main.py

from PIL import ImageGrab
import numpy as np
import matplotlib.pyplot as plt
import cv2
import time
import pyautogui

print("launched")
time.sleep(2)

screenCapture_heigth = 200
screeCapture_width = 200
capturing = True

while(True):

    cursor_position_x, cursor_position_y = pyautogui.position()

    img = ImageGrab.grab(bbox=(cursor_position_x-screenCapture_heigth, cursor_position_y-screeCapture_width,
                               cursor_position_x+screenCapture_heigth, cursor_position_y+screeCapture_width))
    # bbox specifies specific region (bbox= x,y,width,height *starts top-left)

    # convert to opencv's format
    img_np = np.array(img)  # this is the array obtained from conversion
    frame = cv2.cvtColor(img_np, cv2.COLOR_BGR2GRAY)
    # note: generally, we use grayscale images for processing because this use lot less ressources

    cv2.imshow("screenCast", frame)

    if(cv2.waitKey(1) & 0xFF == ord('q')):  # -> press 'q' to quit
        break


cv2.destroyAllWindows()