mtbui2010/rfdetr-small-etri-ONNX

RF-DETR Small — tabletop-22 (ONNX)

An RF-DETR Small detector (COCO-pretrained, Apache-2.0) fine-tuned on 22 tabletop object classes (ETRI tabletop data), exported to ONNX for VisionServe.

visionserve pull rfdetr-small-etri          # this detector alone
visionserve pull rfdetr-gdino-siglip-etri   # + GroundingDINO + SigLIP rescoring (open vocabulary)

Files

file	contents
model.onnx	the detector, opset 17, 114 MB
labels.txt	23 lines: the 22 class names in head order, then N/A

I/O contract

	name	shape	notes
input	input	[1, 3, 512, 512] f32	RGB, squashed to 512×512 (no letterbox, no padding), /255, ImageNet mean/std
output	dets	[1, 300, 4] f32	cxcywh, normalised to the 512×512 input
output	labels	[1, 300, 23] f32	logits, sigmoid (focal loss, not softmax); NMS-free

Squash, not letterbox. The fine-tune used rfdetr's square_resize_div_64=True, and rfdetr's own predict() resizes with F.resize(img, [res, res]). Serving this checkpoint letterboxed is a train/serve mismatch that measured −7.35 mAP on a sibling checkpoint of the same recipe.

Training

rfdetr.RFDETRSmall(...).train(...) with 100 % of the 31.9 M parameters trainable ("pf-full" of a partial-unfreeze sweep), 185 training / 62 validation images. Measured through VisionServe on the 62 validation images: 85.33 mAP, 38 ms per request (RTX A6000) — measured letterboxed, i.e. before the squash fix above.

License

Apache-2.0, inherited from RF-DETR (Roboflow). No third-party weights with other licenses.