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LibreYOLO/LibreDeformableDETRr50twostage
LibreDeformableDETRr50twostage is a object detection model from LibreYOLO. Use it when you need objects located in an image. It is set up for libreyolo. The card lists the license as apache-2.0.
The official box-refinement two-stage ResNet-50 Deformable DETR checkpoint (46.9 AP on COCO val2017), converted for LibreYOLO.
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Updated Aug 2, 2026
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From the Hugging Face model README
The official box-refinement two-stage ResNet-50 Deformable DETR checkpoint (46.9 AP on COCO val2017), converted for LibreYOLO.
from libreyolo import LibreYOLO
model = LibreYOLO("LibreDeformableDETRr50twostage.pt")
results = model.predict("image.jpg")
LibreYOLO ships this museum family for inference only. Its portable deformable
attention uses the upstream pure-PyTorch grid_sample reference path; the
custom CUDA extension is not packaged. Native and ONNX inference use a fixed
800 x 800 PIL-bilinear stretch with ImageNet normalization. That deployment
transform intentionally differs from upstream's short-side-800/max-1333
evaluation transform.
Architecture derived from
fundamentalvision/Deformable-DETR
at commit 11169a60c33333af00a4849f1808023eba96a931.
Copyright (c) 2020 SenseTime. All Rights Reserved. Modified from DETR,
Copyright 2020 - present, Facebook, Inc. Licensed under Apache License 2.0.
The checkpoint comes from
SenseTime/deformable-detr-with-box-refine-two-stage
at revision e74bff70d69f3e825f6cefaf179bfba707f92054.
Source model.safetensors SHA-256:
411bb4238a834d40fff651b1b5b7d6dd80c2dd28be1747eec7b6918674e85de6.
Checkpoint keys are remapped to the original module layout, decoder Q/K/V projections are concatenated, and serialization aliases for the refinement and encoder-proposal heads are restored. Non-parameter BatchNorm tracking counters are omitted; learned tensor values are unchanged. The released 91-column COCO category-id head is retained and mapped to contiguous COCO-80 classes during postprocess.
The converted checkpoint SHA-256 is
7250d79708f53f2f5b8b0daec94011def1c262c4fc723993c1f58128c8002670.
LibreYOLO's output tensors, including encoder proposals, are bit-exact against
the pinned upstream pure-PyTorch path (max_abs_diff == 0.0); fixed-800 ONNX
Runtime prediction parity is also verified.
See weights/convert_deformable_detr_weights.py and
docs/provenance/deformable_detr.md in the
LibreYOLO source repository.
Apache License 2.0. See the LICENSE and NOTICE
files in this repository.