[jira] [Commented] (TIKA-2262) Supporting Image-to-Text (Image Captioning) in Tika for Image MIME Types

2017-07-08 Thread ASF GitHub Bot (JIRA) 

[ 
https://issues.apache.org/jira/browse/TIKA-2262?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16079427#comment-16079427
 ] 

ASF GitHub Bot commented on TIKA-2262:
--

chrismattmann commented on a change in pull request #189: Fix for TIKA-2262: 
Supporting Image-to-Text (Image Captioning) in Tika
URL: https://github.com/apache/tika/pull/189#discussion_r126294778
 
 

 ##
 File path: 
tika-parsers/src/main/resources/org/apache/tika/parser/captioning/tf/Im2txtRestDockerfile
 ##
 @@ -0,0 +1,62 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+FROM inception-rest-tika
+MAINTAINER Apache Tika Team
+
+#Install python pillow. TODO: Remove this with the fix for TIKA 2398
+RUN pip install pillow
+
+# Download the pretrained im2txt checkpoint
+WORKDIR /usr/share/apache-tika/models/dl/image/caption/
+
+RUN \
+wget https://www.dropbox.com/s/l9ignjpjk774n2z/model_main_untuned.zip?dl=0 
\
 
 Review comment:
   can we please check in the model to 
https://github.com/USCDataScience/img2text.git? I can create the repo for you. 
Then please check in any scripts you used to generate the model. Then we can 
check in the model zip file.
 

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> Supporting Image-to-Text (Image Captioning) in Tika for Image MIME Types
> 
>
> Key: TIKA-2262
> URL: https://issues.apache.org/jira/browse/TIKA-2262
> Project: Tika
>  Issue Type: Improvement
>  Components: parser
>Reporter: Thamme Gowda
>Assignee: Thamme Gowda
>  Labels: deeplearning, gsoc2017, machine_learning
>
> h2. Background:
> Image captions are a small piece of text, usually of one line, added to the 
> metadata of images to provide a brief summary of the scenery in the image. 
> It is a challenging and interesting problem in the domain of computer vision. 
> Tika already has a support for image recognition via [Object Recognition 
> Parser, TIKA-1993| https://issues.apache.org/jira/browse/TIKA-1993] which 
> uses an InceptionV3 model pre-trained on ImageNet dataset using tensorflow. 
> Captioning an image is a very useful feature since it helps text based 
> Information Retrieval(IR) systems to "understand" the scenery in images.
> h2. Technical details and references:
> * Google has long back open sourced their 'show and tell' neural network and 
> its model for autogenerating captions. [Source Code| 
> https://github.com/tensorflow/models/tree/master/im2txt], [Research blog| 
> https://research.googleblog.com/2016/09/show-and-tell-image-captioning-open.html]
> * Integrate it the same way as the ObjectRecognitionParser
> ** Create a RESTful API Service [similar to this| 
> https://wiki.apache.org/tika/TikaAndVision#A2._Tensorflow_Using_REST_Server] 
> ** Extend or enhance ObjectRecognitionParser or one of its implementation
> h2. {skills, learning, homework} for GSoC students
> * Knowledge of languages: java AND python, and maven build system
> * RESTful APIs 
> * tensorflow/keras,
> * deeplearning
> 
> Alternatively, a little more harder path for experienced:
> [Import keras/tensorflow model to 
> deeplearning4j|https://deeplearning4j.org/model-import-keras ] and run them 
> natively inside JVM.
> h4. Benefits
> * no RESTful integration required. thus no external dependencies
> * easy to distribute on hadoop/spark clusters
> h4. Hurdles:
> * This is a work in progress feature on deeplearning4j and hence expected to 
> have lots of troubles on the way! 



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[jira] [Commented] (TIKA-2262) Supporting Image-to-Text (Image Captioning) in Tika for Image MIME Types

2017-07-08 Thread ASF GitHub Bot (JIRA) 

[ 
https://issues.apache.org/jira/browse/TIKA-2262?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16079359#comment-16079359
 ] 

ASF GitHub Bot commented on TIKA-2262:
--

chrismattmann closed pull request #189: Fix for TIKA-2262: Supporting 
Image-to-Text (Image Captioning) in Tika
URL: https://github.com/apache/tika/pull/189
 
 
   
 

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> Supporting Image-to-Text (Image Captioning) in Tika for Image MIME Types
> 
>
> Key: TIKA-2262
> URL: https://issues.apache.org/jira/browse/TIKA-2262
> Project: Tika
>  Issue Type: Improvement
>  Components: parser
>Reporter: Thamme Gowda
>Assignee: Thamme Gowda
>  Labels: deeplearning, gsoc2017, machine_learning
>
> h2. Background:
> Image captions are a small piece of text, usually of one line, added to the 
> metadata of images to provide a brief summary of the scenery in the image. 
> It is a challenging and interesting problem in the domain of computer vision. 
> Tika already has a support for image recognition via [Object Recognition 
> Parser, TIKA-1993| https://issues.apache.org/jira/browse/TIKA-1993] which 
> uses an InceptionV3 model pre-trained on ImageNet dataset using tensorflow. 
> Captioning an image is a very useful feature since it helps text based 
> Information Retrieval(IR) systems to "understand" the scenery in images.
> h2. Technical details and references:
> * Google has long back open sourced their 'show and tell' neural network and 
> its model for autogenerating captions. [Source Code| 
> https://github.com/tensorflow/models/tree/master/im2txt], [Research blog| 
> https://research.googleblog.com/2016/09/show-and-tell-image-captioning-open.html]
> * Integrate it the same way as the ObjectRecognitionParser
> ** Create a RESTful API Service [similar to this| 
> https://wiki.apache.org/tika/TikaAndVision#A2._Tensorflow_Using_REST_Server] 
> ** Extend or enhance ObjectRecognitionParser or one of its implementation
> h2. {skills, learning, homework} for GSoC students
> * Knowledge of languages: java AND python, and maven build system
> * RESTful APIs 
> * tensorflow/keras,
> * deeplearning
> 
> Alternatively, a little more harder path for experienced:
> [Import keras/tensorflow model to 
> deeplearning4j|https://deeplearning4j.org/model-import-keras ] and run them 
> natively inside JVM.
> h4. Benefits
> * no RESTful integration required. thus no external dependencies
> * easy to distribute on hadoop/spark clusters
> h4. Hurdles:
> * This is a work in progress feature on deeplearning4j and hence expected to 
> have lots of troubles on the way! 



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[jira] [Commented] (TIKA-2262) Supporting Image-to-Text (Image Captioning) in Tika for Image MIME Types

2017-07-08 Thread ASF GitHub Bot (JIRA) 

[ 
https://issues.apache.org/jira/browse/TIKA-2262?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16079360#comment-16079360
 ] 

ASF GitHub Bot commented on TIKA-2262:
--

chrismattmann commented on issue #189: Fix for TIKA-2262: Supporting 
Image-to-Text (Image Captioning) in Tika
URL: https://github.com/apache/tika/pull/189#issuecomment-313886335
 
 
   merged into the branch. I am going to test this right now. Let's keep 
working on the branch.
 

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> Supporting Image-to-Text (Image Captioning) in Tika for Image MIME Types
> 
>
> Key: TIKA-2262
> URL: https://issues.apache.org/jira/browse/TIKA-2262
> Project: Tika
>  Issue Type: Improvement
>  Components: parser
>Reporter: Thamme Gowda
>Assignee: Thamme Gowda
>  Labels: deeplearning, gsoc2017, machine_learning
>
> h2. Background:
> Image captions are a small piece of text, usually of one line, added to the 
> metadata of images to provide a brief summary of the scenery in the image. 
> It is a challenging and interesting problem in the domain of computer vision. 
> Tika already has a support for image recognition via [Object Recognition 
> Parser, TIKA-1993| https://issues.apache.org/jira/browse/TIKA-1993] which 
> uses an InceptionV3 model pre-trained on ImageNet dataset using tensorflow. 
> Captioning an image is a very useful feature since it helps text based 
> Information Retrieval(IR) systems to "understand" the scenery in images.
> h2. Technical details and references:
> * Google has long back open sourced their 'show and tell' neural network and 
> its model for autogenerating captions. [Source Code| 
> https://github.com/tensorflow/models/tree/master/im2txt], [Research blog| 
> https://research.googleblog.com/2016/09/show-and-tell-image-captioning-open.html]
> * Integrate it the same way as the ObjectRecognitionParser
> ** Create a RESTful API Service [similar to this| 
> https://wiki.apache.org/tika/TikaAndVision#A2._Tensorflow_Using_REST_Server] 
> ** Extend or enhance ObjectRecognitionParser or one of its implementation
> h2. {skills, learning, homework} for GSoC students
> * Knowledge of languages: java AND python, and maven build system
> * RESTful APIs 
> * tensorflow/keras,
> * deeplearning
> 
> Alternatively, a little more harder path for experienced:
> [Import keras/tensorflow model to 
> deeplearning4j|https://deeplearning4j.org/model-import-keras ] and run them 
> natively inside JVM.
> h4. Benefits
> * no RESTful integration required. thus no external dependencies
> * easy to distribute on hadoop/spark clusters
> h4. Hurdles:
> * This is a work in progress feature on deeplearning4j and hence expected to 
> have lots of troubles on the way! 



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Re: [VOTE] Release Apache Tika 1.16 Candidate #1

2017-07-08 Thread Chris Mattmann 
+1 from me SIGS and CHECKSUMS look good. 

Thanks Tim!

Cheers,
Chris

LMC-053601:apache-tika-1.16-rc1 mattmann$ for type in "" \-app \-eval \-server; 
do $HOME/bin/stage_apache_rc tika$type 1.16 
https://dist.apache.org/repos/dist/dev/tika/; done
  % Total% Received % Xferd  Average Speed   TimeTime Time  Current
 Dload  Upload   Total   SpentLeft  Speed
100 53.5M  100 53.5M0 0  3992k  0  0:00:13  0:00:13 --:--:-- 5122k
  % Total% Received % Xferd  Average Speed   TimeTime Time  Current
 Dload  Upload   Total   SpentLeft  Speed
100   836  100   8360 0   1092  0 --:--:-- --:--:-- --:--:--  1092
  % Total% Received % Xferd  Average Speed   TimeTime Time  Current
 Dload  Upload   Total   SpentLeft  Speed
10034  100340 0 96  0 --:--:-- --:--:-- --:--:--96
  % Total% Received % Xferd  Average Speed   TimeTime Time  Current
 Dload  Upload   Total   SpentLeft  Speed
100 41.6M  100 41.6M0 0  6578k  0  0:00:06  0:00:06 --:--:-- 8297k
  % Total% Received % Xferd  Average Speed   TimeTime Time  Current
 Dload  Upload   Total   SpentLeft  Speed
100   836  100   8360 0   1012  0 --:--:-- --:--:-- --:--:--  1012
  % Total% Received % Xferd  Average Speed   TimeTime Time  Current
 Dload  Upload   Total   SpentLeft  Speed
10034  100340 0 46  0 --:--:-- --:--:-- --:--:--46
  % Total% Received % Xferd  Average Speed   TimeTime Time  Current
 Dload  Upload   Total   SpentLeft  Speed
100 56.4M  100 56.4M0 0  3950k  0  0:00:14  0:00:14 --:--:-- 4742k
  % Total% Received % Xferd  Average Speed   TimeTime Time  Current
 Dload  Upload   Total   SpentLeft  Speed
100   836  100   8360 0   1470  0 --:--:-- --:--:-- --:--:--  1469
  % Total% Received % Xferd  Average Speed   TimeTime Time  Current
 Dload  Upload   Total   SpentLeft  Speed
10034  100340 0 65  0 --:--:-- --:--:-- --:--:--65
LMC-053601:apache-tika-1.16-rc1 mattmann$ $HOME/bin/stage_apache_rc tika 
1.16-src https://dist.apache.org/repos/dist/dev/tika/
  % Total% Received % Xferd  Average Speed   TimeTime Time  Current
 Dload  Upload   Total   SpentLeft  Speed
100 84.2M  100 84.2M0 0  6563k  0  0:00:13  0:00:13 --:--:-- 5261k
  % Total% Received % Xferd  Average Speed   TimeTime Time  Current
 Dload  Upload   Total   SpentLeft  Speed
100   836  100   8360 0   2129  0 --:--:-- --:--:-- --:--:--  2127
  % Total% Received % Xferd  Average Speed   TimeTime Time  Current
 Dload  Upload   Total   SpentLeft  Speed
10034  100340 0 47  0 --:--:-- --:--:-- --:--:--47
LMC-053601:apache-tika-1.16-rc1 mattmann$ ls
tika-1.16-src.zip   tika-app-1.16.jar   
tika-eval-1.16.jar  tika-server-1.16.jar
tika-1.16-src.zip.asc   tika-app-1.16.jar.asc   
tika-eval-1.16.jar.asc  tika-server-1.16.jar.asc
tika-1.16-src.zip.md5   tika-app-1.16.jar.md5   
tika-eval-1.16.jar.md5  tika-server-1.16.jar.md5
LMC-053601:apache-tika-1.16-rc1 mattmann$ $HOME/bin/verify_gpg_sigs
Verifying Signature for file tika-1.16-src.zip.asc
gpg: assuming signed data in `tika-1.16-src.zip'
gpg: Signature made Fri Jul  7 19:27:42 2017 PDT using RSA key ID EF0CF38A
gpg: Good signature from "Tim Allison (ASF signing key) "
gpg: WARNING: This key is not certified with a trusted signature!
gpg:  There is no indication that the signature belongs to the owner.
Primary key fingerprint: 833C 1CC4 926C 1DDE 29BB  8731 E403 2DC4 EF0C F38A
Verifying Signature for file tika-app-1.16.jar.asc
gpg: assuming signed data in `tika-app-1.16.jar'
gpg: Signature made Fri Jul  7 19:13:16 2017 PDT using RSA key ID EF0CF38A
gpg: Good signature from "Tim Allison (ASF signing key) "
gpg: WARNING: This key is not certified with a trusted signature!
gpg:  There is no indication that the signature belongs to the owner.
Primary key fingerprint: 833C 1CC4 926C 1DDE 29BB  8731 E403 2DC4 EF0C F38A
Verifying Signature for file tika-eval-1.16.jar.asc
gpg: assuming signed data in `tika-eval-1.16.jar'
gpg: Signature made Fri Jul  7 19:20:17 2017 PDT using RSA key ID EF0CF38A
gpg: Good signature from "Tim Allison (ASF signing key) "
gpg: WARNING: This key is not certified with a trusted signature!
gpg:  There is no

[jira] [Commented] (TIKA-1367) Tika documentation should list tika-parsers parser dependencies

2017-07-08 Thread Gus Heck (JIRA) 

[ 
https://issues.apache.org/jira/browse/TIKA-1367?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16079164#comment-16079164
 ] 

Gus Heck commented on TIKA-1367:


Update... I did start making test cases, but this may have been a matter of my 
artifactory instance behaving strangely. I'm seeing different results with 
mavenCentral() directly... it was supposedly proxying central transparently, 
but perhaps not quite. 

> Tika documentation should list tika-parsers parser dependencies
> ---
>
> Key: TIKA-1367
> URL: https://issues.apache.org/jira/browse/TIKA-1367
> Project: Tika
>  Issue Type: Improvement
>  Components: documentation
>Reporter: Sergey Beryozkin
> Fix For: 1.17
>
>
> tika-parsers module has many strong transitive parser dependencies. Maven 
> users of tika-parsers have to exclude all the transitivie dependencies 
> manually. Documenting the list of the existing transitive dependencies and 
> keeping the list up to date will help developers exclude the libraries not 
> needed for a given project.



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[jira] [Commented] (TIKA-2262) Supporting Image-to-Text (Image Captioning) in Tika for Image MIME Types

2017-07-08 Thread ASF GitHub Bot (JIRA) 

[ 
https://issues.apache.org/jira/browse/TIKA-2262?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16079096#comment-16079096
 ] 

ASF GitHub Bot commented on TIKA-2262:
--

ThejanW commented on issue #189: Fix for TIKA-2262: Supporting Image-to-Text 
(Image Captioning) in Tika
URL: https://github.com/apache/tika/pull/189#issuecomment-313850196
 
 
   @thammegowda @chrismattmann please merge my commits so I can proceed.
 

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> Supporting Image-to-Text (Image Captioning) in Tika for Image MIME Types
> 
>
> Key: TIKA-2262
> URL: https://issues.apache.org/jira/browse/TIKA-2262
> Project: Tika
>  Issue Type: Improvement
>  Components: parser
>Reporter: Thamme Gowda
>Assignee: Thamme Gowda
>  Labels: deeplearning, gsoc2017, machine_learning
>
> h2. Background:
> Image captions are a small piece of text, usually of one line, added to the 
> metadata of images to provide a brief summary of the scenery in the image. 
> It is a challenging and interesting problem in the domain of computer vision. 
> Tika already has a support for image recognition via [Object Recognition 
> Parser, TIKA-1993| https://issues.apache.org/jira/browse/TIKA-1993] which 
> uses an InceptionV3 model pre-trained on ImageNet dataset using tensorflow. 
> Captioning an image is a very useful feature since it helps text based 
> Information Retrieval(IR) systems to "understand" the scenery in images.
> h2. Technical details and references:
> * Google has long back open sourced their 'show and tell' neural network and 
> its model for autogenerating captions. [Source Code| 
> https://github.com/tensorflow/models/tree/master/im2txt], [Research blog| 
> https://research.googleblog.com/2016/09/show-and-tell-image-captioning-open.html]
> * Integrate it the same way as the ObjectRecognitionParser
> ** Create a RESTful API Service [similar to this| 
> https://wiki.apache.org/tika/TikaAndVision#A2._Tensorflow_Using_REST_Server] 
> ** Extend or enhance ObjectRecognitionParser or one of its implementation
> h2. {skills, learning, homework} for GSoC students
> * Knowledge of languages: java AND python, and maven build system
> * RESTful APIs 
> * tensorflow/keras,
> * deeplearning
> 
> Alternatively, a little more harder path for experienced:
> [Import keras/tensorflow model to 
> deeplearning4j|https://deeplearning4j.org/model-import-keras ] and run them 
> natively inside JVM.
> h4. Benefits
> * no RESTful integration required. thus no external dependencies
> * easy to distribute on hadoop/spark clusters
> h4. Hurdles:
> * This is a work in progress feature on deeplearning4j and hence expected to 
> have lots of troubles on the way! 



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[jira] [Commented] (TIKA-2262) Supporting Image-to-Text (Image Captioning) in Tika for Image MIME Types

2017-07-08 Thread ASF GitHub Bot (JIRA) 

[ 
https://issues.apache.org/jira/browse/TIKA-2262?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16079095#comment-16079095
 ] 

ASF GitHub Bot commented on TIKA-2262:
--

ThejanW commented on issue #189: Fix for TIKA-2262: Supporting Image-to-Text 
(Image Captioning) in Tika
URL: https://github.com/apache/tika/pull/189#issuecomment-313850148
 
 
   @tballison I could fix the maven import errors, then there was error 
`TensorflowRESTCaptioner is not abstract and does not override abstract method 
checkInitialization(org.apache.tika.config.InitializableProblemHandler) in 
org.apache.tika.config.Initializable`
   
   I had to put this in TensorflowRESTCaptioner to get rid of the error.
   `@Override
   public void checkInitialization(InitializableProblemHandler handler) 
throws TikaConfigException {
   }`
 

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> Supporting Image-to-Text (Image Captioning) in Tika for Image MIME Types
> 
>
> Key: TIKA-2262
> URL: https://issues.apache.org/jira/browse/TIKA-2262
> Project: Tika
>  Issue Type: Improvement
>  Components: parser
>Reporter: Thamme Gowda
>Assignee: Thamme Gowda
>  Labels: deeplearning, gsoc2017, machine_learning
>
> h2. Background:
> Image captions are a small piece of text, usually of one line, added to the 
> metadata of images to provide a brief summary of the scenery in the image. 
> It is a challenging and interesting problem in the domain of computer vision. 
> Tika already has a support for image recognition via [Object Recognition 
> Parser, TIKA-1993| https://issues.apache.org/jira/browse/TIKA-1993] which 
> uses an InceptionV3 model pre-trained on ImageNet dataset using tensorflow. 
> Captioning an image is a very useful feature since it helps text based 
> Information Retrieval(IR) systems to "understand" the scenery in images.
> h2. Technical details and references:
> * Google has long back open sourced their 'show and tell' neural network and 
> its model for autogenerating captions. [Source Code| 
> https://github.com/tensorflow/models/tree/master/im2txt], [Research blog| 
> https://research.googleblog.com/2016/09/show-and-tell-image-captioning-open.html]
> * Integrate it the same way as the ObjectRecognitionParser
> ** Create a RESTful API Service [similar to this| 
> https://wiki.apache.org/tika/TikaAndVision#A2._Tensorflow_Using_REST_Server] 
> ** Extend or enhance ObjectRecognitionParser or one of its implementation
> h2. {skills, learning, homework} for GSoC students
> * Knowledge of languages: java AND python, and maven build system
> * RESTful APIs 
> * tensorflow/keras,
> * deeplearning
> 
> Alternatively, a little more harder path for experienced:
> [Import keras/tensorflow model to 
> deeplearning4j|https://deeplearning4j.org/model-import-keras ] and run them 
> natively inside JVM.
> h4. Benefits
> * no RESTful integration required. thus no external dependencies
> * easy to distribute on hadoop/spark clusters
> h4. Hurdles:
> * This is a work in progress feature on deeplearning4j and hence expected to 
> have lots of troubles on the way! 



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