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From "Chris A. Mattmann (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (TIKA-2298) To improve object recognition parser so that it may work without external RESTful service setup
Date Sun, 21 May 2017 15:40:11 GMT

     [ https://issues.apache.org/jira/browse/TIKA-2298?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Chris A. Mattmann updated TIKA-2298:
------------------------------------
    Fix Version/s:     (was: 1.15)
                   1.16

> 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
>              Labels: ObjectRecognitionParser
>             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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