galaxy/tools/interactive/interactivetool_ilastik.xml

<tool id="interactive_tool_ilastik" tool_type="interactive" name="Ilastik" version="@VERSION@" profile="23.0">
    <description>interactive learning and segmentation toolkit</description>
    <macros>
        <token name="@VERSION@">1.4.0</token>
    </macros>
    <requirements>
        <container type="docker">quay.io/galaxy/ilastik:@VERSION@</container>
    </requirements>
    <entry_points>
        <entry_point name="Ilastik" requires_domain="True">
            <port>5800</port>
        </entry_point>
    </entry_points>
    <command detect_errors="exit_code">
    <![CDATA[
        ## Check inputs have no duplicated element_identifier:
        #set labels = [input.element_identifier for input in $infiles]
        #set duplicates = [label for label in labels if labels.count(label) > 1]
        #if len(duplicates) > 0:
            #set unique_duplicates = list(set(duplicates))
            echo "Cannot run ilastik because these identifiers are present more than once:" &&
            #for label in $unique_duplicates:
                echo $label &&
            #end for
            exit 1 &&
        #end if
        export HOME=\$PWD &&
        ## Create a directory where the app user has access
        mkdir -p ./output &&
        chown 1000:1000 ./output/ &&
        ## Make a copy of the existing project if exists
        #if str($input_type.existing) == "existing":
            cp '$input_type.project' ./output/MyProject.ilp &&
        #end if

        ## Link input images to current working directory
        #for input in $infiles:
            ln -s '$input' ./'$input.element_identifier'.tif &&
        #end for
        ## Write the bash script to run:
        #if str($input_type.existing) == "new":
            echo "ilastik --new_project \$HOME/output/MyProject.ilp --workflow '$input_type.Workflow'" > ./ilastik_with_args &&
        #else:
            echo "ilastik --project \$HOME/output/MyProject.ilp" > ./ilastik_with_args &&
        #end if
        ## Copy it to /bin/ so it will be used by the container:
        chmod +x ./ilastik_with_args &&
        cp ./ilastik_with_args '/bin/' &&
        /init
    ]]>
    </command>
    <inputs>
        <conditional name="input_type">
            <param name="existing" type="select" label="Which project you want to work on?">
                <option value="new">Start a new project</option>
                <option value="existing">Modify an existing project</option>
            </param>
            <when value="new">
                <param name="Workflow" type="select" label="Type of Workflow" >
                    <option value="PixelClassificationWorkflow">Pixel Classification</option>
                    <option value="AutocontextTwoStage">Autocontext (2-stage)</option>
                    <option value="ObjectClassificationWorkflowPixel">Pixel Classification + Object Classification</option>
                    <option value="ObjectClassificationWorkflowPrediction">Object Classification [Inputs: Raw Data, Pixel Prediction Map]</option>
                    <option value="ObjectClassificationWorkflowBinary">Object Classification [Inputs: Raw Data, Segmentation]</option>
                    <option value="ConservationTrackingWorkflowFromBinary">Tracking [Inputs: Raw Data, Segmentation Image]</option>
                    <option value="ConservationTrackingWorkflowFromPrediction">Tracking [Inputs: Raw Data, Pixel Prediction Map]</option>
                    <option value="AnimalConservationTrackingWorkflowFromBinary">Animal Tracking [Inputs: Raw Data, Segmentation Image]</option>
                    <option value="AnimalConservationTrackingWorkflowFromPrediction">Animal Tracking [Inputs: Raw Data, Pixel Prediction Map]</option>
                    <option value="StructuredTrackingWorkflowFromBinary">Tracking with Learning [Inputs: Raw Data, Segmentation Image]</option>
                    <option value="StructuredTrackingWorkflowFromPrediction">Tracking with Learning [Inputs: Raw Data, Pixel Prediction Map]</option>
                    <option value="EdgeTrainingWithMulticutWorkflow">Bounary-based Segmentation with Multicut</option>
                    <option value="CountingWorkflow">Cell Density Counting</option>
                    <option value="DataConversionWorkflow">Data Conversion</option>
                    <option value="neuralNetwork.RemoteWorkflow">Neural Network Classification (Remote)</option>
                    <option value="neuralNetwork.LocalWorkflow">Neural Network Classification (Local)</option>
                </param>
            </when>
            <when value="existing">
                <param argument="--project" type="data" format="h5" label="Existing ilastik project" />
            </when>
        </conditional>
        <param name="infiles" type="data" format="tiff" multiple="true" label="Input files in TIFF format"/>
    </inputs>
    
    <outputs>
        <data name="ilastik_project" format="h5" label="Ilastik project file" from_work_dir="output/MyProject.ilp"/>
    </outputs>
    
    <tests>
    </tests>
    
    <help><![CDATA[
        Leverage machine learning algorithms to easily segment, classify, track and count your cells or other experimental data. Most operations are interactive, even on large datasets: you just draw the labels and immediately see the result. No machine learning expertise required.

        This tool has been designed uniquely to make/modify a project.
        
        - It requires that input images have unique identifiers.
        - When you have trained your project, save it and quit the application. The project called 'MyProject.ilp' will be imported into your history.
        - If you want to modify a project, make sure you use at least the same images (with the same identifiers) as the first time (but you can add more).

        Please, check the documentation at https://www.ilastik.org/documentation/.
]]>
    </help>
    <citations>
        <citation type="doi">10.1038/s41592-019-0582-9</citation>
    </citations>
</tool>