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DVID Picture

Status: In development, being tested at Janelia, and not ready for external use due to possible breaking changes. In near future, the label data types (labelblk, labelvol, and currently non-working labelsz and labelsurf) will be combined into one "labels64" type for better performance in some operations.

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See the DVID Wiki for more information including installation and examples of use.

Web app for 3d inspection being served from and sending requests to DVID

DVID is a distributed, versioned, image-oriented datastore written to support Janelia Farm Research Center's brain imaging, analysis and visualization efforts. It's goal is to provide:

  • Easily extensible data types that allow tailoring of access speeds, storage space, and APIs.
  • The ability to use a variety of storage systems by either creating a data type for that system or using an ordered key/value datastore interface.
  • A framework for thinking of distribution and versioning of data similar to distributed version control systems like git.

Long-term, DVID aspires to be a "github for large image-oriented data" because each DVID server can manage multiple repositories, each of which contains an image-oriented repo with related data like an image volume, labels, and skeletons. The goal is to provide scientists with a github-like web client + server that can push/pull data to a collaborator's DVID server.

DVID's initial focus is on efficiently handling data essential for Janelia's connectomics research:

  • image and 64-bit label 3d volumes
  • 2d images in XY, XZ, YZ, and arbitrary orientation
  • multiscale 2d images in XY, XZ, and YZ, similar to quadtrees
  • low-latency sparse volumes corresponding to each unique label in a volume
  • label graphs
  • regions of interest represented via a coarse subdivision of space using block indices
  • 2d and 3d image and label data using Google BrainMaps API

Each of the above is handled by built-in data types via a Level 2 REST HTTP API implemented by Go language packages within the datatype directory.

DVID is primarily written in Go and supports different storage backends, a REST HTTP API, and command-line access (likely minimized in near future). Some components are written in C, e.g., storage engines like Leveldb and fast codecs like lz4. DVID has been tested on both MacOS X and Linux (Fedora 16, CentOS 6, Ubuntu) but not on Windows.

Command-line and HTTP API documentation can be found in help constants within packages or by visiting the /api/help HTTP endpoint on a running DVID server. We are in the process of figuring out a nice way to document the APIs either through RAML or Swagger.