README.md

---
license: apache-2.0
library_name: bcdl
tags:
- rdk-s100
- rdk-s100p
- d-robotics
- bpu
- hbm
- ocr
- text-recognition
---

# PP-OCRv6 for RDK S100/S100P — detection + recognition + angle

Compiled BPU models (`.hbm`) for the **D-Robotics RDK S100 / S100P**, ready to
load — no ONNX export, no calibration, no `hb_compile`. Built and measured with
[**BCDL**](https://github.com/ruisv/bcdl), a C++17 inference and media library
for the RDK S-series with Python bindings.

Upstream: [PaddleOCR](https://github.com/PaddlePaddle/PaddleOCR) PP-OCRv6 medium

> [!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](#licence).

## Files

| 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 |

## Measured on an S100P

| 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](https://github.com/ruisv/bcdl/blob/main/benchmarks/RESULTS.md).

## Use it

```bash
conda install -c https://mirrors.ruis.ai/conda -c conda-forge bcdl
```

```python
import bcdl
engine = bcdl.Engine("ppocrv6_medium_det_960x960.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 — see the
[Python API](https://github.com/ruisv/bcdl/blob/main/docs/API.md)
([中文](https://github.com/ruisv/bcdl/blob/main/docs/API.zh.md)).

## What to know before deploying

**The recogniser is all-int16 on purpose.** On the S100P it roughly halves the
character error of the compiler's default mixed-precision int8 build *and* is
about 2x faster, because a uniform int16 graph carries no int8-int16 requant on
its internal boundaries.

**The dictionary is not optional and it is version-specific.** v6 recognises
18710 classes against v5's 18385; pairing a model with the wrong key file
decodes to plausible-looking wrong characters rather than failing. The right one
ships here.

For text lines longer than about 6.7:1 there is also a 960-wide recogniser in
the conversion recipe; this package carries the 320 build.

## Licence

Apache-2.0, on the code **and** on every model card.

**BCDL itself is Apache-2.0 and is unrelated to these terms** — it is a
general-purpose runtime that loads any `.hbm`. The licence above constrains
*these weights and this compiled artefact*.

The conversion recipe — ONNX export, calibration, `hb_compile` config and the
acceptance numbers — is public in
[**bcdl-model-zoo**](https://github.com/ruisv/bcdl-model-zoo), so this build can
be reproduced or retargeted rather than taken on trust.