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Product Updates [November 2023]

December 7, 2023
5 mins
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Upgraded workflows, improved bitmask and DICOM editor, a new automated labeling system, and an enhanced interface between Annotate and Active round out November with Encord. Looking forward to the holidays ahead!



Workflows - the new Task Management System

Workflows graduated from Beta and are now the default task management system for all customers. Scaled to handle 500,000 tasks — workflows is your new go to for large-scale annotation projects. In addition to performance, Workflows enjoy a significantly enhanced UX with a new template editor and easy-to-use task queue, now with priorities!

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Of course — no matter the priority, some tasks can still pose a problem — corrupted data and unclear annotation instructions are among the main reasons annotators might need to skip a task until later. Fortunately, workflows will enhance collaboration by prompting the annotator to clearly explain why the task is being skipped for clear communication with the labeling manager.

Redesigned Bitmask Tool

We're thrilled to announce upgrades to the threshold brush tool for bitmask labels! In addition to B/W (black and white) say hello to RGB (red/green/blue) and HSV (hue/saturation/values) thresholds - allowing you to target specific color ranges with ease. And to make sure you’re labeling what you think you are, the threshold preview has evolved to keep pace. You can now preview your work in transparent and inverted modes in addition to B/W. Whether you're fine-tuning reds, greens, blues, or playing with hues, saturations, and values, these new options make sure bitmask labeling can fit your data.

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Combine the above threshold range improvements with our bitmask lock feature, which allows you to designate that certain bitmask labels should not overlap. Our bitmask brush is now the perfect tool to ensure perfect annotation coverage per frame.

Encord Active - Supporting Nested Attributes, Custom Metadata, Priorities

Encord Active is improving across the board. We have extended support for custom metadata which means you can now filter your images/videos based on all the extra information associated with your data such as location, time of day, or anything else you might have available. Simultaneously we added the option to filter your classes based on all the nested attributes in your label ontology on the Encord platform.

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Pair these enhanced filtering capabilities with improved synergy between Active <> Annotate and you have a fully featured computer vision data platform. Among the headline improvements in November were the ability to create datasets with only specific frames from videos and image groups and send bulk or individual comments to Annotate. Coming soon, adjust priorities, bulk classification, and much more — contact us to learn how Encord Active can help you label the right data faster.

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The world of DICOM imaging is sprawling with various stakeholders and implementations. While it’s great to have so many organisations working together, in practice it means there may be difficulties handling various interpretations or small inconsistencies. To alleviate these pains, we're excited to announce a significant upgrade to our DICOM parsing capabilities! We’re introducing a new parser which extends our compatibility capabilities as well as increasing DICOM performance in the browser! In addition, we are enhancing our Multiplanar Reconstruction (MPR) capabilities — we’re making it possible to create bitmask annotations in the reconstructed views. With MPR Annotations you can now view and annotate from the best angle — giving you the power to annotate accurately and efficiently.

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Introducing VLM Automated Labeling

You may have seen OpenAI’s exciting announcement about GPT 4 Vision, and if you’re anything like us, you were probably thinking something like: ”how can we leverage this to accelerate annotation?” 🤔 After some thinking, we’re happy to introduce our new VLM prediction feature! Currently available for classifications, our VLM prediction tool is a new repertoire in automated labelling which understands the content of the image and automatically creates the appropriate classifications from your ontology. Contact us to discuss if it’s right for your use case, and watch this space as we expand our automated labelling capabilities going forward!

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Written by

Justin Sharps

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