{"categories":[{"label":"Scientific/Engineering","url":"https://skillfed.io/packages/category/scientific-engineering/8"}],"enrichment":{"capability":"Generates multiscale image pyramids organized as Xarray Datatrees, with built-in support for chunked Dask arrays and serialization to OME-NGFF/Zarr formats.","skillfed_tags":["imaging","multiscale-pyramids","ome-ngff"],"use_cases":["Generate multiscale pyramids from microscopy images for efficient zoom-and-pan visualization in web or desktop viewers","Prepare large volumetric datasets for hierarchical processing pipelines that operate at different resolutions","Convert single-scale images to OME-NGFF Zarr stores for archival and sharing with other imaging software","Apply transformations (transpose, reindex) uniformly across all scales of a multiscale dataset","Build image analysis workflows that downsample data for preview or coarse-to-fine processing strategies"],"what_it_does":"multiscale-spatial-image builds multiscale image pyramids\u2014progressively downsampled versions of an image\u2014and organizes them into an Xarray Datatree structure where each scale level is a separate node. Each scale is a chunked Dask array, enabling lazy evaluation and out-of-core processing. The package preserves spatial metadata (coordinates, dimensions) across all scales and can serialize the entire pyramid to OME-NGFF (Open Microscopy Environment Next Generation File Format) via Zarr, making it suitable for scientific imaging workflows that need efficient storage and access to multiscale data.\n\nThe package is built on top of spatial-image, xarray, and Dask, and provides convenience methods like transpose, reindex, and assign_coords that operate across all scales while skipping non-dimensional nodes. It targets scientific Python users working with microscopy, medical imaging, or other multidimensional spatial data who need to generate and store image hierarchies in a standard, interoperable format.","worth_installing":"Yes, if you work with multidimensional spatial imaging data and need to generate and store multiscale pyramids in a standard format. The package has low install friction, permissive licensing, and no known vulnerabilities. Maintenance is aging but not abandoned; the API is explicitly pre-1.0 and subject to change, so pin versions carefully in production. Best suited for scientific and research use cases rather than production services."},"id":"multiscale-spatial-image","links":{"html":"https://skillfed.io/packages/multiscale-spatial-image","md":"https://skillfed.io/packages/multiscale-spatial-image.md","pypi":"https://pypi.org/project/multiscale-spatial-image/"},"maintenance":{"status":"aging"},"meta":{"latest_release":"2025-11-13","license_spdx":null,"license_treatment":"permissive","name":"multiscale-spatial-image","python_support":"supports_current","summary":"Generate a multiscale, chunked, multi-dimensional spatial image data structure that can be serialized to OME-NGFF."},"popularity":{"monthly_downloads":95614,"position":13260,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"2.1.0"}