System and method for semi-automated dataset annotation using similarity based clustering and in-context learning for segmentation

A system comprising:

• one or more non-transitory computer-readable media storing instructions thereon that, when executed by one or more processors, cause the one or more processors to:
• identify a density for each of a plurality of clusters of data points, each data point corresponding to a different image of a plurality of images and the density of each cluster indicating an aggregate similarity of images of the cluster;
• and
• based on the density for each of the plurality of clusters satisfying a criterion, for each cluster of the plurality of clusters:
• identify a first set of annotations for one or more pixels of each of a first subset of the images included in the cluster;
• execute a model using the annotated first subset of images of the cluster with a remaining unannotated subset of images of the cluster not included in the annotated first subset of images;
• and
• generate based on execution of the model using the annotated first subset of images with the remaining unannotated subset of images, a second plurality of annotations for the remaining unannotated subset of images of the cluster not included in the annotated first subset of images.

One or more non-transitory computer-readable media storing instructions thereon that, when executed by one or more processors, cause the one or more processors to perform operations comprising:

• identifying a density for each of a plurality of clusters of data points, each data point corresponding to a different content item of a plurality of content items and the density of each cluster indicating an aggregate similarity of content items of the cluster;
• and
• based on the density for each of the plurality of clusters satisfying a criterion, for each cluster of the plurality of clusters:
• identifying a first set of annotations for one or more pixels of each of a first subset of the content items included in the cluster;
• executing a model using the annotated first subset of content items of the cluster with a remaining unannotated subset of content items of the cluster not included in the annotated first subset of content items;
• and
• generating based on execution of the model using the annotated first subset of content items with the remaining unannotated subset of content items, a second plurality of annotations for the remaining unannotated subset of content items of the cluster not included in the annotated first subset of content items.