code: def _fitImg(self, img):
          '''
          fit perspective and size of the input image to the reference image
          '''
          img = imread(img, 'gray')
          if self.bg is not None:
              img = cv2.subtract(img, self.bg)
  
          if self.lens is not None:
              img = self.lens.correct(img, keepSize=True)
  
          (H, _, _, _, _, _, _, n_matches) = self.findHomography(img)
          H_inv = self.invertHomography(H)
  
          s = self.obj_shape
          fit = cv2.warpPerspective(img, H_inv, (s[1], s[0]))
          return fit, img, H, H_inv, n_matchef _fitImg(self, img):
          '''
          fit perspective and size of the input image to the reference image
          '''
          img = imread(img, 'gray')
          if self.bg is not None:
              img = cv2.subtract(img, self.bg)
  
          if self.lens is not None:
              img = self.lens.correct(img, keepSize=True)
  
          (H, _, _, _, _, _, _, n_matches) = self.findHomography(img)
          H_inv = self.invertHomography(H)
  
          s = self.obj_shape
          fit = cv2.warpPerspective(img, H_inv, (s[1], s[0]))
          return fit, img, H, H_inv, n_matches
docs: fit perspective and size of the input image to the reference image