Co-DETR

Standalone install? If this session was not initialized by the TAO skill bank plugin, run the tao-setup skill first (host preflight, credentials, cross-skill discovery).

Co-DETR trains a DETR detector alongside auxiliary one-to-many assignment heads (num_co_heads), which supervise the encoder more densely than DETR's one-to-one matching alone. The auxiliary heads exist only during training; inference runs the primary DETR head. Backbones are large by default — vit_large_codetr for training, swin_large_patch4_window7_224 for the reference inference/eval configs — so this is an accuracy-first model, not a latency-first one.

Availability — probe, then fall back to the module

The codetr console script is not registered in the TAO PyTorch images checked so far (7.0.1-pyt and the 2026.7.31-rc-12-multiarch nightly), even though the module itself ships. So a bare codetr invocation fails while the network is perfectly usable.

Probe in two steps and use whichever works:

# 1. console script (preferred when present)
docker run --rm "$TAO_PYT_IMAGE" codetr --help >/dev/null 2>&1 && CODETR="codetr"