| --- |
| license: apache-2.0 |
| library_name: tflite |
| tags: |
| - ocr |
| - paddleocr |
| - text-detection |
| - text-recognition |
| - snapdragon |
| - qualcomm |
| - on-device |
| - multilingual |
| language: |
| - zh |
| - ko |
| pipeline_tag: image-to-text |
| authors: |
| - PaddlePaddle / PaddleOCR team (original model) |
| - Viet-Anh Nguyen (vietanh@nrl.ai) — Qualcomm AI Hub compilation & validation |
| --- |
| |
| # PP-OCRv5 — Snapdragon 8 Elite NPU (int8 TFLite) |
|
|
| PP-OCRv5 text detection and recognition (Chinese + Korean), compiled to **int8 TFLite** |
| via [Qualcomm AI Hub](https://aihub.qualcomm.com) for the **Snapdragon 8 Elite (SM8750) |
| Hexagon V79 HTP NPU**. |
|
|
| ## Models |
|
|
| | File | Description | Size | NPU latency (S25 Ultra) | |
| |------|-------------|------|------------------------| |
| | `pp_ocrv5_det_mobile.tflite` | Text detection (PP-HGNetV2 + DB++) | 807 KB | **1.23 ms** | |
| | `pp_ocrv5_zh_rec.tflite` | Chinese text recognition (SVTR/CTC) | 22 MB | **0.99 ms** | |
| | `pp_ocrv5_ko_rec.tflite` | Korean text recognition (SVTR/CTC) | 3.9 MB | **0.49 ms** | |
| | `pp_ocrv5_lat_rec.tflite` | Latin text recognition (SVTR/CTC) | 2.2 MB | **0.31 ms** | |
| | `zh_dict.txt` | 18,383-char ZH dictionary (PaddleOCR `ppocrv5_dict.txt`) | — | — | |
| | `ko_dict.txt` | 11,945-char KO dictionary (PaddleOCR `ppocrv5_korean_dict.txt`) | — | — | |
| | `lat_dict.txt` | 836-char Latin dictionary (PaddleOCR `ppocrv5_latin_dict.txt`) | — | — | |
|
|
| **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. |
|
|
| | model | NPU ms | NPU ops | vs ORT CPU | |
| |-------|--------|---------|------------| |
| | det | **1.23** | 156/156 (100%) | 105× faster | |
| | zh rec | **0.99** | 219/219 (100%) | 180× faster | |
| | ko rec | **0.49** | 223/223 (100%) | 86× faster | |
| | lat rec | **0.31** | 223/223 (100%) | 148× faster | |
|
|
| 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. |
|
|
| | metric | value | |
| |--------|-------| |
| | recall@full (answer fully recognized) | **48.5%** | |
| | mean char-recall | **66.0%** | |
|
|
| 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 |
|
|
| ```python |
| 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](https://github.com/PaddlePaddle/PaddleOCR) (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 |
|
|
| ```bibtex |
| @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 (vietanh@nrl.ai), Neural Research Lab. |
|
|
