| Next changeset 1:d10a46ef77d3 (2023-11-14) |
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Commit message:
planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tree/master/tools/rfove/ commit e1a945d60e1fb8211cab0a8ecd1aaf129971e64c |
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rfove.xml test-data/BBBC033_C2_z28.png test-data/output.tiff |
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| diff -r 000000000000 -r ddff439fac16 rfove.xml --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/rfove.xml Mon Nov 13 09:35:00 2023 +0000 |
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| @@ -0,0 +1,52 @@ +<tool id="rfove" name="Perform segmentation region-based fitting of overlapping ellipses" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@" profile="20.05"> + <description>with RFOVE</description> + <macros> + <token name="@TOOL_VERSION@">2023.11.12</token> + <token name="@VERSION_SUFFIX@">0</token> + </macros> + <edam_operations> + <edam_operation>operation_3443</edam_operation> + </edam_operations> + <xrefs> + <xref type="bio.tools">rfove</xref> + </xrefs> + <requirements> + <container type="docker">docker.io/kostrykin/rfove:@TOOL_VERSION@</container> + </requirements> + <command detect_errors="aggressive"> + <![CDATA[ + #set $neighborhood_size = "%d" % ($half_neighborhood_size.value * 2 + 1) + /rfove + ${area_ub} + ${min_area_max_area_ratio_ub} + ${overlap_ub} + ${neighborhood_size} + '${dataset}' + + output.tiff + ]]> + </command> + <inputs> + <param name="dataset" type="data" format="tiff,png" label="Dataset" /> + <param name="area_ub" type="integer" label="Maximum ellipse area" min="5" value="250" /> + <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" /> + + <param name="overlap_ub" type="float" label="Maximum ellipse overlap" min="0" value="0.2" /> + <param name="half_neighborhood_size" type="integer" label="Half neighborhood size" min="1" value="100" /> + </inputs> + <outputs> + <data format="tiff" name="masks" from_work_dir="output.tiff" label="${tool.name} on ${on_string}" /> + </outputs> + <tests> + <test> + <param name="dataset" value="BBBC033_C2_z28.png" /> + <output name="masks" value="output.tiff" ftype="tiff" compare="sim_size" /> + </test> + </tests> + <help> + 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. + </help> + <citations> + <citation type="doi">10.1016/j.imavis.2019.09.001</citation> + </citations> +</tool> |
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