code: def normalized_per_object(image, labels):
      
      nobjects = labels.max()
      objects = np.arange(nobjects + 1)
      lmin, lmax = scind.extrema(image, labels, objects)[:2]
      # Divisor is the object's max - min, or 1 if they are the same.
      divisor = np.ones((nobjects + 1,))
      divisor[lmax > lmin] = (lmax - lmin)[lmax > lmin]
      return (image - lmin[labels]) / divisor[labels]
docs: Normalize the intensities of each object to the [0, 1] range.