Selecting ROI on video and tracking movement in the selected area. OpenCV\Python

Question

I ran into an error. I need to track motion in a specific area of a video. But when I try to crop a frame using ROI or a rectangle, Python throws the following error:

Traceback (most recent call last): File "C:\Users\Nitro 5\Desktop\sad.py", line 22, in diff = cv2.absdiff(frame1, frame2) cv2.error: OpenCV(4.6.0) D:\a\opencv-python\opencv-python\opencv\modules\core\src\arithm.cpp:650: error: (-209:Sizes of input arguments do not match) The operation is neither 'array op array' (where arrays have the same size and the same number of channels), nor 'array op scalar', nor 'scalar op array' in function 'cv::arithm_op'

I'm still a beginner, I tried to find something similar on the Internet, but nothing happened:( Can someone help me?

My code:

import cv2 
import imutils

cap = cv2.VideoCapture(0); 

#cap.set(3,1280)
#cap.set(4,700)

ret, frame1 = cap.read()
ret, frame2 = cap.read()

r = cv2.selectROI(frame1)
frame1 = frame1[int(r[1]):int(r[1]+r[3]), int(r[0]):int(r[0]+r[2])]

frame2 = frame2[int(r[1]):int(r[1]+r[3]), int(r[0]):int(r[0]+r[2])]



while cap.isOpened(): 


  diff = cv2.absdiff(frame1, frame2) 

  gray = cv2.cvtColor(diff, cv2.COLOR_BGR2GRAY) 

  blur = cv2.GaussianBlur(gray, (5, 5), 0) 

  _, thresh = cv2.threshold(blur, 20, 255, cv2.THRESH_BINARY) 

  dilated = cv2.dilate(thresh, None, iterations = 3) 

  сontours, _ = cv2.findContours(dilated, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE) 

  for contour in сontours:
    (x, y, w, h) = cv2.boundingRect(contour)

    if cv2.contourArea(contour) < 1000:
      continue
    cv2.rectangle(frame1, (x, y), (x+w, y+h), (0, 255, 0), 2) 
    cv2.putText(frame1, "Status: {}".format("Dvijenie is detected!"), (10, 20),     cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 3, cv2.LINE_AA)
    print('Motion Detection. Object area  - ',     cv2.contourArea(contour))
     
  cv2.imshow("WebCamera", frame1)
  frame1 = frame2  #
  ret, frame2 = cap.read()   

  if cv2.waitKey(1) == 27: 
    break


cap.release()
cv2.destroyAllWindows()