Algorithm metadata

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Algorithm metadata#

Every algorithm in Imaging Server Kit automatically generates a documentation page describing its purpose and parameters. This page is populated from metadata fields provided in the @sk.algorithm decorator.

Here is an example:

import imaging_server_kit as sk

@sk.algorithm(
    parameters={
        "image": sk.Image(
            name="Image", 
            description="Input image (grayscale)",
        ),
        "threshold": sk.Float(
            name="Threshold", 
            description="Intensity threshold for the binarization", 
            default=0.5,
        ),
    },
    name="Threshold",
    description="Intensity threshold algorithm.", # <- A short description
    tags=["Segmentation", "Demo"],  # A list of tags (arbitrary)
    project_url="https://github.com/Imaging-Server-Kit/imaging-server-kit",
)
def threshold_algo(image, threshold):
    mask = image > threshold
    return sk.Mask(mask)

threshold_algo.info()  # <- Open the doc page in a web browser

In Napari, you can open the documentation page of an algorithm in a web browser by clicking on the 🌐 Doc button. Alternatively, you can call .info() on the algorithm object itself for the same effect.

Meta

Summary#

  • You can include algorithm metadata through fields like name, description, tags and project_url.

  • This metadata automatically populates a documentation web page for the algorithm, which you can access from Python or Napari.

Next steps#

In the next section, we will cover how to combine multiple algorithms to be able to use them together more easily.

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