<tool id="label_to_binary" name="Convert label map to binary image" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@" profile="22.05">
    <description>with NumPy</description>
    <macros>
        <token name="@TOOL_VERSION@">1.26.4</token>
        <token name="@VERSION_SUFFIX@">0</token>
    </macros>
    <edam_operations>
        <edam_operation>operation_3443</edam_operation>
    </edam_operations>
    <xrefs>
        <xref type="bio.tools">galaxy_image_analysis</xref>
    </xrefs>
    <requirements>
        <requirement type="package" version="1.26.4">numpy</requirement>
        <requirement type="package" version="0.18.1">scikit-image</requirement>
    </requirements>
    <command><![CDATA[
    
    ## Inputs
    
    python '$__tool_directory__/label_to_binary.py'
    '$input'
    '$bg_label'
    
    ## Outputs
    
    ./output.tif
    
    ]]>
    </command>
    <inputs>
        <param name="input" type="data" format="tiff,png" label="Input image (label map)" />
        <param argument="--bg_label" type="integer" value="0" label="Background label" />
    </inputs>
    <outputs>
        <data format="tiff" name="output" from_work_dir="output.tif" />
    </outputs>
    <tests>
        <test>
            <param name="input" value="input1.tif" />
            <param name="bg_label" value="0" />
            <output name="output" value="output1.tif" ftype="tiff" compare="sim_size" delta_frac="0.1"/>
        </test>
    </tests>
    <help>
        This tools converts a label map (objects labeled by different labels/values) to a binary image.

        The input image is converted by assigning white (pixel value 255) to image regions corresponding to labeled objects,
        and black (pixel value 0) to image regions corresponding to image background (by default, this is label 0).
    </help>
    <citations>
        <citation type="doi">10.1038/s41586-020-2649-2</citation>
    </citations>
</tool>