pp-ocrv5-zh-ko-snapdragon-int8

PP-OCRv5 — Snapdragon 8 Elite NPU (int8 TFLite)

PP-OCRv5 text detection and recognition (Chinese + Korean), compiled to int8 TFLite via Qualcomm AI Hub for the Snapdragon 8 Elite (SM8750) Hexagon V79 HTP NPU.

Models

Full ZH/KO sign pipeline ≈ 2.2 ms on Hexagon NPU. 100% NPU — zero CPU fallback.

Performance

Latency — Samsung Galaxy S25 Ultra (SM8750, Android 15)

Measured via Qualcomm AI Hub cloud-hosted real device. Bench date: 2026-06-06.

AI Hub profile job IDs: det=jgkd9yowp, zh=j56vd1r6p, ko=jpv49w9kp, lat=jgj1wlwvg (viewable with a Qualcomm AI Hub account at workbench.aihub.qualcomm.com/jobs/<id> — the job pages require sign-in, they are not publicly browsable without one).

Accuracy — public dataset (ReCTS, Apache-2.0)

Real store-front signage photos (200 scored), standard ChineseOCRBench-style substring matching.

ReCTS is VQA-style (ground truth = one region; full-image OCR is substring-matched), so recall@full understates pure recognition; char-recall reflects character-level quality on real, cluttered, perspective-distorted signs.

Note on this accuracy number: measured on the float32 ONNX reference implementation (det + zh rec via rapidocr-onnxruntime), not independently re-measured on the int8 TFLite artifacts shipped in this repo. Int8 post-training quantization can shift accuracy from the float baseline — treat this as directional for the shipped models, not an exact figure for them.

Vietnamese: PP-OCRv5's Latin dictionary has no precomposed Vietnamese tone-mark vowels (verified by byte-level grep). Do not use this for Vietnamese — use a Vietnamese-specialized recognizer (e.g. VietOCR) instead.

Usage

from huggingface_hub import hf_hub_download
det = hf_hub_download("<REPO_ID>", "pp_ocrv5_det_mobile.tflite")
rec = hf_hub_download("<REPO_ID>", "pp_ocrv5_zh_rec.tflite")

Load with LiteRT (TFLite) + the QNN delegate for NPU execution on Snapdragon devices.

Source models & compilation

• Source: PaddleOCR 3.x (Apache-2.0)
• ONNX exports: monkt/paddleocr-onnx (Apache-2.0, no pickle)
• Compiled: qai-hub submit_compile_job(..., options="--target_runtime tflite --quantize_full_type int8") with random PTQ calibration data (100 samples per model)

Citation

@software{ppocrv5_snapdragon2026,
  author    = {{PaddlePaddle / PaddleOCR team}},
  title     = {{PP-OCRv5}: Multilingual Text Detection and Recognition},
  year      = {2025},
  url       = {https://github.com/PaddlePaddle/PaddleOCR}
}

AI Hub compilation and NPU validation by Viet-Anh Nguyen ([email protected]), Neural Research Lab.