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Tasks

What you can actually train on this.

A capture is not a dataset for every task at once. These are the three a NameFrame run supports properly today, with the ground truth each one gets and what it costs. Anything not listed here is either derivable from the raw dump with work, or not supported, and this page says which.

Reference capture
40 frames
Classes
6
Instances
4,378

What each task gets from one frame

All three come from the same capture. You do not choose a task at capture time and lose the others.

TaskGround truthDerived fromIn the sample pack
Object detectionClass + boxidentity bufferyes, YOLO and COCO
Instance segmentationClass + per-object maskidentity bufferyes, COCO polygons
Semantic segmentationClass per pixelidentity bufferderivable from the ID buffer
Depth estimationfloat32 metresdepth bufferyes, 3 frames

Semantic segmentation does not have a page of its own under tasks because it is a projection of the instance masks rather than a separate output. How that derivation works is worth reading if you need it.

Not supported today

Keypoints and pose

The capture contract has room for it and the plugin can carry pose-enabled actors, but the reference capture has none and nothing here is validated for it. It will get a page when there is a run to point at.

Tracking across frames

Objects are reshuffled every frame by design, so consecutive frames are independent samples rather than a sequence. A tracking dataset needs a different capture mode.

Optical flow, normals, materials

The engine has all of them. The capture does not currently write them, so they are not claimed here.