tika-dev mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From "ASF GitHub Bot (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (TIKA-2322) Video labeling using existing ObjectRecognition
Date Thu, 27 Apr 2017 03:37:04 GMT

    [ https://issues.apache.org/jira/browse/TIKA-2322?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15985941#comment-15985941
] 

ASF GitHub Bot commented on TIKA-2322:
--------------------------------------

chrismattmann commented on issue #168: fix for TIKA-2322 contributed by msharan@usc.edu
URL: https://github.com/apache/tika/pull/168#issuecomment-297602511
 
 
   @thammegowda can you take a look here. I can't access the server on 8764:
   
   h3. Docker quick start terminal
   ```
   LMC-053601:tf mattmann$ docker run -p 8764:8764 -it inception-rest-tika
   >> Downloading inception_v4_2016_09_09.tar.gz 100.0%
   Successfully downloaded inception_v4_2016_09_09.tar.gz 171177982 bytes.
   >> Downloading imagenet_lsvrc_2015_synsets.txt 163.8%
   Successfully downloaded imagenet_lsvrc_2015_synsets.txt 10000 bytes.
   >> Downloading imagenet_metadata.txt 100.5%
   Successfully downloaded imagenet_metadata.txt 741401 bytes.
   W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled
to use SSE3 instructions, but these are available on your machine and could speed up CPU computations.
   W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled
to use SSE4.1 instructions, but these are available on your machine and could speed up CPU
computations.
   W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled
to use SSE4.2 instructions, but these are available on your machine and could speed up CPU
computations.
   W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled
to use AVX instructions, but these are available on your machine and could speed up CPU computations.
   Serving on port 8764
    * Running on http://0.0.0.0:8764/ (Press CTRL+C to quit)
   ```
   
   h3. Docker client (separate terminal)
   
   ```
   LMC-053601:tf mattmann$ curl "http://localhost:8764/inception/v4/classify?topk=2&url=https://upload.wikimedia.org/wikipedia/commons/f/f6/Working_Dogs%2C_Handlers_Share_Special_Bond_DVIDS124942.jpg"
   curl: (7) Failed to connect to localhost port 8764: Connection refused
   LMC-053601:tf mattmann$ 
   ```
 
----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on GitHub and use the
URL above to go to the specific comment.
 
For queries about this service, please contact Infrastructure at:
users@infra.apache.org


> Video labeling using existing ObjectRecognition
> -----------------------------------------------
>
>                 Key: TIKA-2322
>                 URL: https://issues.apache.org/jira/browse/TIKA-2322
>             Project: Tika
>          Issue Type: Improvement
>          Components: parser
>            Reporter: Madhav Sharan
>            Assignee: Chris A. Mattmann
>              Labels: memex
>             Fix For: 1.15
>
>
> Currently TIKA supports ObjectRecognition in Images. I am proposing to extend this to
support videos. 
> Idea is -
> 1. Extract frames from video and run IncV3 to get labels for these frames. 
> 2. We average confidence scores of same labels for each frame. 
> 3. Return results in sorted order of confidence score. 
> I am writing code for different modes of frame extractions -
> 1. Extract center image.
> 2. Extract frames after every fixed interval.
> 3. Extract N frames equally divided across video.
> We used this approach in [0]. Code in [1]
> [0] https://github.com/USCDataScience/hadoop-pot
> [1] https://github.com/USCDataScience/video-recognition



--
This message was sent by Atlassian JIRA
(v6.3.15#6346)

Mime
View raw message