code: def addImg(self, img, maxShear=0.015, maxRot=100, minMatches=12,
                 borderWidth=3):  # borderWidth=100
          
          try:
              fit, img, H, H_inv, nmatched = self._fitImg(img)
          except Exception as e:
              print(e)
              return
  
          # CHECK WHETHER FIT IS GOOD ENOUGH:
          (translation, rotation, scale, shear) = decompHomography(H)
          print('Homography ...\n\ttranslation: %s\n\trotation: %s\n\tscale: %s\n\tshear: %s'
                % (translation, rotation, scale, shear))
          if (nmatched > minMatches
                  and abs(shear) < maxShear
                  and abs(rotation) < maxRot):
              print('==> img added')
              # HOMOGRAPHY:
              self.Hs.append(H)
              # INVERSE HOMOGRSAPHY
              self.Hinvs.append(H_inv)
              # IMAGES WARPED TO THE BASE IMAGE
              self.fits.append(fit)
              # ADD IMAGE TO THE INITIAL flatField ARRAY:
              i = img > self.signal_ranges[-1][0]
  
              # remove borders (that might have erroneous light):
              i = minimum_filter(i, borderWidth)
  
              self._ff_mma.update(img, i)
  
              # create fit img mask:
              mask = fit < self.signal_ranges[-1][0]
              mask = maximum_filter(mask, borderWidth)
              # IGNORE BORDER
              r = self.remove_border_size
              if r:
                  mask[:r, :] = 1
                  mask[-r:, :] = 1
                  mask[:, -r:] = 1
                  mask[:, :r] = 1
              self._fit_masks.append(mask)
  
              # image added
              return fit
          return False
docs: Args:
              img (path or array): image containing the same object as in the reference image
          Kwargs:
              maxShear (float): In order to define a good fit, refect higher shear values between
                                this and the reference image
              maxRot (float): Same for rotation
              minMatches (int): Minimum of mating points found in both, this and the reference image