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https://issues.apache.org/jira/browse/TIKA-2298?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Chris A. Mattmann updated TIKA-2298:
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Labels: ObjectRecognitionParser gsoc memex (was: ObjectRecognitionParser
memex)
> To improve object recognition parser so that it may work without external
> RESTful service setup
> -----------------------------------------------------------------------------------------------
>
> Key: TIKA-2298
> URL: https://issues.apache.org/jira/browse/TIKA-2298
> Project: Tika
> Issue Type: Improvement
> Components: parser
> Affects Versions: 1.14
> Reporter: Avtar Singh
> Assignee: Chris A. Mattmann
> Labels: ObjectRecognitionParser, gsoc, memex
> Fix For: 1.16
>
> Original Estimate: 672h
> Remaining Estimate: 672h
>
> When ObjectRecognitionParser was built to do image recognition, there wasn't
> good support for Java frameworks. All the popular neural networks were in
> C++ or python. Since there was nothing that runs within JVM, we tried
> several ways to glue them to Tika (like CLI, JNI, gRPC, REST).
> However, this game is changing slowly now. Deeplearning4j, the most famous
> neural network library for JVM, now supports importing models that are
> pre-trained in python/C++ based kits [5].
> *Improvement:*
> It will be nice to have an implementation of ObjectRecogniser that
> doesn't require any external setup(like installation of native libraries or
> starting REST services). Reasons: easy to distribute and also to cut the IO
> time.
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