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author greg
date Fri, 13 Oct 2017 10:34:23 -0400
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1 <tool id="yolo" name="YOLO" version="1.0">
2 <description>real-time object detection</description>
3 <requirements>
4 <requirement type="package" version="1.0">darknet</requirement>
5 </requirements>
6 <command detect_errors="exit_code"><![CDATA[
7 darknet detect cfg/yolo.cfg yolo.weights '$input' 2> output.log
8 && mv ./predictions.png $output
9 ]]></command>
10 <inputs>
11 <param name="input" type="data" format="jpg" label="Select input image" />
12 </inputs>
13 <outputs>
14 <data name="output_log" format="txt" label="${tool.name} darknet output log) on ${on_string}" />
15 <data name="output" format="png"/>
16 </outputs>
17 <tests>
18 <test>
19 </test>
20 </tests>
21 <help>
22 **What it does**
23
24 You only look once (YOLO) is a state-of-the-art, real-time object detection system.
25
26 -----
27
28 **Options**
29
30 </help>
31 <citations>
32 <citation type="bibtex">
33 @misc{darknet13,
34 author = {Joseph Redmon},
35 title = {Darknet: Open Source Neural Networks in C},
36 url = {http://pjreddie.com/darknet/},
37 year = {2013--2016}}
38 </citation>
39 <citation type="bibtex">
40 @article{redmon2016yolo9000,
41 title={YOLO9000: Better, Faster, Stronger},
42 author={Redmon, Joseph and Farhadi, Ali},
43 journal={arXiv preprint arXiv:1612.08242},
44 year={2016}}
45 </citation>
46 </citations>
47 </tool>