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.hbm) for the D-Robotics RDK S100 / S100P, ready to
load — 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.[!TIP] Redistributable, including commercially. The licence chain was checked on the code, the pretrained weights it started from, and the data it was trained on — all three, because a permissive repository badge does not by itself say anything about the weights. See Licence.
| file | what it is |
|---|---|
ppocrv6_medium_det_960x960.hbm | text detection, 960x960 — 22.4 MB |
ppocrv6_medium_rec_int16_48x320.hbm | recognition, 48x320, all-int16 — 24.0 MB |
ppocrv5_lcnet_cls_80x160.hbm | textline angle 0/180 (from v5 — v6 ships none) — 2.3 MB |
ppocr_keys_v6_18710.txt | dictionary — required by the recogniser |
| stage | latency | throughput |
|---|---|---|
| detection | 8.55 ms | 117 FPS |
| recognition | 2.22 ms | 451 FPS |
| angle classifier | 0.37 ms | 2710 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 — CPU
pre/post-processing is on top and is listed per task in BCDL's
benchmark results.conda install -c https://mirrors.ruis.ai/conda -c conda-forge bcdl1import bcdl
2engine = bcdl.Engine("ppocrv6_medium_det_960x960.hbm")
3print(engine.input_shape(0), engine.output_shape(0)).hbm. The licence above constrains
these weights and this compiled artefact.hb_compile config and the
acceptance numbers — is public in
bcdl-model-zoo, so this build can
be reproduced or retargeted rather than taken on trust.