- Auto-segment 2.0, powered by Meta's Segment Anything model, helps you draw draw segmentation masks much faster in the image editor. To use this new feature, you can use:
- Hover-and-click: When you hover over your image in the editor, Labelbox highlights the object underneath the cursor. Select the highlighted object to create a segmentation mask.
- Box mode: Draw a bounding box over an object in the image to automatically create a segmentation mask over the object.
- You can now use a brush tool to draw segmentation masks in the image editor. You can adjust the size and shape of the brush.
- Our new LLM data generation editor lets you prepare a dataset of prompts and responses to fine-tune large language models (LLMs).
- The Performance dashboard has been improved to be more reliable and offers more metrics.
Note: Performance dashboard updates are being rolled out gradually. If you do not see the changes at this time, check again in a day or two.
The latest version of our Python SDK is v3.49.0. See our full changelog in Github for more details on what was added recently.
- Improved batch creation logic when more than 1000 global keys provided
- Added example on how to access mark in export v2
- Removed NDJSON library from
- Support for ISO format to exports V2 date filters
- Support to specify confidence for all free-text annotations
- Removed backports library and replaced it with python dateutil package to parse iso strings
- Added predictions to model run example
- Added notebook to run yolov8 and sam on video and upload to LB
- Updated google colab notebooks to reflect raster segmentation tool being released on 6/13
- Updated radio NDJSON annotations format to support confidence
- Added confidence to all free-text annotations (ndjson)
- Fixed issues with cv2 library rooting from the Geospatial notebook used a png map with a signed URL with an expired token