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A method to flatten generated JSON data into timed CSV events in support of analytic workflows within the ContentAI Platform.

1.4

1.4.0

  • fix for timing offsets; don't overwrite any output if timing offset indicator

1.3

1.3.3

  • minor fix for azure_videoindexer parsing, now first video shot can not contain a keyframe ?

1.3.2

  • minor fix for gcp_videointelligence_text_detection parsing

1.3.1

  • fix for no-output generators
  • fix complete output for returned dictionary of data
  • add richer documentation for library/api usage

1.3.0

  • update output of main parse function to return a dict instead of file listing
  • modify generator specification to allow ALL (* default) or NONE for outputs

1.2

1.2.2

  • add parsers for gcp_videointelligence_text_detection, comskip_json, ibm_max_audio_classifier,
    gcp_videointelligence_object_tracking, gcp_videointelligence_people_detection
  • improve testing to iterate over known set of data in testing dir
  • fix generator/parser retrieve for whole name matches, not partials
  • add documentation for new types, explicitly call out person tag_type
  • update the dsai_activity_emotions parser to return tag type emotion (matching that of other AWS, Azure parsers)

1.2.1

  • update azure_videoindexer for tag_type in detected brands (was speech, now video)

1.2.0

  • add unit-testing to package build
  • add command-line / parser input as complement to contentai-driven ENV variables
  • fix bugs around specification of result path or specific generator

1.1

1.1.8

  • fix issue about constant reference
  • fix run_local.sh script for extra run param config
  • fix querying for local files in non-contentai environments (regression since 1.1.0)

1.1.7

  • inclusion of other constants for compatibility with other packages
  • refactor/rename of parser classes to mandate a filename output prefix (e.g. flatten_)
  • add dsai_activity_emotions parser (a clone of dsai_activity_classifier)

1.1.6

1.1.4

  • name update for dsai_moderation_image extractor

1.1.3

  • hotfix for build distribution
  • fix for content creation in streamlit/browsing app

1.1.2

  • deployed extractor (docker fix) for updated namespace

1.1.1

  • docs update, testing fixes, version bump for publication

1.1.0

  • rename to contentai-metadata-flatten and publish to pypi as a package!

1.0

1.0.2

1.0.1

  • add ability to parse input CSVs but not segment into shot
  • move to a single NLP library (spacy) for applications, using large model (with vectors)

1.0.0

0.9

0.9.9

  • update to optimize the pull of asset keys

0.9.7

0.9.6

0.9.6

  • small tweaks/normalization of rounding factor for extractors
  • correct emotion souce type for azure
  • refactor app location for primary streamlit browser - fix mode discovery for modules with specific UX interface
  • update file listing to show data bundle files as well
  • refactor utilities script for reuse in other apps

0.9.5

  • update to parse new version of dsai_places
  • add new parser for detectron2 extractor

0.9.4

  • add static file serving to streamlit app, inspired by this streamlit issue discussion
  • modify some pages to point to downloadable tables (with button click)
  • create new download page/mode that lists the generated and source files
  • minor refactor of app's docker image for better caching in local creation and testing

0.9.3

  • add dsai_moderation_text parser, update dsai_moderation parser for version robustness - add min threshold (0.05) to both moderation detectors

0.9.2

  • add recursion to file-based discovery method for processed assets - unify read of JSON and text files with internalaized function call in extractor base class
  • fix some extractors to use single name reference self.EXTRACTOR

0.9.1

  • fix transcript parsing in azure_videoindexer component
  • add speaker differentiation as an identity block in azure_videoindexer (similar to aws_transcribe)

0.9.0

  • add timeline viewing to the event_table mode of streamlit app

0.8

0.8.9

  • fixes to main streamlit app for partial extractors (e.g. missing identity, sparse brand)

0.8.8

  • add parser for dsai_moderation

0.8.7

  • add parser for dsai_activity_classifier
  • fix bug for faulty rejection of flatten_aws_transcribe results

0.8.6

  • add parsers for pyscenedetect, dsai_sceneboundary, aws_transcribe, yolo3, aws_rekognition_video_text_detect
  • add speaker identity (from speech) to gcp_videointelligence_speech_transcription
  • add type field (maps to tag_type) to output generated by wbTimeTaggedTmetadata generator - add hashing against data (e.g. box) within JSON metadata generator

0.8.5

  • add parsers for dsai_yt8m (youtube8M or mediapipe)

0.8.4

  • add parsers for dsai_activity_slowfast (activity) and dsai_places (scene/settings)
  • add source_type sub-field to event_table browsing mode

0.8.3

  • add manifest option to application for multiple assets
  • fix app docker file for placement/generation of code with a specific user ID
  • fix CI/CD integration for auto launch
  • fix app explorer bugs (derive 'words' from transcript/keywords if none)

0.8.2

  • hotfix for missing data in dsai_metadata parser

0.8.2

  • slight refactor of how parsers are discovered, to allow search by name or type (for use as package)
  • fix package import for contentai local file
  • switch tag_type of ocr to transcript and ocr for source_type (azure_videoindexer)

0.8.1

  • adding music parser dsai_musicnn for different audio regions

0.8.0

  • convert to package for other modules to install
  • switch document to RST from MD
  • add primitive testing capabilities (to be filled)

0.7

0.7.1

  • added truncation/trim of events before zero mark if time offset is negative
  • re-brand extractor as dsai_metadata_flatten for ownership consistency

0.7.0

  • create new set of generator class objects for varying output generator
  • add new generator input for limiting output to a single type

0.6

0.6.2

  • rename rekognition_face_collection to aws_rekognition_face_collection for consistency

0.6.1

  • split documentation and changes
  • add new cae_metadata type of parser
  • modify source_type of detected faces in azure_videoindexer to face
  • modify to add new extractor input for limit to scanning (skips sub-dir check)

0.6.0

  • adding CI/CD script for gitlab
  • validate usage as a flattening service
  • modify source_type for aws_rekognition_video_celebs to face

0.5

0.5.4

  • adding face_attributes visualization mode for exploration of face data
  • fix face processing to split out to tag_type as face with richer subtags

0.5.3

  • add labeling component to application (for video/image inspection)
  • fix shot duration computeation in application (do not overwrite original event duration)
  • add text-search for scanning named entities, words from transcript

0.5.2

  • fix bugs in gcp_videointelligence_logo_recognition (timing) and aws_rekognition_video_faces (face emotions)
  • add new detection of timing.txt for integration of multiple results and their potential time offsets
  • added verbose flag to input of main parser
  • rename rekognition_face_collection for consistency with other parsers

0.5.1

  • split app modules into different visualization modes (overview, event_table, brand_expansion)
    • brand_expansion uses kNN search to expand from shots with brands to similar shots and returns those brands
    • event_table allows specific exploration of identity (e.g. celebrities) and brands witih image/video playback
    • NOTE The new application requires scikit-learn to perform live indexing of features
  • dramatically improved frame targeting (time offset) for event instances (video) in application

0.5.0

  • split main function into sepearate auto-discovered modules
  • add new user collection detection parser rekognition_face_collection (custom face collections)

0.4

0.4.5

  • fixes for gcp moderation flattening
  • fixes for app rendering (switch most graphs to scatter plot)
  • make all charts interactive again
  • fix for time zone/browser challenge in rendering

0.4.4

  • fixes for azure_videoindexer parser
  • add sentiment and emotion summary
  • rework graph generation and add bran/entity search capability

0.4.3

  • add new azure_videoindexer parser
  • switch flattened reference from logo to brand; explicit to moderation
  • add parsing library pytimeparse for simpler ingest
  • fix bug to delete old data bundle if reference files are available

0.4.2

  • add new time_offset parameter to environment/run configuration
  • fix bug for reusing/rewriting existing files
  • add output prefix flatten_ to all generated CSVs to avoid collision with other extractor input

0.4.1

  • fix docker image for nlp tasks, fix stop word aggregation

0.4.0

  • adding video playback (and image preview) via inline command-line execution of ffmpeg in application
  • create new Dockerfile.app for all-in-one explorer app creation

0.3

0.3.2

  • argument input capabilities for exploration app
  • sort histograms in exploration app by count not alphabet

0.3.1

  • browsing bugfixes for exploration application

0.3.0

  • added new streamlit code for data explorer interface
    • be sure to install extra packages if using this app and starting from scratch (e.g. new flattened files)
    • if you’re working from a cached model, you can also drop it in from a friend

0.2

0.2.1

  • schema change for verb/action consistency time_start -> time_begin
  • add additional row field tag_type to describe type of tag (see generated-insights)
  • add processing type gcp_videointelligence_logo_recognition
  • allow compression as a requirement/input for generated files (compressed as input)

0.2.0

  • add initial package, requirements, docker image
  • add basic readme for usage example
  • processes types gcp_videointelligence_label, gcp_videointelligence_shot_change, gcp_videointelligence_explicit_content, gcp_videointelligence_speech_transcription, aws_rekognition_video_content_moderation, aws_rekognition_video_celebs, aws_rekognition_video_labels, aws_rekognition_video_faces, aws_rekognition_video_person_tracking,