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117 lines
6.9 KiB
Markdown
117 lines
6.9 KiB
Markdown
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---
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comments: true
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---
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# 1. Introduction to PP-OCRv5 Multilingual Text Recognition
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PP-OCRv5 is the latest generation of the PP-OCR series text recognition solutions, focusing on text recognition tasks across multiple scenarios and languages. By default, the recognition model supports accurate recognition of five mainstream text types: Simplified Chinese, Chinese Pinyin, Traditional Chinese, English, and Japanese. In addition, PP-OCRv5 provides multilingual recognition capabilities covering 37 languages, including Korean, Spanish, French, Portuguese, German, Italian, Russian, and more (see [Section 4](#4-supported-languages-and-abbreviations) for the full list of supported languages and abbreviations). Compared to the previous PP-OCRv3 version, PP-OCRv5 achieves more than a 30% improvement in recognition accuracy for multilingual tasks.
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## 2. Quick Start
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You can use the `--lang` parameter in the command line to specify the text recognition model for your target language when running the general OCR pipeline:
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```bash
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# Use the `--lang` parameter to specify the French recognition model
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paddleocr ocr -i https://paddle-model-ecology.bj.bcebos.com/paddlex/imgs/demo_image/general_ocr_french01.png \
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--lang fr \
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--use_doc_orientation_classify False \
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--use_doc_unwarping False \
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--use_textline_orientation False \
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--save_path ./output \
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--device gpu:0
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```
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For explanations of other command line parameters, please refer to the [command line usage](../../pipeline_usage/OCR.en.md#21-command-line) of the general OCR pipeline. After execution, results will be printed to the terminal:
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```bash
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{'res': {'input_path': '/root/.paddlex/predict_input/general_ocr_french01.png', 'page_index': None, 'model_settings': {'use_doc_preprocessor': True, 'use_textline_orientation': False}, 'doc_preprocessor_res': {'input_path': None, 'page_index': None, 'model_settings': {'use_doc_orientation_classify': False, 'use_doc_unwarping': False}, 'angle': -1}, 'dt_polys': array([[[119, 23],
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...,
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[118, 75]],
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...,
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[[109, 506],
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...,
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[108, 556]]], dtype=int16), 'text_det_params': {'limit_side_len': 64, 'limit_type': 'min', 'thresh': 0.3, 'max_side_limit': 4000, 'box_thresh': 0.6, 'unclip_ratio': 1.5}, 'text_type': 'general', 'textline_orientation_angles': array([-1, ..., -1]), 'text_rec_score_thresh': 0.0, 'rec_texts': ['mifere; la profpérité & les fuccès ac-', 'compagnent l’homme induftrieux.', 'Quel eft celui qui a acquis des ri-', 'cheffes, qui eft devenu puiffant, qui', 's’eft couvert de gloire, dont l’éloge', 'retentit par-tout, qui fiege au confeil', "du Roi? C'eft celui qui bannit la pa-", "reffe de fa maifon, & qui a dit à l'oifi-", 'veté : tu es mon ennemie.'], 'rec_scores': array([0.98409832, ..., 0.98091048]), 'rec_polys': array([[[119, 23],
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...,
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[118, 75]],
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...,
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[[109, 506],
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...,
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[108, 556]]], dtype=int16), 'rec_boxes': array([[118, ..., 81],
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...,
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[108, ..., 562]], dtype=int16)}}
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```
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If you specify `save_path`, the visualization results will be saved in the `save_path` directory. An example visualization is shown below:
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<img src="https://raw.githubusercontent.com/cuicheng01/PaddleX_doc_images/refs/heads/main/images/pipelines/ocr/general_ocr_french01_res.png"/>
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You can also use Python code to specify the recognition model for your target language using the `lang` parameter when initializing the general OCR pipeline:
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```python
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from paddleocr import PaddleOCR
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ocr = PaddleOCR(
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lang="fr", # Specify the French recognition model via the lang parameter
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use_doc_orientation_classify=False, # Disable document orientation classification
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use_doc_unwarping=False, # Disable text image unwarping
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use_textline_orientation=False, # Disable textline orientation classification
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)
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result = ocr.predict("https://paddle-model-ecology.bj.bcebos.com/paddlex/imgs/demo_image/general_ocr_french01.png")
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for res in result:
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res.print()
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res.save_to_img("output")
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res.save_to_json("output")
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```
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For more details on the `PaddleOCR` class parameters, refer to the [Python script integration](../../pipeline_usage/OCR.en.md#22-python-script-integration) of the general OCR pipeline.
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## 3. Benchmark Comparison
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| Model | Korean Dataset Accuracy (%) | | Model | Latin Script Languages Dataset Accuracy (%) | | Model | East Slavic Languages Dataset Accuracy (%) |
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|--|--|--|--|--|--|--|--|
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| korean_PP-OCRv5_mobile_rec | 88.0 | | latin_PP-OCRv5_mobile_rec | 84.7 | | eslav_PP-OCRv5_mobile_rec | 85.8 |
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| korean_PP-OCRv3_mobile_rec | 23.0 | | latin_PP-OCRv3_mobile_rec | 37.9 | | cyrillic_PP-OCRv3_mobile_rec| 50.2 |
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**Notes:**
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- Korean Dataset: PP-OCRv5's latest dataset containing 5,007 Korean text images.
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- Latin Script Languages Dataset: The latest PP-OCRv5 recognition dataset, containing 3,111 text images in Latin script languages.
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- East Slavic Languages Dataset: PP-OCRv5's latest dataset containing a total of 7,031 Russian, Belarusian, and Ukrainian text images.
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## 4. Supported Languages and Abbreviations
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| Language | Description | Abbreviation | | Language | Description | Abbreviation |
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| --- | --- | --- | ---|--- | --- | --- |
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| Chinese | Chinese & English | ch | | Hungarian | Hungarian | hu |
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| English | English | en | | Serbian (Latin) | Serbian(latin) | rslatin |
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| French | French | fr | | Indonesian | Indonesian | id |
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| German | German | de | | Occitan | Occitan | oc |
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| Japanese | Japanese | japan | | Icelandic | Icelandic | is |
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| Korean | Korean | korean | | Lithuanian | Lithuanian | lt |
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| Chinese Traditional | Chinese Traditional | chinese_cht | | Maori | Maori | mi |
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| Afrikaans | Afrikaans | af | | Malay | Malay | ms |
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| Italian | Italian | it | | Dutch | Dutch | nl |
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| Spanish | Spanish | es | | Norwegian | Norwegian | no |
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| Bosnian | Bosnian | bs | | Polish | Polish | pl |
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| Portuguese | Portuguese | pt | | Slovak | Slovak | sk |
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| Czech | Czech | cs | | Slovenian | Slovenian | sl |
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| Welsh | Welsh | cy | | Albanian | Albanian | sq |
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| Danish | Danish | da | | Swedish | Swedish | sv |
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| Estonian | Estonian | et | | Swahili | Swahili | sw |
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| Irish | Irish | ga | | Tagalog | Tagalog | tl |
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| Croatian | Croatian | hr | | Turkish | Turkish | tr |
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| Uzbek | Uzbek | uz | | Latin | Latin | la |
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| Russian | Russian | ru | | Belarusian | Belarusian | be |
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| Ukrainian | Ukranian | uk | | | | |
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