annotate rfove.xml @ 1:d10a46ef77d3 draft

planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tree/master/tools/rfove/ commit ea0b0711c265375bc6db69ebf421b39a3b0aa602
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date Tue, 14 Nov 2023 00:09:17 +0000
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1 <tool id="rfove" name="Perform segmentation using region-based fitting of overlapping ellipses" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@" profile="20.05">
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2 <description>with RFOVE</description>
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3 <macros>
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4 <token name="@TOOL_VERSION@">2023.11.12</token>
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5 <token name="@VERSION_SUFFIX@">1</token>
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6 </macros>
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7 <edam_operations>
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8 <edam_operation>operation_3443</edam_operation>
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9 </edam_operations>
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10 <xrefs>
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11 <xref type="bio.tools">rfove</xref>
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12 </xrefs>
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13 <requirements>
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14 <container type="docker">docker.io/kostrykin/rfove:@TOOL_VERSION@</container>
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15 </requirements>
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16 <command detect_errors="aggressive">
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17 <![CDATA[
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18 #set $neighborhood_size = "%d" % ($half_neighborhood_size.value * 2 + 1)
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19 /rfove
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20 ${area_ub}
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21 ${min_area_max_area_ratio_ub}
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22 ${overlap_ub}
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23 ${neighborhood_size}
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24 '${dataset}'
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25
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26 output.tiff
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27 ]]>
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28 </command>
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29 <inputs>
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30 <param name="dataset" type="data" format="tiff,png" label="Dataset" />
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31 <param name="area_ub" type="integer" label="Maximum ellipse area" min="5" value="250" />
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32 <param name="min_area_max_area_ratio_ub" type="float" min="0" max="1" value="0.1" label="Upper bound of the ratio: minimum area / maximum area" />
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33
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34 <param name="overlap_ub" type="float" label="Maximum ellipse overlap" min="0" value="0.2" />
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35 <param name="half_neighborhood_size" type="integer" label="Half neighborhood size" min="1" value="100" />
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36 </inputs>
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37 <outputs>
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38 <data format="tiff" name="masks" from_work_dir="output.tiff" label="${tool.name} on ${on_string}" />
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39 </outputs>
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40 <tests>
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41 <test>
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42 <param name="dataset" value="BBBC033_C2_z28.png" />
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43 <output name="masks" value="output.tiff" ftype="tiff" compare="sim_size" />
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44 </test>
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45 </tests>
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46 <help>
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47 RFOVE is completely unsupervised, operates without any assumption or prior knowledge on the object’s shape and extends and improves the Decremental Ellipse Fitting Algorithm (DEFA). Both RFOVE and DEFA solve the multi-ellipse fitting problem by performing model selection that is guided by the minimization of the Akaike Information Criterion on a suitably defined shape complexity measure. However, in contrast to DEFA, RFOVE minimizes an objective function that allows for ellipses with higher degree of overlap and, thus, achieves better ellipse-based shape approximation.
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48 </help>
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49 <citations>
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50 <citation type="doi">10.1016/j.imavis.2019.09.001</citation>
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51 </citations>
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52 </tool>