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--- |
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license: apache-2.0 |
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language: |
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- en |
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- fr |
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- de |
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- es |
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- it |
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- pt |
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- nl |
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- pl |
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- cs |
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- sk |
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- hr |
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- bs |
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- sr |
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- sl |
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- da |
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- "no" |
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- sv |
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- is |
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- et |
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- lt |
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- hu |
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- sq |
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- cy |
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- ga |
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- tr |
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- id |
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- ms |
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- af |
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- sw |
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- tl |
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- uz |
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- la |
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- ru |
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- bg |
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- uk |
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- be |
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- ko |
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- zh |
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- ja |
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- th |
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- el |
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- hi |
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- mr |
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- ne |
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- sa |
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- ar |
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- ur |
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- fa |
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- ta |
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- te |
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tags: |
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- ocr |
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- optical-character-recognition |
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- text-detection |
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- text-recognition |
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- paddleocr |
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- onnx |
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- computer-vision |
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- document-ai |
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library_name: onnx |
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pipeline_tag: image-to-text |
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--- |
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# PP-OCR ONNX Models |
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Multilingual OCR models from PaddleOCR, converted to ONNX format for production deployment. |
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**Use as a complete pipeline**: Integrate with [monkt.com](https://monkt.com) for end-to-end document processing. |
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**Source**: [PaddlePaddle PP-OCRv5 Collection](https://huggingface.co/collections/PaddlePaddle/pp-ocrv5-684a5356aef5b4b1d7b85e4b) |
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**Format**: ONNX (optimized for inference) |
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**License**: Apache 2.0 |
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--- |
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## Overview |
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**16 models** covering **48+ languages**: |
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- 11 PP-OCRv5 models (latest, highest accuracy) |
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- 5 PP-OCRv3 models (legacy, additional language support) |
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--- |
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## Quick Start |
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### Download from HuggingFace |
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```bash |
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pip install huggingface_hub rapidocr-onnxruntime |
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``` |
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<details> |
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<summary><b>Download specific language models</b></summary> |
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```python |
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from huggingface_hub import hf_hub_download |
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# Download English models |
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det_path = hf_hub_download("monkt/paddleocr-onnx", "detection/v5/det.onnx") |
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rec_path = hf_hub_download("monkt/paddleocr-onnx", "languages/english/rec.onnx") |
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dict_path = hf_hub_download("monkt/paddleocr-onnx", "languages/english/dict.txt") |
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# Use with RapidOCR |
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from rapidocr_onnxruntime import RapidOCR |
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ocr = RapidOCR(det_model_path=det_path, rec_model_path=rec_path, rec_keys_path=dict_path) |
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result, elapsed = ocr("document.jpg") |
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``` |
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</details> |
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<details> |
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<summary><b>Download entire language folder</b></summary> |
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```python |
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from huggingface_hub import snapshot_download |
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# Download all French/German/Spanish (Latin) models |
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snapshot_download("monkt/paddleocr-onnx", allow_patterns=["detection/v5/*", "languages/latin/*"]) |
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# Download Arabic models (v3) |
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snapshot_download("monkt/paddleocr-onnx", allow_patterns=["detection/v3/*", "languages/arabic/*"]) |
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``` |
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</details> |
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<details> |
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<summary><b>Clone entire repository</b></summary> |
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```bash |
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git clone https://huggingface.co/monkt/paddleocr-onnx |
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cd paddleocr-onnx |
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``` |
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</details> |
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### Basic Usage |
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```python |
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from rapidocr_onnxruntime import RapidOCR |
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ocr = RapidOCR( |
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det_model_path="detection/v5/det.onnx", |
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rec_model_path="languages/english/rec.onnx", |
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rec_keys_path="languages/english/dict.txt" |
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) |
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result, elapsed = ocr("document.jpg") |
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for line in result: |
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print(line[1][0]) # Extracted text |
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``` |
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--- |
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## Available Models |
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### PP-OCRv5 Recognition Models |
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| Language Group | Path | Languages | Accuracy | Size | |
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|----------------|------|-----------|----------|------| |
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| English | `languages/english/` | English | 85.25% | 7.5 MB | |
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| Latin | `languages/latin/` | French, German, Spanish, Italian, Portuguese, + 27 more | 84.7% | 7.5 MB | |
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| East Slavic | `languages/eslav/` | Russian, Bulgarian, Ukrainian, Belarusian | 81.6% | 7.5 MB | |
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| Korean | `languages/korean/` | Korean | 88.0% | 13 MB | |
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| Chinese/Japanese | `languages/chinese/` | Chinese, Japanese | - | 81 MB | |
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| Thai | `languages/thai/` | Thai | 82.68% | 7.5 MB | |
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| Greek | `languages/greek/` | Greek | 89.28% | 7.4 MB | |
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### PP-OCRv3 Recognition Models (Legacy) |
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| Language Group | Path | Languages | Version | Size | |
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|----------------|------|-----------|---------|------| |
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| Devanagari | `languages/hindi/` | Hindi, Marathi, Nepali, Sanskrit | v3 | 8.6 MB | |
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| Arabic | `languages/arabic/` | Arabic, Urdu, Persian/Farsi | v3 | 8.6 MB | |
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| Tamil | `languages/tamil/` | Tamil | v3 | 8.6 MB | |
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| Telugu | `languages/telugu/` | Telugu | v3 | 8.6 MB | |
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### Detection Models |
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| Model | Path | Version | Size | |
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|-------|------|---------|------| |
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| PP-OCRv5 Detection | `detection/v5/det.onnx` | v5 | 84 MB | |
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| PP-OCRv3 Detection | `detection/v3/det.onnx` | v3 | 2.3 MB | |
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**Note**: Use v5 detection with v5 recognition models. Use v3 detection with v3 recognition models. |
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### Preprocessing Models (Optional) |
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| Model | Path | Purpose | Accuracy | Size | |
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|-------|------|---------|----------|------| |
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| Document Orientation | `preprocessing/doc-orientation/` | Corrects rotated documents (0°, 90°, 180°, 270°) | 99.06% | 6.5 MB | |
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| Text Line Orientation | `preprocessing/textline-orientation/` | Corrects upside-down text (0°, 180°) | 98.85% | 6.5 MB | |
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| Document Unwarping | `preprocessing/doc-unwarping/` | Fixes curved/warped documents | - | 30 MB | |
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--- |
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## Language Support |
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### PP-OCRv5 Languages (40+) |
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**Latin Script** (32 languages): English, French, German, Spanish, Italian, Portuguese, Dutch, Polish, Czech, Slovak, Croatian, Bosnian, Serbian, Slovenian, Danish, Norwegian, Swedish, Icelandic, Estonian, Lithuanian, Hungarian, Albanian, Welsh, Irish, Turkish, Indonesian, Malay, Afrikaans, Swahili, Tagalog, Uzbek, Latin |
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**Cyrillic**: Russian, Bulgarian, Ukrainian, Belarusian |
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**East Asian**: Chinese (Simplified, Traditional), Japanese (Hiragana, Katakana, Kanji), Korean |
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**Southeast Asian**: Thai |
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**Other**: Greek |
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### PP-OCRv3 Languages (8) |
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**South Asian**: Hindi, Marathi, Nepali, Sanskrit, Tamil, Telugu |
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**Middle Eastern**: Arabic, Urdu, Persian/Farsi |
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--- |
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## Usage Examples |
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<details> |
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<summary><b>PP-OCRv5 Models (English, Latin, East Asian, etc.)</b></summary> |
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|
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```python |
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from rapidocr_onnxruntime import RapidOCR |
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# English |
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ocr = RapidOCR( |
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det_model_path="detection/v5/det.onnx", |
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rec_model_path="languages/english/rec.onnx", |
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rec_keys_path="languages/english/dict.txt" |
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) |
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# French, German, Spanish, etc. (32 languages) |
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ocr = RapidOCR( |
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det_model_path="detection/v5/det.onnx", |
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rec_model_path="languages/latin/rec.onnx", |
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rec_keys_path="languages/latin/dict.txt" |
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) |
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# Russian, Bulgarian, Ukrainian, Belarusian |
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ocr = RapidOCR( |
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det_model_path="detection/v5/det.onnx", |
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rec_model_path="languages/eslav/rec.onnx", |
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rec_keys_path="languages/eslav/dict.txt" |
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) |
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# Korean |
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ocr = RapidOCR( |
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det_model_path="detection/v5/det.onnx", |
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rec_model_path="languages/korean/rec.onnx", |
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rec_keys_path="languages/korean/dict.txt" |
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) |
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# Chinese/Japanese |
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ocr = RapidOCR( |
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det_model_path="detection/v5/det.onnx", |
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rec_model_path="languages/chinese/rec.onnx", |
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rec_keys_path="languages/chinese/dict.txt" |
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) |
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# Thai |
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ocr = RapidOCR( |
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det_model_path="detection/v5/det.onnx", |
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rec_model_path="languages/thai/rec.onnx", |
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rec_keys_path="languages/thai/dict.txt" |
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) |
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# Greek |
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ocr = RapidOCR( |
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det_model_path="detection/v5/det.onnx", |
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rec_model_path="languages/greek/rec.onnx", |
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rec_keys_path="languages/greek/dict.txt" |
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) |
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``` |
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</details> |
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<details> |
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<summary><b>PP-OCRv3 Models (Hindi, Arabic, Tamil, Telugu)</b></summary> |
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|
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```python |
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from rapidocr_onnxruntime import RapidOCR |
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# Hindi, Marathi, Nepali, Sanskrit |
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ocr = RapidOCR( |
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det_model_path="detection/v3/det.onnx", |
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rec_model_path="languages/hindi/rec.onnx", |
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rec_keys_path="languages/hindi/dict.txt" |
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) |
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# Arabic, Urdu, Persian/Farsi |
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ocr = RapidOCR( |
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det_model_path="detection/v3/det.onnx", |
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rec_model_path="languages/arabic/rec.onnx", |
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rec_keys_path="languages/arabic/dict.txt" |
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) |
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# Tamil |
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ocr = RapidOCR( |
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det_model_path="detection/v3/det.onnx", |
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rec_model_path="languages/tamil/rec.onnx", |
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rec_keys_path="languages/tamil/dict.txt" |
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) |
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# Telugu |
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ocr = RapidOCR( |
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det_model_path="detection/v3/det.onnx", |
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rec_model_path="languages/telugu/rec.onnx", |
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rec_keys_path="languages/telugu/dict.txt" |
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) |
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``` |
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</details> |
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--- |
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## Full Pipeline with Preprocessing |
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<details> |
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<summary><b>Optional preprocessing for rotated/distorted documents</b></summary> |
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Preprocessing models improve accuracy on rotated or distorted documents: |
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```python |
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from rapidocr_onnxruntime import RapidOCR |
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# Complete pipeline with preprocessing |
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ocr = RapidOCR( |
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det_model_path="detection/v5/det.onnx", |
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rec_model_path="languages/english/rec.onnx", |
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rec_keys_path="languages/english/dict.txt", |
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# Optional preprocessing |
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use_angle_cls=True, |
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angle_cls_model_path="preprocessing/textline-orientation/PP-LCNet_x1_0_textline_ori.onnx" |
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) |
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result, elapsed = ocr("rotated_document.jpg") |
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``` |
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**When to use preprocessing**: |
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- **Document Orientation** (`doc-orientation/`): Scanned documents with unknown rotation (0°/90°/180°/270°) |
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- **Text Line Orientation** (`textline-orientation/`): Upside-down text lines (0°/180°) |
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- **Document Unwarping** (`doc-unwarping/`): Curved pages, warped documents, camera photos |
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**Performance impact**: +10-30% accuracy on distorted images, minimal speed overhead. |
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</details> |
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--- |
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## Repository Structure |
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``` |
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. |
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├── detection/ |
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│ ├── v5/ |
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│ │ ├── det.onnx # 84 MB - PP-OCRv5 detection |
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│ │ └── config.json |
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│ └── v3/ |
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│ ├── det.onnx # 2.3 MB - PP-OCRv3 detection |
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│ └── config.json |
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│ |
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├── languages/ |
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│ ├── english/ |
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│ │ ├── rec.onnx # 7.5 MB |
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│ │ ├── dict.txt |
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│ │ └── config.json |
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│ ├── latin/ # 32 languages |
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│ ├── eslav/ # Russian, Bulgarian, Ukrainian, Belarusian |
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│ ├── korean/ |
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│ ├── chinese/ # Chinese, Japanese |
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│ ├── thai/ |
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│ ├── greek/ |
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│ ├── hindi/ # Hindi, Marathi, Nepali, Sanskrit (v3) |
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│ ├── arabic/ # Arabic, Urdu, Persian (v3) |
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│ ├── tamil/ # Tamil (v3) |
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│ └── telugu/ # Telugu (v3) |
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│ |
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└── preprocessing/ |
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├── doc-orientation/ |
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├── textline-orientation/ |
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└── doc-unwarping/ |
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``` |
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--- |
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## Model Selection |
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| Document Language | Model Path | |
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|-------------------|------------| |
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| English | `languages/english/` | |
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| French, German, Spanish, Italian, Portuguese | `languages/latin/` | |
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| Russian, Bulgarian, Ukrainian, Belarusian | `languages/eslav/` | |
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| Korean | `languages/korean/` | |
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| Chinese, Japanese | `languages/chinese/` | |
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| Thai | `languages/thai/` | |
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| Greek | `languages/greek/` | |
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| Hindi, Marathi, Nepali, Sanskrit | `languages/hindi/` + `detection/v3/` | |
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| Arabic, Urdu, Persian/Farsi | `languages/arabic/` + `detection/v3/` | |
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| Tamil | `languages/tamil/` + `detection/v3/` | |
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| Telugu | `languages/telugu/` + `detection/v3/` | |
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--- |
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|
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## Technical Specifications |
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- **Framework**: PaddleOCR → ONNX |
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- **ONNX Opset**: 11 |
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- **Precision**: FP32 |
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- **Input Format**: RGB images (dynamic size) |
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- **Inference**: CPU/GPU via onnxruntime |
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### Detection Model |
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- **Input**: `(batch, 3, height, width)` - dynamic |
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- **Output**: Text bounding boxes |
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### Recognition Model |
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- **Input**: `(batch, 3, 32, width)` - height fixed at 32px |
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- **Output**: CTC logits → decoded with dictionary |
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|
|
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--- |
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|
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## Performance |
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|
|
|
|
### Accuracy (PP-OCRv5) |
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|
|
|
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| Model | Accuracy | Dataset | |
|
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|-------|----------|---------| |
|
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| Greek | 89.28% | 2,799 images | |
|
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| Korean | 88.0% | 5,007 images | |
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| English | 85.25% | 6,530 images | |
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| Latin | 84.7% | 3,111 images | |
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| Thai | 82.68% | 4,261 images | |
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| East Slavic | 81.6% | 7,031 images | |
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|
|
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--- |
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|
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## FAQ |
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|
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**Q: Which version should I use?** |
|
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A: Use PP-OCRv5 models for best accuracy. Use PP-OCRv3 only for South Asian languages not available in v5. |
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|
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**Q: Can I mix v5 and v3 models?** |
|
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A: No. Use `detection/v5/det.onnx` with v5 recognition models, and `detection/v3/det.onnx` with v3 recognition models. |
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**Q: GPU acceleration?** |
|
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A: Install `onnxruntime-gpu` instead of `onnxruntime` for 10x faster inference. |
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|
|
|
**Q: Commercial use?** |
|
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A: Yes. Apache 2.0 license allows commercial use. |
|
|
|
|
|
--- |
|
|
|
|
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## Credits |
|
|
|
|
|
- **Original Models**: [PaddlePaddle Team](https://github.com/PaddlePaddle/PaddleOCR) |
|
|
- **Conversion**: [paddle2onnx](https://github.com/PaddlePaddle/Paddle2ONNX) |
|
|
- **Source**: [PP-OCRv5 Collection](https://huggingface.co/collections/PaddlePaddle/pp-ocrv5-684a5356aef5b4b1d7b85e4b) |
|
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|
|
|
--- |
|
|
|
|
|
## Links |
|
|
|
|
|
- [PaddleOCR GitHub](https://github.com/PaddlePaddle/PaddleOCR) |
|
|
- [PaddleOCR Documentation](https://paddlepaddle.github.io/PaddleOCR/) |
|
|
- [ONNX Runtime](https://onnxruntime.ai/) |
|
|
- [monkt.com](https://monkt.com) - Document processing pipeline |
|
|
|
|
|
--- |
|
|
|
|
|
**License**: Apache 2.0 |
