Official HRNet-W32 256x192 COCO-17 top-down pose weights, repackaged for
LibreYOLO.
This is a person-crop pose head. Its fixed input is one 256x192 RGB person
crop; the checkpoint does not contain a person detector. LibreYOLO can compose
the head with its default YOLO9 detector, another PersonDetector, explicit
person_boxes, or cropped=True.
Derived from
leoxiaobin/deep-high-resolution-net.pytorch
at commit
6f69e4676ad8d43d0d61b64b1b9726f0c369e7b1.
The upstream repository license is Copyright (c) 2019 Leo Xiao and is MIT.
Adapted implementation files also identify Microsoft and Bin Xiao.
The original state dict is wrapped with LibreYOLO checkpoint metadata. Learned
tensor keys, values, and dtypes are unchanged and strict-load into the native
HRNet-W32 graph. The converted file is
LibreHRNetw32-pose.pt, SHA-256
c9d8eb383e63ce795f87a3ee2f2b0c8aa0df9bae981573ec4b3909d63815a825.
See
weights/convert_hrnet_weights.py and
docs/provenance/hrnet.md in the
LibreYOLO source repository.
The official project distributes this checkpoint from its MIT-licensed model
zoo but does not attach a separate checkpoint-specific license. This mirror's
redistribution basis is the MIT license implied by the releasing project, not
a claim of an independently confirmed per-file grant. Training-data rights
remain separate. See
LICENSE and
NOTICE.
