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There are presently five working workflows: Transcript-NER-HMGM, Transcript-NER-no Human MGM, NER HMGM for Corrected Transcripts, Scene Detection with Contact Sheets, and Contact Sheets Only. The primary difference between the first two is that the former has human intervention at several steps to improve performance/the quality of the final deliverables. These workflows achieve two primary goals: generating a transcript (whether the transcript is human-edited or not), and recognizing named entities (people, places, etc.) in said transcript. The third, related to the former two, skips the transcript steps entirely, going directly to the named entity recognition steps. Scene Detection with Contact Sheets creates a contact sheet of video content by first automatically detecting shots using a Python library called PySceneDetect, then taking a frame in the middle of each of the said shots and placing them in order in a contact sheet. Contact Sheets Only creates only a contact sheet, taking frames from the video according to an arbitrary time interval.

The Dashboard

The dashboard Dashboard allows users both to find files that have already been submitted to a workflow, as well as track the progress of files in a workflow. It contains a fairly robust search feature that allows users to filter results in a multifaceted manner, as well as sort the results. The Dashboard by default displays all job steps by date in descending order, though you are able to sort by any column ascending or descending. Users are additionally able to export the data displayed on the Dashboard as a CSV file for easier analysis in software outside of AMP.

The attributes you are able both to filter and sort by are as follows:

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