cv2
from PIL import Image

def mark_region(imagE_path):
    
    im = cv2.imread(image_path)

    gray = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY)
    blur = cv2.GaussianBlur(gray, (9,9), 0)
    thresh = cv2.adaptiveThreshold(blur,255,cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY_INV,11,30)

    # Dilate to combine adjacent text contours
    kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (9,9))
    dilate = cv2.dilate(thresh, kernel, iterations=4)

    # Find contours, highlight text areas, and extract ROIs
    cnts = cv2.findContours(dilate, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
    cnts = cnts[0] if len(cnts) == 2 else cnts[1]

    line_items_coordinates = []
    for c in cnts:
        area = cv2.contourArea(c)
        x,y,w,h = cv2.boundingRect(c)

        if y >= 600 and x <= 1000:
            if area > 10000:
                image = cv2.rectangle(im, (x,y), (2200, y+h), color=(255,0,255), thickness=3)
                line_items_coordinates.append([(x,y), (2200, y+h)])

        if y >= 2400 and x<= 2000:
            image = cv2.rectangle(im, (x,y), (2200, y+h), color=(255,0,255), thickness=3)
            line_items_coordinates.append([(x,y), (2200, y+h)])


    return image, line_items_coordinates

if we want to optimize this code:

import cv2
from PIL import Image
from pdf2image import convert_from_path

def mark_region(im):
gray = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY)
blur = cv2.GaussianBlur(gray, (9,9), 0)
thresh = cv2.adaptiveThreshold(blur, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY_INV, 11, 30)
kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (9,9))
dilate = cv2.dilate(thresh, kernel, iterations=4)
cnts = cv2.findContours(dilate, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)[0]
line_items_coordinates = []
for c in cnts:
area = cv2.contourArea(c)
x, y, w, h = cv2.boundingRect(c)
if y >= 600 and x <= 1000 and area > 10000:
image = cv2.rectangle(im, (x,y), (2200, y+h), color=(255,0,255), thickness=3)
line_items_coordinates.append([(x,y), (2200, y+h)])
elif y >= 2400 and x<= 2000:
image = cv2.rectangle(im, (x,y), (2200, y+h), color=(255,0,255), thickness=3)
line_items_coordinates.append([(x,y), (2200, y+h)])
return image, line_items_coordinates

poppler_path = r 'you should write poppler bin folder path '
pages = convert_from_path("you should write here pdf path", 480, poppler_path=poppler_path)

for i, page in enumerate(pages):
image_name = f"Deneme_{i}.JPEG"
page.save(image_name, "JPEG")
im = cv2.imread(image_name)
marked_image, coordinates = mark_region(im)
cv2.imwrite(f"Marked_{image_name}", marked_image)