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https://issues.apache.org/jira/browse/TIKA-2322?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15990043#comment-15990043
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ASF GitHub Bot commented on TIKA-2322:
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ThejanW commented on issue #168: fix for TIKA-2322 contributed by
msha...@usc.edu
URL: https://github.com/apache/tika/pull/168#issuecomment-298195464
Well, I built the image after replacing
https://github.com/smadha/tika/blob/TIKA-2322/tika-parsers/src/main/resources/org/apache/tika/parser/recognition/tf/InceptionVideoRestDockerfile#L26-L32
with ffmpeg build from source. unfortunately, no luck, still it gives me false
for "cap.isOpened()". The problem is OpenCV has to find FFMPEG on the given
system at **compile time** and generate links. Currently , Conda's pre-built
OpenCV package isn't compiled with ffmpeg support. They say ffmpeg is difficult
to support across platforms. So you are only left with a single solution, you
have to build OpenCV within docker.
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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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