Sigmawave

Field notes10 min read

The labelling bill nobody budgets for

Annotation is the line item that arrives after the model is approved. Where the hours actually go, and which of them a generator can take back.

Sigmawave field team
AI in the real world

Key takeaways

  • Annotation arrives as a line item after the model is approved, which is the worst possible order.
  • Most of the hours go to the rare classes, not the common ones.
  • Review and adjudication cost more than first pass labelling and are usually unbudgeted.
  • Generated footage arrives pre labelled, which is where it pays for itself.

The model gets approved, the cameras get ordered, and then somebody works out that the training set needs forty thousand labelled frames and asks, reasonably, who is doing that.

Where the hours actually go

Not where people assume. The common class, a person in a high visibility vest, in daylight, in the middle of the frame, is fast, consistent, and cheap. The bill is made up of everything else: the partial occlusions, the two people or one arguments, the frames where reasonable annotators disagree and somebody senior has to settle it.

ActivityShare of hoursUsually budgeted
First pass labelling, common cases35%Yes
Rare and ambiguous cases30%Rarely
Review and adjudication25%No
Guideline rewrites and relabelling10%No

What a generator takes back

A generated frame knows what is in it, because something placed every object in the scene before it was rendered. The labels are exact, free, and consistent, which removes the adjudication argument along with the labelling hour, and adjudication was the expensive half.

Frequently asked

Can existing labelled footage be reused across sites?

Partly. The classes transfer, the camera geometry does not, and a set labelled at four metres does a model at nine metres very little good.

Is it worth labelling in house?

For the ambiguous ten per cent, yes, those decisions are about your policy. The routine bulk is the part worth outsourcing or generating.

Sigmawave field team · 24 July 2026

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