code: def image(self, images, name=None, ch_axis=1, row=0, mode=None,
                batched=True, subdir=''):
          
          from chainerui.report.image_report import check_available
          if not check_available():
              return
          from chainerui.report.image_report import report as _image
  
          col_name = self.get_col_name(name, 'image')
          out_dir, rel_out_dir = self.get_subdir(subdir)
          filename, _ = _image(
              images, out_dir, col_name, ch_axis, row, mode, batched)
          self.images[col_name] = os.path.join(rel_out_dir, filename)
  
          self.count += 1
docs: Summary images to visualize.
  
          Args:
              images (:class:`numpy.ndarray` or :class:`cupy.ndarray` or \
                  :class:`chainer.Variable`): batch of images. If Number of
                  dimension is 3 (or 2 when set `batched=False`), the pixels
                  assume as black and white image.
              name (str): name of image. set as column name. when not setting,
                  assigned ``'image'`` + sequential number.
              ch_axis (int): index number of channel dimension. set 1 by default.
                  if the images don't have channel axis, this parameter is
                  ignored.
              row (int): row size to visualize batched images. when set 0,
                  show on unstuck. if images set only one image, the row size
                  will be ignored.
              mode (str): if the images are not RGB or RGBA space, set their
                  color space code. ChainerUI supports 'HSV'.
              batched (bool): if the image is not batched, set ``False``.
              subdir (str): sub-directory path of output.