comparison colorize_labels.xml @ 1:43c80f3c3b60 draft

planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tree/master/tools/colorize_labels commit 98270c8f2805d406e0d88605fde778f8f182df9b

0:0afb17e107ff

<tool id="colorize_labels" name="Colorize label map" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@" profile="20.05">
    <description>with SuperDSM</description>
    <macros>
        <token name="@TOOL_VERSION@">0.2.0</token>
        <token name="@VERSION_SUFFIX@">0</token>
    </macros>
    <edam_operations>
        <edam_operation>operation_3443</edam_operation>
    </edam_operations>
    <xrefs>
        <xref type="bio.tools">superdsm</xref>
        <xref type="biii">superdsm</xref>
    </xrefs>
    <requirements>
        <requirement type="package" version="0.2.0">superdsm</requirement>
        <requirement type="package" version="1.20">numpy</requirement>
        <requirement type="package" version="0.18.1">scikit-image</requirement>
    </requirements>
    <command><![CDATA[
    
    ## Inputs
    
    python '$__tool_directory__/colorize_labels.py' '$input'
    --seed $seed
    --bg_label $bg_label
    --bg_color '$bg_color'
    
    ## Outputs
    

    
    ]]>
    </command>
    <inputs>
        <param name="input" type="data" format="tiff,png" label="Input image (label map)" />
        <param argument="--seed" type="integer" value="0" label="Randomization seed" />
        <param argument="--bg_label" type="integer" value="0" label="Background label" />
        <param argument="--bg_color" type="color" value="#000000" label="Background color"/>
    </inputs>
    <outputs>
       <data format="png" name="output" from_work_dir="output.png" />
    </outputs>
    <tests>
        <test>
            <param name="input" value="input1.tif"/>
            <param name="bg_label" value="0"/>
            <param name="bg_color" value="#5a5a5a"/>
            <output name="output" value="output1.png" ftype="png" compare="sim_size" delta_frac="0.1"/>
        </test>
    </tests>
    <help>
        Colorize a 2-D label map for visualization.

        Label maps are produced by segmentation and other image analysis steps.
        Direct inspection of label maps can be difficult,
        because labels usually correspond to gray values which are difficult to
        distinguish visually from each other and from the image background.
        To facilitate the visual inspection of label maps, this tools converts
        label maps to color images, by assigning each label a unique color.
    </help>
    <citations>
        <citation type="doi">10.1109/TPAMI.2022.3185583</citation>
    </citations>
</tool>

1:43c80f3c3b60

<tool id="colorize_labels" name="Colorize label map" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@" profile="20.05">
    <description>with NetworkX</description>
    <macros>
        <token name="@TOOL_VERSION@">3.2.1</token>
        <token name="@VERSION_SUFFIX@">0</token>
    </macros>
    <edam_operations>
        <edam_operation>operation_3443</edam_operation>
    </edam_operations>
    <requirements>
        <requirement type="package" version="3.2.1">networkx</requirement>
        <requirement type="package" version="1.22">numpy</requirement>
        <requirement type="package" version="0.18.1">scikit-image</requirement>
    </requirements>
    <command><![CDATA[
    
    ## Inputs
    
    python '$__tool_directory__/colorize_labels.py' '$input'
    --radius $radius
    --bg_label $bg_label
    --bg_color '$bg_color'
    
    ## Outputs
    

    
    ]]>
    </command>
    <inputs>
        <param name="input" type="data" format="tiff,png" label="Input image (label map)" />
        <param argument="--radius" type="integer" min="1" value="10" label="Radius of the neighborhood" help="Defines the neighborhood (in pixels) where labels are considered to be adjacent." />
        <param argument="--bg_label" type="integer" value="0" label="Background label" />
        <param argument="--bg_color" type="color" value="#000000" label="Background color"/>
    </inputs>
    <outputs>
       <data format="png" name="output" from_work_dir="output.png" />
    </outputs>
    <tests>
        <test>
            <param name="input" value="input1.tif" />
            <param name="radius" value="1" />
            <param name="bg_label" value="0" />
            <param name="bg_color" value="#5a5a5a" />
            <output name="output" value="output1.png" ftype="png" compare="sim_size" delta_frac="0.1" />
        </test>
        <test>
            <param name="input" value="input2.tif" />
            <param name="radius" value="10" />
            <param name="bg_label" value="0" />
            <param name="bg_color" value="#ffffff" />
            <output name="output" value="output2.png" ftype="png" compare="sim_size" delta_frac="0.1" />
        </test>
    </tests>
    <help>
        Colorize a 2-D label map for visualization using greedy coloring.

        Label maps are produced by segmentation and other image analysis steps.
        Direct inspection of label maps can be difficult,
        because labels usually correspond to gray values which are difficult to
        distinguish visually from each other and from the image background.
        To facilitate the visual inspection of label maps, this tools converts
        label maps to color images, by assigning each label a unique color.
    </help>
    <citations>
        <citation type="bibtex">
        @inproceedings{networkx,
          author = {Hagberg, Aric A. and Schult, Daniel A. and Swart, Pieter J.},
          title = {Exploring network structure, dynamics, and function using {NetworkX}},
          booktitle = {Proc. of the 7th Python in Science Conference (SciPy 2008)},
          pages = {11--15},
          year = {2008},
        }
        </citation>
    </citations>
</tool>