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https://issues.apache.org/jira/browse/TIKA-2298?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16075786#comment-16075786
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Hudson commented on TIKA-2298:
------------------------------
FAILURE: Integrated in Jenkins build Tika-trunk #1310 (See
[https://builds.apache.org/job/Tika-trunk/1310/])
TIKA-2298: DL4J-VGG16 simplify conf, implementation (thammegowda:
[https://github.com/apache/tika/commit/c476ec14efe2d9007f461ecf09ccd2ade4ffc197])
* (edit)
tika-dl/src/test/resources/org/apache/tika/dl/imagerec/dl4j-vgg16-config.xml
* (edit) tika-dl/src/main/java/org/apache/tika/dl/imagerec/DL4JVGG16Net.java
Record change for TIKA-2298: Very Deep Convolutional Networks for (mattmann:
[https://github.com/apache/tika/commit/b58cfcf1935d138065eb4a090ba4c1fef17ddacd])
* (edit) CHANGES.txt
TIKA-2298 -- skip test if no network connectivity. Should rework for
(tallison:
[https://github.com/apache/tika/commit/158675def02810d116e7cdab8409c121a88e77eb])
* (edit) tika-dl/src/test/java/org/apache/tika/dl/imagerec/DL4JVGG16NetTest.java
> 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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