Head over to the Annotators section. Previously you could only see current image statuses. Now you will be abe to see the pass/reject rate over time as well as the overall dataset progress.
One highly requested feature is to allow manipulating the image's appearance. This means tweaking contrast, saturation, and the visibility of annotations.
You can now tweak these through an Image Manipulation panel on the top right. We will keep adding more ways to tweak images, including color channels and image overlays. If there is something you'd like to see when it comes to image manipulation let us know!
Late last month the Annotator tab became available, allowing you to monitor the performance of labelers across all datasets with granular detail.
We based this feature on your feedback, adding the ability to monitor:
- Images completed
- Labels completed
- Total time spent labeling
- Labels per second
- Accuracy score (based on review)
These metrics can be filtered by day, week, or month and are beautifully plotted on a comparable graph.
We've compacted (almost) everything you can do on the annotation workview in a short tutorial. We recommend trying this out if you are new to Darwin. It's now available for all teams in the Dataset Management tab.
You'll see a new tool appear by default in the annotation workview toolbar. You can select a region of an image to leave a comment in and start a thread. Other users, annotators, or reviewers can reply to it, or resolve it.
This should help streamline communication in very large datasets, and helps you trace back to comments you left as you will be notified when other users leave a reply. During review, you can leave a comment to explain what needs to be fixed so that annotators can learn where to improve.
Annotation comments are also useful in industries where experts need to be consulted, such as healthcare, where a comment annotation records an expert's opinion. You can try comments now on Darwin or check out the example video below