Annotating a pedestrian on small datasets in a week manually might feel as a commodity but annotating large datasets in weeks time in hybrid effort is not!
If anyone already has such a data engine, i would love to connect and discuss!
I questioned whether computer‑vision annotation can be treated as a commodity, noting that a commodity should have clear price points, standardized service levels, and minimal vendor lock‑in, which currently isn’t true for novel label sets that aren’t covered by major cloud APIs.
I raise the open question: is data annotation for computer vision AI a commodity?
Desired feasibility: annotate millions of images with polygons within ≤ 24 hours or ≤ one week while achieving ≥ 90 % precision and recall for a label not available via AWS, Azure, or Google Cloud APIs.
The original yes/no question was flagged as incomplete because it omitted critical criteria such as budget, workforce size, and tooling. Any answer must first clarify these missing parameters.
I investigated whether data annotation has truly become a commodity by interviewing over 100 stakeholders and prototyping a high‑complexity labeling task to expose supply‑side bottlenecks.
I interviewed over 100 individuals to obtain a robust view of the annotation market.
The target project involves 1,000,000 images labeled with 50 unique custom bounding‑box categories.
The turnaround deadline is four weeks.
The required labeling quality is ≥ 95 % accuracy.
I decided to interview >100 people to get a representative view, and I focused on a high‑complexity task (50 custom boxes) with a strict 4‑week deadline and 95 %+ accuracy to surface real capacity limits of annotation providers.