| --- |
| license: mit |
| library_name: libreyolo |
| tags: |
| - keypoint-detection |
| - pose-estimation |
| - hrnet |
| --- |
| |
| # LibreHRNetw32-pose |
|
|
| 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`. |
|
|
| ## Source |
|
|
| Derived from |
| [`leoxiaobin/deep-high-resolution-net.pytorch`](https://github.com/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. |
|
|
| Official source file: `pose_hrnet_w32_256x192.pth` |
|
|
| Source SHA-256: |
| `19bc083708bb8d873211e50d85d56344c10290c6e8b564c813fdde09645c4c1c` |
|
|
| ## Modifications |
|
|
| 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](https://github.com/LibreYOLO/libreyolo). |
|
|
| ## License |
|
|
| 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`](./LICENSE) and [`NOTICE`](./NOTICE). |
|
|
