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Releases: HumanSignal/label-studio

Release 1.0.2

19 May 17:11
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1.0.2 release notes

Label Studio makes the master branch available as a stable beta at all times. This release includes bug fixes and improvements since 1.0.1 was released, but that were available to anyone using the Docker container or building from the Git repo directly.

New functionality

  • Use environment variables for specifying usernames and passwords when you restrict signup to be invite-only. See Restrict signup for cloud deployments in the Label Studio documentation.
  • Additional features after adding a machine learning backend, such as options for manual and automated retrieval of predictions, and the option to send a training signal to a connected ML backend when new annotations are submitted. See Set up machine learning with Label Studio.
  • CSV and other export formats from Label Studio now allow exporting an entire task with annotations and predictions. Thanks to @uriel-tannen for your issue requesting this.
  • Added draft annotation functionality, allowing you to switch between an in-progress annotation and a past annotation.
  • Added the ability to copy and edit an annotation in the Label Studio UI by clicking Create Copy when labeling.
  • Support Google Cloud Services credentials from the environment. Thanks to @lordzuko for a pull request with this bug fix and improvement!

Bug fixes

  • Fixed the PORT variable index in the example shell script for serving local files. Thanks @JustasB for the pull request!
  • Static files in the Label Studio container are now shared with the nginx container. Thanks to @nlml for the pull request!
  • Fixed an issue where a validation error prevents label deletion. Thanks @JustinGovender for your bug report!
  • Fixed distinct collaborators getting the same task in a project. Thanks to @rodrigocaus for the pull request!
  • Fixed an issue where S3 imported tasks were created with nested JSON files. Thanks to @yashwantkeswani for the pull request!
  • Fixed the path to the template assets. Thanks to @even-wei for the pull request!
  • Fixed an issue where seeking in audio files did not work as expected.
  • Improved the experience for adding local files as a source.
  • Fixed an issue where data files used an absolute path instead of a relative path. Thanks @jackklpan for the pull request!
  • Fixed an issue with Redis storage validation. Thanks to @jvdavim for your bug report.
  • Fixed an issue where filtering by numeric data types didn't work. Thanks to @dkalaitzidis for reporting this issue!
  • Fixed an issue where changing the filter field didn't affect the operator.

Other improvements

  • Updated the look and feel of the Label Studio UI.
  • Made it easier to see the task ID in the Label Studio UI.
  • Improved error messaging.
  • Improved API documentation.

Release 1.0.1

05 Apr 19:16
71278b0
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Improved functionality:

  • You can invite users to Label Studio instead of having them sign up. See Invite collaborators to a project.
  • Connect local directories to access files and labeling tasks stored locally or on remote servers. See Local storage.
  • Exported and stored annotations now include data about who completed the labeling task and created the annotation. Thanks to Uriel Tannen and others who requested this in Slack.

Fixed the following issues:

  • Hotkeys that weren't working
  • Issues preventing the data manager and the UI from loading
  • Cases where some data was not UTF-8-encoded, causing problems on some Windows machines. Thanks to @secslim for your PR!
  • Ordering by prediction score was not working.
  • Only the latest annotation would be exported, instead of all annotations for a task. Thanks to Uriel Tannen and others who reported this in Slack.
  • Deleting selected tasks deleted annotations from annotated tasks instead of deleting tasks and annotations. Thanks to @gamblard and @antonyscerri for reporting.

Release 1.0.0

16 Mar 16:37
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Label Studio has been rewritten to provide a streamlined UI, scalability, and support for multiple projects.

  • Multi-user labeling. Sign up and log in to Label Studio so that any annotations you create are tied to your account.
  • Multiple projects to allow you to annotate multiple datasets in parallel.
  • Project setup wizard to make it easier to start a new project and import your data.
  • Customize the labeling interface without editing the label config XML directly. Add labels and select the relevant fields in your data for the type of labeling you want to perform.
  • Database storage to allow you to scale your data labeling. Start with a SQLite database or set up PostgreSQL for large volume data labeling projects.
  • Django backend replaces the Flask backend.

Release 0.9.1.post1

18 Feb 16:42
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Fix LSF with TextArea editing mechanics
Fix labeling configs for NeMo
Fix predict drag&drop redirect on the model page

Release 0.9.1

16 Feb 23:32
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Cloud storage improvements

  • Set up Microsoft Azure as source or target storage for tasks and completions (@keesschollaart81).
  • Set up Redis as source or target storage for tasks and completions. (@kasuteru)
  • Added an option to set the Amazon AWS S3 endpoint with an environment variable when setting up cloud storage (@herber523).

See Cloud Storages.

Automated Speech Recognition with Nvidia NeMo ML backend

  • Added an example for Automatic Speech Recognition (ASR) machine learning backend using NVIDIA NeMo toolkit, including an ASR_MANIFEST export format.
  • Updated the Label Studio Frontend for textarea labeling to make it easier to update transcription labels.
  • Renamed the template "Whole Audio Transcription" to "Speech Transcription".

Other improvements

  • POST a label config as XML using the API (@laynr).
  • Add a while loop to check for more busy ports (@UtrechtUniversity).
  • Use pre-labeling to make predictions for specific tasks by ID.
  • No longer require tasks and completions to be ASCII-formatted, supporting non-ASCII languages like Persian (#578)
  • Improved the workflow for importing data to make it easier to fix label configuration errors.
  • Improved the timeseries data import flow to make it clearer how to import from text files.
  • Improved the multi-session mode experience.

Notable bug fixes

  • Fixed an issue where exported data would have duplicate completions.
  • Fixed a bug when uploading files in multi-session mode.
  • Improved handling of timeseries and polygon labels.
  • Fixed a bug where the .conll export format misses labels or assigns them to the subsequent token.

Release 0.9.0.post5

22 Jan 13:49
571ef26
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Fixes

  • Remove hostname prefix for upload files in case of localhost
  • Add timeout to version check (#560) (@LamDang)
  • Update requests dependency
  • Add list to Image in validation
  • Change attrs version to >=19.1.0
  • Add INIT_COMMAND to run.sh

Features

  • Add task patch API

Co-authored-by: LamDang tunglam.dang@gmail.com

Release 0.9.0.post4

19 Jan 00:44
7b56a66
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  • Add export format to filename
  • Fix name for predictions_score

Release 0.9.0.post3

16 Jan 00:09
707223a
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Fixes

  • Grid view cell number and not loading images
  • API import
  • AudioPlus in DM
  • Styles on storage errors
  • Import through API after files upload
  • Data type for config values

Release 0.9.0 - New Data Management

12 Jan 22:16
cc619f5
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  • New superior data manager with orderings, subset selectors, tabs, previews, and many other useful things
  • Enhanced import workflow
  • More stable cloud storages behaviour

Release 0.8.2

01 Dec 20:58
e34e4cd
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Paragraphs

Now you can label structured text in simple json format. Introducing Paragraphs!
It requires array of phrases, defined as object with two required fields:
first one for author (set by nameKey, "author" by default) and second one for text itself
(set by textKey, "text" by default). For better appearance use layout="dialogue".

Audio pre-listening

Also you can attach audio for these phrases by audioUrl.
It uses optional fields in phrases' objects: start and end/duration in seconds,
linking phrases with according part of audio.

Taxonomy

<Taxonomy> is a new control tag wrapper that allows you to build a nested choices structure - a multi-class classification tree. The usage is quite intuitive:

  <Taxonomy name="" toName="text">
    <Choice value="Archaea" />
    <Choice value="Bacteria" />
    <Choice value="Eukarya">
      <Choice value="Human" />
      <Choice value="Oppossum" />
      <Choice value="Extraterrestial" />
    </Choice>
  </Taxonomy>

Learn more by playing with Text taxonomy template on Setup page!

Undo/Redo/Reset

Now you can see the current state of your actions history — is it possible to undo/redo.
Also reset can be undone.
Both cmd+z and ctrl+z are working now.

TextArea regions

Improve text comments, especially multiline ones — they appears much better than before,
you can add them by shift+enter or cancel editing by escape.
Also you can delete classification comments with trash bin icon next to it.
And they will back to Regions list soon.

Machine Learning Backend Features

  • New ML backend for chatbot responses generation from <Paragraphs> (powered by HuggingFace's GPT2)

  • Project local path is accessible on ML backend API - in case you want to read uploaded images/audio directly from disk

New UI settings

  • Line numbers for Text/Paragraphs
  • Select region after create for better per-region labeling

Project sharing

Now it's possible to move and share the entire project folder and start annotations from any other path

Fixes

  • Restore region's text for NER labeling from data if it was missed
  • Display spinner while loading heavy TimeSeries
  • Return back onEntityDelete/onEntityCreate callbacks
  • Various fixes Image regions stability
  • Performance improvements for large regions numbers
  • Task IDs are now safely restored, even if you break or delete source.json
  • Get rid of some packages dependencies error
  • Export to VOC with broken image paths
  • Windows path for ML backend #500
  • Export to specific formats with relation results