license: bsd-3-clause
library_name: libreyolo
pipeline_tag: object-detection
datasets:
- detection-datasets/coco
tags:
- object-detection
- fcos
- torchvision
- libreyolo
LibreFCOSr50
FCOS with a ResNet-50 FPN backbone, repackaged for LibreYOLO.
from libreyolo import LibreYOLO
model = LibreYOLO("LibreFCOSr50.pt")
results = model.predict("image.jpg")
Source
Derived from pytorch/vision at commit
336d36e8db990a905498c73933e35231876e28bc.
Copyright (c) Soumith Chintala 2016 and torchvision contributors. The source
implementation is BSD-3-Clause.
Official checkpoint: fcos_resnet50_fpn_coco-99b0c9b7.pth
SHA-256: 99b0c9b7cfb1527d782db86b91d207f00547c792fb4103fc612b651d0a07b9e7
Published COCO val2017 box mAP: 39.2.
Modifications
Checkpoint metadata was added for LibreYOLO's v1.0 schema. Learned tensors and
state-dict keys are unchanged. The native LibreYOLO graph loads all 319
official state entries strictly and matches the pinned source at raw heads,
anchors, preprocessing, and final detections. See
weights/convert_fcos_weights.py in the
LibreYOLO source repository.
Benchmarks
Independent accuracy and speed benchmarks: visionanalysis.org/model/fcos-r50
License
The checkpoint publisher did not attach a separate per-object license file.
This mirror applies the releasing project's BSD-3-Clause license on an
implied, not publisher-confirmed, basis. Torchvision warns that pretrained
models may have their own licenses or terms derived from training data and
that users must determine whether they have permission for their use case.
COCO annotations are CC BY 4.0; source images retain their individual Flickr
terms. See LICENSE and NOTICE.