SMILA Pipelet for communicating with LikeLines servers
License
ShinNoNoir/likelines-smila
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
master
Could not load branches
Nothing to show
Could not load tags
Nothing to show
{{ refName }}
default
Name already in use
A tag already exists with the provided branch name. Many Git commands accept both tag and branch names, so creating this branch may cause unexpected behavior. Are you sure you want to create this branch?
Code
-
Clone
Use Git or checkout with SVN using the web URL.
Work fast with our official CLI. Learn more.
- Open with GitHub Desktop
- Download ZIP
Sign In Required
Please sign in to use Codespaces.
Launching GitHub Desktop
If nothing happens, download GitHub Desktop and try again.
Launching GitHub Desktop
If nothing happens, download GitHub Desktop and try again.
Launching Xcode
If nothing happens, download Xcode and try again.
Launching Visual Studio Code
Your codespace will open once ready.
There was a problem preparing your codespace, please try again.
Latest commit
Git stats
Files
Failed to load latest commit information.
Type
Name
Latest commit message
Commit time
LikeLines pipelet for SMILA 1.1. Computes the top <n> most interesting keyframes of the video denoted by the parameter <input_field> using the LikeLines server <server> and stores the time-codes of the keyframes as a sequence in the attribute <output_field>. ============ Configuring ============ In order to have the SMILA pipelet invoke content analysis on videos, the LLIndexer component needs to be configured. Please see configuration/README.txt for more information. ============ Testing ============ To test the pipelet, copy the BPEL file (LikeLinesPipeline.bpel) to your BPEL container folder of SMILA.Application and add the following lines to the deploy.xml file: <process name="proc:LikeLinesPipeline"> <in-memory>true</in-memory> <provide partnerLink="Pipeline"> <service name="proc:LikeLinesPipeline" port="ProcessorPort" /> </provide> </process> Then, open the Run or Debug Configurations window in Eclipse and check the bundle. Run SMILA. When it is ready, use a REST client to interact with SMILA: URL: http://localhost:8080/smila/pipeline/LikeLinesPipeline/process METHOD: POST REQUEST BODY: { "Text": "Some record", "youtube_id": "YouTube:wPTilA0XxYE" } RESULT (example): { "Text": "Some record", "youtube_id": "YouTube:wPTilA0XxYE", "_recordid": "LikeLinesPipeline-800097b9-62e4-4a7b-aab4-fba8d0df06c7", "topkeyframes": [ 63 ], "topkeyframes_jpg": [ "...base64 encoded jpg..." ] } Note that the field "topkeyframes_jpg" is only available if the video has been indexed and is still in the cache. Also, if frame extraction fails for one of the frames, the corresponding entry will be an empty string. Alternatively, if you're running SMILA 1.2, you can also test the pipelet in isolation using the following REST request: URL: http://localhost:8080/smila/pipelets/cubrikproject.tud.likelines.pipelets.LikeLines/process METHOD: POST REQUEST BODY: { "_configuration": { "server": "http://likelines-shinnonoir.dotcloud.com", "input_field": "youtube_id", "n": 3, "output_field": "topkeyframes", "output_frames_field": "topkeyframes_jpg" }, "Text": "Some record", "youtube_id": "YouTube:wPTilA0XxYE" } RESULT (example): { "_configuration": { "server": "http://likelines-shinnonoir.dotcloud.com", "input_field": "youtube_id", "n": 3, "output_field": "topkeyframes" }, "Text": "Some record", "youtube_id": "YouTube:wPTilA0XxYE", "_recordid": "cubrikproject.tud.likelines.pipelets.LikeLines-9e816aa0-3ca9-40de-aaa0-aed857e26291" "topkeyframes": [ 63, 2, 37 ], "topkeyframes_jpg": [ "...base64 encoded jpg...", "...base64 encoded jpg...", "...base64 encoded jpg..." ] }
About
SMILA Pipelet for communicating with LikeLines servers
Resources
License
Stars
Watchers
Forks
Releases
No releases published
Packages 0
No packages published