annotate 2d_filter_segmentation_by_features.xml @ 1:6ad1d3cfdea1 draft

planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tree/master/tools/2d_filter_segmentation_by_features/ commit 2286a6c9da88596349ed9d967c51541409c0a7bf

<tool id="ip_2d_filter_segmentation_by_features" name="Filter label map by rules" version="0.0.1-2">
   <description></description>
    <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="0.14.2">scikit-image</requirement> 
        <requirement type="package" version="5.3.0">pillow</requirement>
        <requirement type="package" version="0.23.4">pandas</requirement>
        <requirement type="package" version="0.15.1">tifffile</requirement>
    </requirements>
    <command detect_errors="aggressive">
    <![CDATA[
    python '$__tool_directory__/2d_filter_segmentation_by_features.py' '$input' '$output' '$feature_file' '$rule_file'
    ]]>
    </command>
    <inputs>
        <param name="input" type="data" format="tiff" label="Source file" /> 
        <param name="feature_file" type="data" format="tabular" label="Feature file" /> 
        <param name="rule_file" type="data" format="tabular" label="Rules file" /> 
    </inputs>
    <outputs>
       <data format="tiff" name="output" />
    </outputs>
    <tests>
        <test>
            <param name="input" value="in.tif"/>
            <param name="feature_file" value="features.tabular"/>
            <param name="rule_file" value="rules.tabular"/>
            <output name="output" value="out.tif" ftype="tiff" compare="sim_size"/>
        </test>
    </tests>
    <help>
        Filter label image by rules (e.g., remove large or deformed objects).
        Rules file has a specific format (cols: ,f1,2, rows: feature_name, min, max). The features have to be also profived in a specific format (cols: label, f1, f2).
    </help>
    <citations>
        <citation type="doi">10.1016/j.jbiotec.2017.07.019</citation>
    </citations>
</tool>