ViTPose-S whole-body for RDK S100/S100P β 133 keypoints
Compiled BPU models (.hbm) for the D-Robotics RDK S100 / S100P, ready to
load β no ONNX export, no calibration, no hb_compile. Built and measured with
BCDL, a C++17 inference and media library
for the RDK S-series with Python bindings.
Upstream: easy_ViTPose ViTPose-S wholebody, COCO-WholeBody
Non-commercial. These weights carry a restriction the upstream code licence never mentions β see Licence at the bottom. Redistribution is permitted; commercial use is not. If you need a commercial build, the recipe is public and you can retrain or substitute the backbone.
Files
| file | what it is |
|---|---|
vitpose_s_wholebody_nashm_256x192.hbm |
256x192, 133-keypoint heatmaps β 27.7 MB |
Measured on an S100P
| stage | latency | throughput |
|---|---|---|
| pose, per person | 1.60 ms | 623 FPS |
hrt_model_exec perf, one thread, minimum of three runs, on a board first gated
against its own previously recorded numbers. BPU time only β CPU
pre/post-processing is on top and is listed per task in BCDL's
benchmark results.
Use it
conda install -c https://mirrors.ruis.ai/conda -c conda-forge bcdl
import bcdl
engine = bcdl.Engine("vitpose_s_wholebody_nashm_256x192.hbm")
print(engine.input_shape(0), engine.output_shape(0))
Each task has a decoder in BCDL that turns those raw outputs into boxes, keypoints, masks, disparity or text β see the Python API (δΈζ).
What to know before deploying
This is a top-down model: it runs once per person, on a crop, so it needs a detector in front of it and its cost grows with the head count. What you get for that is feet, a 68-point face and both hands β 133 keypoints against the 17 a bottom-up pose head gives.
A plain ViT's cost tracks its token count, which is why a ViT runs at 1.6 ms here: 256x192 is 192 tokens. The int8 build needed no LayerNorm intervention.
Two conventions must be copied exactly or the keypoints land off-target: the model takes RGB, and the crop geometry is not the mmpose affine β widen the box by 10 px, zero-pad to 3:4, resize.
Non-commercial. See the licence note above.
Licence
Apache-2.0 on the code, but the checkpoint is fine-tuned from MAE, which is CC-BY-NC-4.0, and trained on COCO-WholeBody. A fine-tune is a direct derivative of the weights it started from, so the non-commercial term reaches this build.
BCDL itself is Apache-2.0 and is unrelated to these terms β it is a
general-purpose runtime that loads any .hbm. The licence above constrains
these weights and this compiled artefact.
The conversion recipe β ONNX export, calibration, hb_compile config and the
acceptance numbers β is public in
bcdl-model-zoo, so this build can
be reproduced or retargeted rather than taken on trust.