nimbusimage

Compute properties, export data, manage connections, and share NimbusImage datasets using the nimbusimage Python API. Use this skill when the user wants to compute annotation measurements, export data as JSON or CSV, create connections between annotations, share datasets with collaborators, or manage access control. Also use when you see ds.properties, ds.export, ds.connections, or ds.sharing in code, or the user mentions measurements, statistics, data export, lineage tracking, or sharing imaging datasets.

Create, list, filter, update, and delete annotations on NimbusImage datasets using the nimbusimage Python API. Use this skill when the user wants to work with annotations — creating points or polygons, filtering by shape or tags, bulk operations, geometry conversion (shapely, numpy masks), or programmatic annotation manipulation. Also use when you see ds.annotations in code, or the user mentions spots, cells, nuclei, ROIs, polygons, or segmentation masks in an imaging context.

Fetch image data from NimbusImage datasets as numpy arrays using the nimbusimage Python API. Use this skill when the user wants to retrieve image frames, composites, z-stacks, crops, or channel data from a NimbusImage dataset. Also use when you see ds.images in code, or the user mentions getting pixel data, viewing channels, making composites, or processing image arrays from their imaging server.

Connect to a NimbusImage server and work with scientific imaging datasets using the nimbusimage Python API. Use this skill whenever the user mentions NimbusImage, wants to connect to a Girder-based imaging server, list or open datasets, or asks about the nimbusimage package. Also use when you see `import nimbusimage` in code or the user references dataset IDs, channels, z-slices, or time points in an imaging context. This is the entry point — it routes to more specific skills (annotations, images, workers, analyze) for deeper operations.

Run Docker-based computational workers on NimbusImage datasets using the nimbusimage Python API. Use this skill when the user wants to run segmentation, spot detection, property computation, or any Docker worker on their imaging data. Also use when you see ds.annotations.compute or ds.properties.compute in code, or the user mentions running workers, submitting jobs, tracking job status, or automating image analysis pipelines on a NimbusImage server.