license: mit
library_name: libreyolo
pipeline_tag: object-detection
datasets:
- detection-datasets/coco
tags:
- object-detection
- centernet
- libreyolo
LibreCenterNetresdcn18
CenterNet ResNet-18 with deformable upsampling COCO detector, repackaged for LibreYOLO.
from libreyolo import LibreYOLO
model = LibreYOLO("LibreCenterNetresdcn18.pt")
results = model.predict("image.jpg")
Source
Derived from xingyizhou/CenterNet
at commit
4c50fd3a46bdf63dbf2082c5cbb3458d39579e6c.
Copyright (c) 2019 Xingyi Zhou. The source implementation is MIT licensed.
Official checkpoint: ctdet_coco_resdcn18.pth
Official SHA-256: f9e413f91cdb235adbcb41c5c4052b8f7ff53999374048949789c29d6df18eaa
Published COCO test-dev AP without test-time augmentation: 28.1.
Modifications
The data-parallel module. prefix was removed and LibreYOLO v1 checkpoint
metadata was added. Learned tensors are unchanged. The native graph strictly
loads the official state dict and its hm, wh, and reg outputs are
bit-exact against the pinned implementation. LibreYOLO replaces the legacy
DCNv2 extension with torchvision deformable convolution.
See weights/convert_centernet_weights.py and
docs/provenance/centernet.md in the
LibreYOLO source repository.
Benchmarks
Independent accuracy and speed benchmarks: visionanalysis.org/model/centernet-resdcn18
License
The checkpoint publisher did not attach a standalone per-object license file.
This mirror applies the releasing project's MIT license on an implied, not
publisher-confirmed, basis. COCO annotations are CC BY 4.0; source images
retain their individual Flickr terms. See LICENSE and
NOTICE.