Labelbox•November 29, 2022
You can now optimize model-assisted labeling, better queue and review your data rows, and more.
Automating your data labeling process is not only a key component of an effective data engine, but is key to producing high-quality data, fast.
Learn more about the automation efficiency score in a recent blog post.
A vital aspect of a data engine involves the creation of large volumes of high-quality training data. Often, AI teams struggle to prioritize the right data to label and end up spending more money on data labeling than they should.
To help you better queue, review, surface and prioritize your training data, Labelbox has begun to roll out configuring new projects with batches, custom workflows, and the Data Rows tab.
On November 21st, we released an update to Free, Education, and Starter users that automatically configured new projects with batch-based queueing, custom workflows, and the Data Rows tab.
Pro and Enterprise users can expect the same changes in mid-December.
To familiarize yourself with these new changes and workflows, please refer to the resources below:
The conversational text editor allows users to create unique message-based classifications that can identify user intent or sentiment.
Learn more about our conversational text editor or importing pre-labels in our documentation.
The document editor now supports text entity imports for NER, allowing you to import text entity annotations as pre-labels on their assets.
With this update, the document editor supports both imports for text entity and bounding box imports – you can use model-assisted labeling to dramatically decrease iteration cycles and the overall time taken to reach a performant model.
Learn more about our document editor or importing pre-labels in our documentation.
We now support up to 5,000 vector annotations (i.e point, line, box, polygon) in the image editor.
If you’re annotating large scale images with numerous labels, this allows you to annotate with ease with no slow down. Learn more in our documentation.
We recently released a new version of our Python SDK (see changelog here). It includes the following major updates:
Please use `pip install –upgrade labelbox` to upgrade to the latest version of the SDK.
Check out the latest tutorials & walkthroughs on how to effectively manage your labeling operations: