[ 
https://issues.apache.org/jira/browse/TIKA-2322?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15988234#comment-15988234
 ] 

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

chrismattmann commented on issue #168: fix for TIKA-2322 contributed by 
[email protected]
URL: https://github.com/apache/tika/pull/168#issuecomment-297910260
 
 
   talked to @smadha on GChat. Basically the issue is even in the current 
Docker file with Conda/OpenCV, etc., we can't get it to recognize the video 
file (FFMPEG + OpenCV, not working). I SSH'ed onto the docker machine:
   
   ```
   root@2156ca034e87:/# curl -LO 
https://github.com/smadha/tika/blob/TIKA-2322/tika-parsers/src/test/resources/test-documents/testVideoMp4.mp4?raw=true
     % Total    % Received % Xferd  Average Speed   Time    Time     Time  
Current
                                    Dload  Upload   Total   Spent    Left  Speed
   100   174    0   174    0     0    459      0 --:--:-- --:--:-- --:--:--   
519
   100   185  100   185    0     0    320      0 --:--:-- --:--:-- --:--:--   
320
   100 1028k  100 1028k    0     0   523k      0  0:00:01  0:00:01 --:--:--  
888k
   root@2156ca034e87:/# ls
   bin   c15fada28113eca32dc98d6e3bec4755d0d5b4c2.zip  etc   lib         media  
models-c15fada28113eca32dc98d6e3bec4755d0d5b4c2  proc  run   srv  
testVideoMp4.mp4?raw=true  usr
   boot  dev                                        home  lib64  mnt    opt     
                                         root  sbin  sys  tmp                   
     var
   root@2156ca034e87:/# mv testVideoMp4.mp4\?raw\=true testVideoMp4.mp4
   root@2156ca034e87:/# ls
   bin   c15fada28113eca32dc98d6e3bec4755d0d5b4c2.zip  etc   lib         media  
models-c15fada28113eca32dc98d6e3bec4755d0d5b4c2  proc  run   srv  
testVideoMp4.mp4  usr
   boot  dev                                        home  lib64  mnt    opt     
                                         root  sbin  sys  tmp               var
   root@2156ca034e87:/# python
   Python 2.7.13 |Continuum Analytics, Inc.| (default, Dec 20 2016, 23:09:15) 
   [GCC 4.4.7 20120313 (Red Hat 4.4.7-1)] on linux2
   Type "help", "copyright", "credits" or "license" for more information.
   Anaconda is brought to you by Continuum Analytics.
   Please check out: http://continuum.io/thanks and https://anaconda.org
   >>> import cv2
   >>> cap = cv2.VideoCapture('testVideoMp4.mp4')
   >>> cap.isOpened()
   False
   >>> 
   root@2156ca034e87:/# ls
   bin   c15fada28113eca32dc98d6e3bec4755d0d5b4c2.zip  etc   lib         media  
models-c15fada28113eca32dc98d6e3bec4755d0d5b4c2  proc  run   srv  
testVideoMp4.mp4  usr
   boot  dev                                        home  lib64  mnt    opt     
                                         root  sbin  sys  tmp               var
   root@2156ca034e87:/# exit
   exit
   LMC-053601:tf mattmann$ 
   ```
   So, @smadha is going to try to build OpenCV with Python and FFMPEG support 
from source, and then include the instructions for that in the Docker. Any help 
from others is appreciated.
   
 
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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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