Python code to replace string on image with randomly generated string with proper fusion [closed]

def generate_random_string(input_string):
    random_string = ""
    for char in input_string:
        if char.isalpha() and char.isupper():
            random_string += random.choice('ABCDEFGHIJKLMNOPQRSTUVWXYZ')
        elif char.isalpha() and char.islower():
            random_string += random.choice('abcdefghijklmnopqrstuvwxyz')
        elif char.isdigit():
            random_string += random.choice('0123456789')
        else:
            random_string += ' '
    return random_string


def generate_random_dict(original_dict):
    new_dict = {}
    for key, value in original_dict.items():
        new_key = generate_random_string(key)
        new_dict[new_key] = value
    return new_dict

def get_word_bounding_boxes(image_path):
    image =  cv2.imread(image_path)
    # Initialize PaddleOCR with specified languages and model
    ocr = PaddleOCR(lang="en")  # You can adjust the language and GPU usage
    # Preprocess the image (resizing and grayscale conversion)
    resized_image = cv2.resize(image, (0, 0), fx=1.0, fy=1.0)  # Resize for better accuracy
    gray_image = cv2.cvtColor(resized_image, cv2.COLOR_BGR2GRAY)  # Convert to grayscale
    show_img(gray_image)
    # Perform OCR using PaddleOCR on the preprocessed image
    result = ocr.ocr(gray_image)
    # Process the OCR output and extract bounding boxes for each word
    word_bounding_boxes = {}
    for line in result:
        for word_info in line:
            word = word_info[1][0]
            box = word_info[0]
            if len(word) > 1:
                x_min, y_min, x_max, y_max = box[0][0], box[0][1], box[2][0], box[2][1]
                word_bounding_boxes[word] = [int(x_min)-1, int(y_min)-1,int(x_max)+1,int(y_max)+1]
    return word_bounding_boxes