DETR (ResNet-50 / ResNet-101)

• Original code: https://github.com/facebookresearch/detr at 29901c51d7fe
• Code licence: Apache-2.0 (permissive); files: LICENSE
• Weights licence: Apache-2.0
• Licence evidence: https://github.com/facebookresearch/detr/blob/29901c51d7fe8712168b8d0d64351170bc0f83e0/README.md (License section)
• Training data: COCO 2017 (train, instance annotations), ImageNet-1k (ILSVRC 2012 classification) (COCO 2017 train (500 epochs); the ResNet backbone was initialised from torchvision's ImageNet-1k model)
• Options: score_threshold = 0.05 (0.0 to 1.0), max_detections = 100 (>= 1)
• Kernel libraries: cudnn_hacc
• Variants: detr-r50-coco, detr-r101-coco
• Outputs: boxes, scores, labels; label_set: coco-80
• Input size: any H x W >= 32, padded to a multiple of 32
• Tested up to (portable, fp16, RTX 5060 Ti 16 GB): detr-r50-coco 3000x4000 (0.6 GiB peak allocated, 0.6 reserved); detr-r101-coco 3000x4000 (0.6 GiB peak allocated, 0.7 reserved)
• detr-r50-coco 800x1344, first call: portable + torch.compile 22 s (cold Inductor cache), TensorRT fp16 33 s (ONNX + engine).
• detr-r50-coco original (fp32) 800x1344: incl. CPU resize + host copy (official pipeline)
• detr-r50-coco original 800x1344: torch.autocast(fp16) around the forward; incl. CPU resize + host copy (official pipeline)
• detr-r101-coco original (fp32) 800x1344: incl. CPU resize + host copy (official pipeline)
• detr-r101-coco original 800x1344: torch.autocast(fp16) around the forward; incl. CPU resize + host copy (official pipeline)
• detr-r50-coco load / first call: original 2.55 s / 0.827 s, portable 0.7 s / 0.439 s, kernels 0.28† s / 0.032 s
• detr-r101-coco load / first call: original 0.95 s / 0.063 s, portable 0.81 s / 0.019 s, kernels 0.22† s / 0.014 s
• † measured in the speed sweep after the portable load (or an earlier size) in the same process: file cache and kernels are warm, so the time is lower than a fresh start.
• Protocol, median of 5 after 3 warm-up, uint8 CUDA input (synthetic for bench_inputs sizes), card defaults; gc before each load; peak = max over the first call and the timed calls

Measured

pycocotools COCOeval of the top 100 detections per image. Original = the original code named under Details, same checkpoint and protocol.

Measured on NVIDIA GeForce RTX 5060 Ti, torch 2.14.1+cu130, fastforks 939adfe8, 2026-11-06.

Parity

CPU, float32: max |diff| <= 0.002 vs the original. GPU, float16 (the default), portable and kernels: mean |diff| <= 0.2 and p99 <= 1.0 (absolute error of the output boxes).