.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "auto_examples/plot_HandE.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        :ref:`Go to the end <sphx_glr_download_auto_examples_plot_HandE.py>`
        to download the full example code.

.. rst-class:: sphx-glr-example-title

.. _sphx_glr_auto_examples_plot_HandE.py:


Histology - H&E Staining
========================

Applying the cellsam_pipeline to segment H&E stained images.

This FOV is extracted from dataset `HBM248.QRTB.362`_ available
on the `HuBMAP data portal`_.

.. _HBM248.QRTB.362: https://portal.hubmapconsortium.org/browse/dataset/692cd314ab251e5b1b1b02a9b7a9beec
.. _HuBMAP data portal: https://portal.hubmapconsortium.org/

.. GENERATED FROM PYTHON SOURCE LINES 13-43



.. image-sg:: /auto_examples/images/sphx_glr_plot_HandE_001.png
   :alt: plot HandE
   :srcset: /auto_examples/images/sphx_glr_plot_HandE_001.png
   :class: sphx-glr-single-img


.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    (512, 512, 3)
    /home/administrator/envs/cs-13-dev/lib/python3.13/site-packages/cellSAM/sam_inference.py:351: UserWarning: Low IOU threshold, ignoring mask.
      warnings.warn("Low IOU threshold, ignoring mask.")
    /home/administrator/repos/cellSAM/examples/plot_HandE.py:38: FutureWarning: `napari.view_image` is deprecated and will be removed in napari 0.7.0.
    Use `viewer = napari.Viewer(); viewer.add_image(...)` instead.
      nim = napari.view_image(img, name="H&E image");






|

.. code-block:: Python

    import zarr
    import skimage
    import napari
    from cellSAM import cellsam_pipeline
    # NOTE: data is stored with zarr_format 3
    assert int(zarr.__version__[0]) > 2

    # Access H&E image
    store = zarr.storage.FsspecStore.from_url(
        "s3://cellsam-gallery-sample-data/sample-data.zarr",
        storage_options={"anon": True},
        read_only=True,
    )
    z = zarr.open_group(store=store, mode="r")
    # Load H&E image into local memory
    # Limit to upper-left quadrant to reduce CI computation load
    tilesize = 512
    img = z["HBM248_QRTB_362"][:tilesize, :tilesize, :]
    print(img.shape)

    # NOTE: H&E images are often RGB - CellSAM expects RGB images to
    # be condensed to a single channel, as with `skimage.color.rgb2gray`,
    # for example
    mask = cellsam_pipeline(skimage.color.rgb2gray(img), use_wsi=False)

    nim = napari.view_image(img, name="H&E image");
    nim.add_labels(mask, name="Cellsam segmentation");

    if __name__ == "__main__":
        napari.run()


.. rst-class:: sphx-glr-timing

   **Total running time of the script:** (0 minutes 5.726 seconds)


.. _sphx_glr_download_auto_examples_plot_HandE.py:

.. only:: html

  .. container:: sphx-glr-footer sphx-glr-footer-example

    .. container:: sphx-glr-download sphx-glr-download-jupyter

      :download:`Download Jupyter notebook: plot_HandE.ipynb <plot_HandE.ipynb>`

    .. container:: sphx-glr-download sphx-glr-download-python

      :download:`Download Python source code: plot_HandE.py <plot_HandE.py>`

    .. container:: sphx-glr-download sphx-glr-download-zip

      :download:`Download zipped: plot_HandE.zip <plot_HandE.zip>`


.. only:: html

 .. rst-class:: sphx-glr-signature

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_