<tool id="ip_localthreshold" name="Local Threshold" version="0.0.1">
   <description>applies a local threshold algorithm to an image</description>
   <requirements>
        <requirement type="package" version="0.14.2">scikit-image</requirement>
        <requirement type="package" version="1.15.4">numpy</requirement>
        <requirement type="package" version="5.3.0">pillow</requirement>
        <requirement type="package" version="0.15.1">tifffile</requirement>
   </requirements>
   <command detect_errors="aggressive">
   <![CDATA[
   python '$__tool_directory__/auto_local_threshold.py' '$input' '$output' $block_size $thresh_type $dark_background
   ]]>
   </command>
   <inputs>
        <param name="input" type="data" format="tiff" label="Source file" />
        <param name="thresh_type" type="select" label="Threshold Algorithm">
          <option value="gaussian" selected="True">Gaussian</option>
          <option value="median">Median</option>
          <option value="mean">Mean</option>
        </param>        
        <param name="block_size" type="integer" value="5" label="Odd size of pixel neighborhood which is used to calculate the threshold value" />
        <param name="dark_background" type="boolean" checked="true" truevalue="True" falsevalue="False" label="Dark Background" />
    </inputs>
    <outputs>
       <data format="tiff" name="output" />
    </outputs>
    <tests>
        <test>
            <param name="input" value="sample.tif"/>
            <output name="output" value="out.tif" ftype="tiff" compare="sim_size"/>
            <param name="thresh_type" value="gaussian"/>
            <param name="block_size" value="429"/>
            <param name="dark_backgroud" value="True"/>
        </test>
    </tests>
    <help>
        Applies a local threshold algorithm to an image.
    </help>
    <citations>
        <citation type="doi">10.1016/j.jbiotec.2017.07.019</citation>
    </citations>
</tool>