Spaces and Transforms

The Definition of Spaces

Every Entity in Rerun exists in some space. This is at the core of how Rerun organizes the visualizations of the data that you have logged. In the Rerun Viewer you view data by configuring a space view, which is a view of a set of entities as seen from a particular space.

A space is, very loosely, a generalization of the idea of a "coordinate system" (sometimes known as a "coordinate frame") to arbitrary data. If a collection of entities are part of the same space, it means they can be rendered together in the same "coordinate system".

For examples:

  • For 2D and 3D geometric primitives this means they share the same origin and coordinate system.
  • For scalar plots it means they share the same plot axes.
  • For text logs, it means they share the same conceptual stream.

As explained bellow, a space view may display data belonging to multiple spaces, but its coordinate system is defined by a specific space, and the other spaces must have well-defined transforms to that space to be displayed in the same view.

Which entities belong to which spaces is a function of the transform system, which uses the following rules to define the space connectivity:

  1. Every unique entity path defines a potentially unique space.
  2. Unless otherwise specified, every path is trivially connected to its parent by the identity transform.
  3. Logging a transform to a path defines the relationship between that path and its parent (replacing the identity connection).
  4. Only paths which are connected by the identity transform are effectively considered to be part of the same space. All others are considered to be disjoint.

Note that in the absence of transforms, all entity paths are fully connected by the identity transform, and therefore share the same space. However, as soon as you begin to log transforms, you can end up with additional spaces.

Consider the following scenario:

rr.log("world/mapped_keypoints", rr.Points3D()) rr.log("world/robot/observed_features",rr.Points3D()) rr.log("world/robot", rr.Transforms3D())

There are 4 parent/child entity relationships represented in this hierarchy.

  • (root) -> world
  • world -> world/mapped_keypoints
  • world -> world/robot
  • world/robot -> world/robot/observed_features

The call: rr.log("world/robot", rr.Transforms3D(…)) only applies to the relationship: world -> world/robot because the logged transform (world/robot) describes the relationship between the entity and its parent (world). All other relationships are considered to be an identity transform.

This leaves us with two spaces. In one space, we have the entities world, and world/mapped_keypoints. In the other space we have the entities world/robot and world/robot/observed_features.

Practically speaking, this means that the position values of the points from world/mapped_keypoints and the points from world/robot/observed_features are not directly comparable. If you were to directly draw these points in a single coordinate system the results would be meaningless. As noted above, Rerun can still display these entities in the same space view because it is able to automatically transform data between different spaces.

Space Transformations

In order to correctly display data from different spaces in the same view, Rerun uses the information from logged transforms. Since most transforms are invertible, Rerun can usually transform data from a parent space to a child space or vice versa. As long as there is a continuous chain of well-defined transforms, Rerun will apply the correct series of transformations to the component data when building the scene.

Rerun transforms are currently limited to connections between spatial views of 2D or 3D data. There are 3 types of transforms that can be logged:

  • Affine 3D transforms, which can define any combination of translation, rotation, and scale relationship between two paths (see rr.Transform3D).
  • Pinhole transforms define a 3D -> 2D camera projection (see rr.Pinhole).
  • A disconnected space specifies that the data cannot be transformed (see rr.DisconnectedSpace). In this case it will not be possible to combine the data into a single view, and you will need to create two separate views to explore the data.

In the future, Rerun will be adding support for additional types of transforms.

Examples

Say you have a 3D world with two cameras with known extrinsics (pose) and intrinsics (pinhole model and resolution). You want to log some things in the shared 3D space, and also log each camera image and some detection in these images.

# Log some data to the 3D world: rr.log("world/points", rr.Points3D()) # Log first camera: rr.log("world/camera/0", rr.Transform3D(translation=cam0_pose.pos, mat3x3=cam0_pose.rot)) rr.log("world/camera/0/image", rr.Pinhole()) # Log second camera: rr.log("world/camera/1", rr.Transform3D(translation=cam1_pose.pos, mat3x3=cam1_pose.rot)) rr.log("world/camera/1/image", rr.Pinhole()) # Log some data to the image spaces of the first camera: rr.log("world/camera/0/image", rr.Image()) rr.log("world/camera/0/image/detection", rr.Boxes2D())

Rerun will from this understand how the world space and the two image spaces (world/camera/0/image and world/camera/1/image) relate to each other, which allows you to explore their relationship in the Rerun Viewer. In the 3D view you will see the two cameras show up with their respective camera frustums (based on the intrinsics). If you hover your mouse in one of the image spaces, a corresponding ray will be shot through the 3D space.

Note that none of the names in the paths are special.

View coordinates

You can use rr.ViewCoordinates to set your preferred view coordinate systems, giving semantic meaning to the XYZ axes of the space.

For 3D spaces it can be used to log what the up-axis is in your coordinate system. This will help Rerun set a good default view of your 3D scene, as well as make the virtual eye interactions more natural. This can be done with rr.log("world", rr.ViewCoordinates(up="+Z"), timeless=True).

You can also use this log_view_coordinates for pinhole entities, but it is encouraged that you instead use rr.log(…, rr.Pinhole(camera_xyz=…)) for this. The default coordinate system for pinhole entities is RDF (X=Right, Y=Down, Z=Forward).

WARNING: unlike in 3D views where rr.ViewCoordinates only impacts how the rendered scene is oriented, applying rr.ViewCoordinates to a pinhole-camera will actually influence the projection transform chain. Under the hood this value inserts a hidden transform that re-orients the axis of projection. Different world-content will be projected into your camera with different orientations depending on how you choose this value. See for instance the open_photogrammetry_format example.

For 2D spaces and other entities the view coordinates currently do nothing (#1387).