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https://issues.apache.org/jira/browse/TIKA-2322?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15990856#comment-15990856
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ASF GitHub Bot commented on TIKA-2322:
--------------------------------------
chrismattmann commented on a change in pull request #175: TIKA-2322: update
dockerfile
URL: https://github.com/apache/tika/pull/175#discussion_r114130580
##########
File path:
tika-parsers/src/main/resources/org/apache/tika/parser/recognition/tf/InceptionVideoRestDockerfile
##########
@@ -60,7 +57,7 @@ RUN cmake -D CMAKE_BUILD_TYPE=RELEASE \
-D INSTALL_C_EXAMPLES=OFF \
-D OPENCV_EXTRA_MODULES_PATH=../../opencv_contrib-3.2.0/modules \
-D BUILD_EXAMPLES=ON ..
-RUN make -j4
+RUN make -j8
Review comment:
no, this is what caused it to use too much disk/memory, so not going to
change this to 8.
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> 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
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