code: def prepare_image(self, image):
          
          from decaf.util import transform  # soft dep
          _JEFFNET_FLIP = True
  
          # first, extract the 256x256 center.
          image = transform.scale_and_extract(transform.as_rgb(image), 256)
          # convert to [0,255] float32
          image = image.astype(np.float32) * 255.
          if _JEFFNET_FLIP:
              # Flip the image if necessary, maintaining the c_contiguous order
              image = image[::-1, :].copy()
          # subtract the mean
          image -= self.net_._data_mean
          return image
docs: Returns image of shape `(256, 256, 3)`, as expected by
          `transform` when `classify_direct = True`.