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# Import packages
import time
import cv2
import numpy as np
import ddddocr
import pyautogui
from io import BytesIO

import pyscreenshot
import pyscreenshot as ImgCap

# Load the template image
template = cv2.imread('captcha_box.png', 0)  # replace with your template
w, h = template.shape[::-1]

# Instance
cls_ocr = ddddocr.DdddOcr()

while True:  # I assume it's an infinite loop here, if there is a specific condition you can modify it at True
    # Capturing full screen image
    img = pyscreenshot.grab()
    img.save('screenshot.png')
    screenshot = cv2.imread('screenshot.png', 0)

    # Template matching
    res = cv2.matchTemplate(screenshot, template, cv2.TM_CCOEFF_NORMED)
    threshold = 0.8  # adjust this value based on your requirement
    loc = np.where(res >= threshold)

    if np.any(loc[0]):  # if there is any match
        for pt in zip(*loc[::-1]):  # for each matching location
            # Define relative position and new size
            offset_x = 60  # adjust this value based on your requirement
            offset_y = 45  # adjust this value based on your requirement
            new_w = 260  # adjust this value based on your requirement
            new_h = 85  # adjust this value based on your requirement8

            # Capturing image in the matched area with relative position
            bbox = (pt[0] + offset_x, pt[1] + offset_y, pt[0] + offset_x + new_w, pt[1] + offset_y + new_h)
            cls_img = pyscreenshot.grab(bbox=bbox)
            cls_img.save('screenshot.png')

            # Doing OCR
            try:
                # Convert PIL image to BytesIO
                cls_img_bytes = BytesIO()
                cls_img.save(cls_img_bytes, format='PNG')  # You are using the PIL Image object cls_img here
                cls_img_bytes = cls_img_bytes.getvalue()

                ret = cls_ocr.classification(cls_img_bytes)  # OCR classification
                print(f"ret = {ret}")  # Debug output
                time.sleep(0.5)  # Avoid 'Watch Dog' problem

                # Typing OCR result
                pyautogui.typewrite(ret)  # type out the result
                time.sleep(0.5)  # simulate the interval of human typing
                pyautogui.press('enter')  # press 'Enter'
            except:
                print("An exception occurred")

    # Waiting some time
    time.sleep(3)