text: import click
  import numpy as np
  import re
  import tifffile
  import xtiff
  
  from pathlib import Path
  
  from .data import anndata_cmd, csv_cmd, fcs_cmd
  from .graphs import graphs_cmd
  from ..._cli.utils import OrderedClickGroup
  from ... import io
  
  
  @click.group(
      name="export",
      cls=OrderedClickGroup,
      help="Export data to third-party formats",
  )
  def export_cmd_group():
      pass
  
  
  @export_cmd_group.command(name="ome", help="Export images as OME-TIFF")
  @click.option(
      "--img",
      "img_dir",
      type=click.Path(exists=True, file_okay=False),
      default="img",
      show_default=True,
      help="Path to the image directory",
  )
  @click.option(
      "--panel",
      "panel_file",
      type=click.Path(exists=True, dir_okay=False),
      default="panel.csv",
      show_default=True,
      help="Path to the panel file",
  )
  @click.option(
      "-o",
      "ome_dir",
      type=click.Path(file_okay=False),
      default="ome",
      show_default=True,
      help="Path to the OME-TIFF export directory",
  )
  def ome_cmd(img_dir, panel_file, ome_dir):
      panel = io.read_panel(panel_file)
      channel_names = [
          f"{channel_id}_{channel_name}"
          for channel_id, channel_name in zip(
              panel["channel"].values, panel["name"].values
          )
      ]
      Path(ome_dir).mkdir(exist_ok=True)
      for img_file in io.list_image_files(img_dir):
          img = io.read_image(img_file, native_dtype=True)
          ome_file = io._as_path_with_suffix(Path(ome_dir) / img_file.name, ".ome.tiff")
          xtiff.to_tiff(
              io._to_dtype(img, np.float32),
              ome_file,
              channel_names=channel_names,
          )
          click.echo(ome_file)
          del img
  
  
  @export_cmd_group.command(name="histocat", help="Export images to histoCAT for MATLAB")
  @click.option(
      "--img",
      "img_dir",
      type=click.Path(exists=True, file_okay=False),
      default="img",
      show_default=True,
      help="Path to the image directory",
  )
  @click.option(
      "--masks",
      "mask_dir",
      type=click.Path(file_okay=False),
      default="masks",
      show_default=True,
      help="Path to the mask directory",
  )
  @click.option(
      "--panel",
      "panel_file",
      type=click.Path(exists=True, dir_okay=False),
      default="panel.csv",
      show_default=True,
      help="Path to the panel file",
  )
  @click.option(
      "-o",
      "histocat_dir",
      type=click.Path(file_okay=False),
      default="histocat",
      show_default=True,
      help="Path to the histoCAT export directory",
  )
  def histocat_cmd(img_dir, mask_dir, panel_file, histocat_dir):
      panel = io.read_panel(panel_file)
      channel_names = [
          f"{channel_id}_{channel_name}"
          for channel_id, channel_name in zip(
              panel["channel"].values, panel["name"].values
          )
      ]
      img_files = io.list_image_files(img_dir)
      mask_files = None
      if Path(mask_dir).exists():
          mask_files = io.list_mask_files(mask_dir, base_files=img_files)
      Path(histocat_dir).mkdir(exist_ok=True)
      for i, img_file in enumerate(img_files):
          img = io.read_image(img_file, native_dtype=True)
          histocat_img_dir = Path(histocat_dir) / img_file.stem
          histocat_img_dir.mkdir(exist_ok=True)
          for channel_name, channel_img in zip(channel_names, img):
              channel_name = re.sub(r"\s*/\s*", "_", channel_name)
              channel_name = re.sub(r"\s", "_", channel_name)
              histocat_img_file = histocat_img_dir / f"{channel_name}.tiff"
              tifffile.imwrite(
                  histocat_img_file,
                  data=io._to_dtype(channel_img, np.float32)[
                      np.newaxis, np.newaxis, np.newaxis, :, :, np.newaxis
                  ],
                  imagej=True,
              )
              click.echo(histocat_img_file)
          mask = None
          if mask_files is not None:
              mask = io.read_mask(mask_files[i], native_dtype=True)
              histocat_mask_file = histocat_img_dir / f"{img_file.stem}_mask.tiff"
              tifffile.imwrite(
                  histocat_mask_file,
                  data=io._to_dtype(mask, np.uint16)[
                      np.newaxis, np.newaxis, np.newaxis, :, :, np.newaxis
                  ],
                  imagej=True,
              )
              click.echo(histocat_mask_file)
          del img, mask
  
  
  export_cmd_group.add_command(csv_cmd)
  export_cmd_group.add_command(fcs_cmd)
  export_cmd_group.add_command(anndata_cmd)
  export_cmd_group.add_command(graphs_cmd)
  