Segments.ai July update: Automated Labeling Workflows with Webhooks

By Bert De Brabandere on August 1st, 2021

Segments.ai July update: Automated Labeling Workflows with Webhooks

Summer break or not, we keep shipping new features at Segments.ai. Our highlight for this month is the release of the new webhook functionality, which makes it even easier to set up automated labeling workflows.

Introducing webhooks

Webhooks are automated messages sent to your server when something happens. You can use webhooks to subscribe to certain events on your account and automatically trigger reactions.

For example, you could set up a workflow such that when an image is labeled on Segments.ai, the label is copied to your own database immediately. This is especially useful for real-time applications, compared to listening for changes by periodically polling an API endpoint.

Other examples include sending a Slack message when someone creates an issue, triggering a prediction pipeline in Apache Airflow when a new image is added to a dataset or returning the result from a labeling job to your customer in real-time.

Find out how to enable webhooks in our docs, and let us know how you will be using this new functionality!

Set up a Slack integration with webhooks.

⭐️ New features and improvements

  • When labeling, you can now quick-select categories with number hotkeys
  • When labeling, you can now redo changes with Ctrl+Y
  • The undo functionality is now improved when labeling in polygon mode in the segmentation interface
  • On the samples tab, you can now also upload images by dragging them onto the screen
  • You can now copy the dataset name by clicking a copy-to-clipboard button next to the dataset name in the dataset overview page
  • You can now copy an image name and/or download the image by clicking the respective buttons next to the image name in the interface
  • The labeling progress of a dataset is now also displayed in the list of datasets
  • You can now see at a glance who has reviewed an image in the interface
  • Rejected images now go back to their original labeler, and once corrected they go back to the original reviewer for the follow-up review.
  • Performance of some API endpoints is improved, leading to faster load times
  • Python SDK:
    • Can now be installed on Windows
    • Added export options for (colored) instance and semantic PNGs

Other features.

🔨 Bug fixes

  • Fixed issue with label queue when multiple labelsets are present
  • Fixed issue with exporting to coco panoptic format in the Python SDK
  • Fixed display of NaN value for dataset labeling progress

Stay tuned for our next newsletter with more product updates!

Bert
Bert De Brabandere
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