February 15th, 2023

Changelog (v2.129.2)

[Python SDK] We’ve added two new methods: kili.inferences() and kili.predictions(). You can use them to get the list of labels that were created by ML models (inference or prediction label types).

[Labeling] In video projects, when you click Submit on an asset that has incomplete frame-level jobs, the submission process is stopped and a warning message with the index of the first incomplete frame appears. This way, you’ll be able to locate and fix the problem much faster.
[Labeling] We’ve added support for a wider range of TIFF raster drivers. For details, refer to our documentation.
[Issues & questions] We’ve improved the accessibility of the resolved issues & questions.
[Analytics] Team performance graphs are now grouped by user id instead of user name. This will help you spot specific users with more precision.
[Python SDK] When calling methods that run queries (.assets, .labels etc.), you can now request a specific object type to be returned. Set the as_generator argument to True if you want the method to return a generator. If as_generator is set to False, the method returns a list. This will give you more flexibility when handling returned data.

[Labeling] The Interactive Segmentation tool used in semantic object detection was not working with PNG images. We’ve fixed this issue.
[Labeling] When a rotated bbox added to a GeoTIFF image was being resized, the shape of the bbox would sometimes change to shapes other than rectangle. We’ve fixed this issue.
[Labeling] In text projects with many overlapping annotations, some tags were not being displayed. We’ve fixed this issue.
[Python SDK] Mutation methods would sometimes end before the mutation was complete, for example: entities (assets or projects) were not available yet on the server. This potentially lead to errors when trying to process these entities. We’ve fixed this issue.