%matplotlib inline

Show layers of the ImageContainer

This example shows how to use squidpy.im.ImageContainer.show().

This function is useful to visualize statically different layers of the squidpy.im.ImageContainer class.

See also

• See Crop images with ImageContainer and Smooth an image for additional examples on methods of the squidpy.im.ImageContainer.

import squidpy as sq

Load the Mibitof dataset.

adata = sq.datasets.mibitof()

We can briefly visualize the data to understand the type of images we have.

sq.pl.spatial_segment(
    adata,
    library_id=["point16", "point23", "point8"],
    seg_cell_id="cell_id",
    color="Cluster",
    library_key="library_id",
    title=["point16", "point23", "point8"],
)

We have three different tissue samples. We also have segmentation masks for each tissue sample. Let’s extract the image from the anndata.AnnData object and create a squidpy.im.ImageContainer object.

imgs = []
for library_id in adata.uns["spatial"].keys():
    img = sq.im.ImageContainer(
        adata.uns["spatial"][library_id]["images"]["hires"], library_id=library_id
    )
    img.add_img(
        adata.uns["spatial"][library_id]["images"]["segmentation"],
        library_id=library_id,
        layer="segmentation",
    )
    img["segmentation"].attrs["segmentation"] = True
    imgs.append(img)
img = sq.im.ImageContainer.concat(imgs)

WARNING: Channel dimension cannot be aligned with an existing one, using `channels_0`
WARNING: Channel dimension cannot be aligned with an existing one, using `channels_0`
WARNING: Channel dimension cannot be aligned with an existing one, using `channels_0`

We can visualize each image of the object with squidpy.im.ImageContainer.show().

img.show("image")

squidpy.im.ImageContainer.show() also allows to overlay the results of segmentation.

img.show("image", segmentation_layer="segmentation", segmentation_alpha=0.5)