<tool id="ip_detection_viz" name="Detection Visualization" version="0.2"> 
    <description>Detection Visualization</description>
    <requirements>
        <requirement type="package" version="0.14.2">scikit-image</requirement>
        <requirement type="package" version="3.0.2">matplotlib</requirement>
        <requirement type="package" version="0.15.1">tifffile</requirement>
    </requirements>
    <command detect_errors="aggressive">
        <![CDATA[
        python '$__tool_directory__/detection_viz.py' '$input' '$output' 
        --stroke_size $thickness --circle_radius $circle_radius $tp $fn $fp
        ]]> 
    </command>
    <inputs>
        <param name="input" type="data" format="tiff,png,jpg,bmp" label="Binary Image File"/>
        <param argument="--tp" type="boolean" checked="false" falsevalue="" truevalue="--tp"/>
        <param argument="--fn" type="boolean" checked="false" falsevalue="" truevalue="--fn"/>
        <param argument="--fp" type="boolean" checked="false" falsevalue="" truevalue="--fp"/>
        <param name="thickness" type="float" value="3.0" label="Stroke thickness"/>
        <param name="circle_radius" type="float" value="50.0" label="Circle radius"/>
    </inputs>
    <outputs>
        <data format="png" name="output"/>
    </outputs>
    <tests>
        <test>
            <param name="input" value="sample.png"/>
            <output name="output" value="out.png" ftype="png"/>
        </test>
    </tests>
    <help>
    **What it does**

    Draws circles of different colors around detected true positives, false negatives and false positives.
    </help>
    <citations>
        <citation type="doi">10.1016/j.jbiotec.2017.07.019</citation>
    </citations>
</tool>