Как взаимодействовать только с заданной областью

import cv2
import numpy as np
import math
 
 
cap = cv2.VideoCapture(0)
while(cap.isOpened()):
    # read image
    ret, img = cap.read()
    hsv=cv2.cvtColor(img,cv2.COLOR_BGR2HSV)
    red_lower=np.array([136,87,111],np.uint8)
    red_upper=np.array([180,255,255],np.uint8)
    red=cv2.inRange(hsv, red_lower, red_upper)
    kernal = np.ones((5 ,5), "uint8")
    red=cv2.dilate(red, kernal)
    res=cv2.bitwise_and(img, img, mask = red)
    
    # get hand data from the rectangle sub window on the screen
    cv2.rectangle(img, (300,300), (100,100), (0,255,0),0)
    crop_img = img[100:300, 100:300]
 
    # convert to grayscale
    grey = cv2.cvtColor(res, cv2.COLOR_BGR2GRAY)
 
    # applying gaussian blur
    value = (35, 35)
    blurred = cv2.GaussianBlur(grey, value, 0)
 
    # thresholdin: Otsu's Binarization method
    _, thresh1 = cv2.threshold(blurred, 127, 255,
                               cv2.THRESH_BINARY_INV+cv2.THRESH_OTSU)
 
    # show thresholded image
    cv2.imshow('Thresholded', thresh1)
 
    # check OpenCV version to avoid unpacking error
    (version, _, _) = cv2.__version__.split('.')
 
    se = np.ones((7,7), dtype='uint8')
    image_close = cv2.morphologyEx(red, cv2.MORPH_CLOSE, se)
    
    if version == '3':
        image, contours, hierarchy = cv2.findContours(image_close, cv2.RETR_EXTERNAL,
    cv2.CHAIN_APPROX_SIMPLE)
    elif version == '2':
        contours, hierarchy = cv2.findContours(thresh1.copy(),cv2.RETR_TREE, \
               cv2.CHAIN_APPROX_NONE)
 
    # find contour with max area
    
 
   # create bounding rectangle around the contour (can skip below two lines)
    
 
    # drawing contours
    for (i, c) in enumerate(contours):
    # draw the contour
    
      ((x, y), _) = cv2.minEnclosingCircle(c)
      cv2.putText(img, "#{}".format(i + 1), (int(x) - 10, int(y)), cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0, 0, 255), 2)
      cv2.drawContours(img, [c], -1, (0, 255, 0), 2)
 
 
    # show appropriate images in windows
    cv2.imshow('Gesture', img)
   
    cv2.imshow('Contours', image_close)
 
    k = cv2.waitKey(10)
    if k == 27:
        break