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Tools for neuroglancer scenes.

Project description

NGSidekick

Documentation

Tools for working with neuroglancer. See docs.

Feature Highlights

  • Segment properties: read and write neuroglancer's precomputed segment properties format from a pandas DataFrame.

  • Local annotations: construct local annotations directly in viewer state. (API subject to change.)

  • Precomputed annotations: export annotations in neuroglancer's precomputed annotations format from a pandas DataFrame.

    • Supports all five annotation types:
      • point
      • line
      • axis_aligned_bounding_box
      • ellipsoid
      • polyline
    • Per-annotation properties (numeric, enum/categorical, and rgb/rgba color).
    • Per-annotation relationships (lists of related segment IDs, used by neuroglancer to filter annotations by segment).
    • Written to all "index" types (annotation id, related segment, and multi-level spatial grid)
    • Sharded output, written in parallel via tensorstore.
    • Note: writing directly to cloud storage is not yet supported; outputs must be written to a local filesystem (you must upload to cloud storage afterwards).

Installation

Packages are available from both PyPI and conda-forge.

Using pixi:

pixi add ngsidekick

Using conda:

conda install -c conda-forge ngsidekick

Using pip:

pip install ngsidekick

Using uv:

uv add ngsidekick

# or in an existing environment
uv pip install ngsidekick

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