Note
- Compared with the model v2.0, the 2.1 version of the detection model has a improvement in accuracy, and the 2.1 version of the recognition model is optimized in accuracy and CPU speed.
- Compared with models 1.1, which are trained with static graph programming paradigm, models 2.0 are the dynamic graph trained version and achieve close performance.
- All models in this tutorial are all ppocr-series models, for more introduction of algorithms and models based on public dataset, you can refer to algorithm overview tutorial.
- 1. Text Detection Model
- 2. Text Recognition Model
- 3. Text Angle Classification Model
- 4. Paddle-Lite Model
The downloadable models provided by PaddleOCR include inference model, trained model, pre-trained model and slim model. The differences between the models are as follows:
| model type | model format | description |
|---|---|---|
| inference model | inference.pdmodel、inference.pdiparams | Used for inference based on Paddle inference engine，detail |
| trained model, pre-trained model | *.pdparams、*.pdopt、*.states | The checkpoints model saved in the training process, which stores the parameters of the model, mostly used for model evaluation and continuous training. |
| slim model | *.nb | Model compressed by PaddleSim (a model compression tool using PaddlePaddle), which is suitable for mobile-side deployment scenarios (Paddle-Lite is needed for slim model deployment). |
Relationship of the above models is as follows.
| model name | description | config | model size | download |
|---|---|---|---|---|
| ch_PP-OCRv2_det_slim | [New] slim quantization with distillation lightweight model, supporting Chinese, English, multilingual text detection | ch_PP-OCRv2_det_cml.yml | 3M | inference model |
| ch_PP-OCRv2_det | [New] Original lightweight model, supporting Chinese, English, multilingual text detection | ch_PP-OCRv2_det_cml.yml | 3M | inference model / trained model |
| ch_ppocr_mobile_slim_v2.0_det | Slim pruned lightweight model, supporting Chinese, English, multilingual text detection | ch_det_mv3_db_v2.0.yml | 2.6M | inference model |
| ch_ppocr_mobile_v2.0_det | Original lightweight model, supporting Chinese, English, multilingual text detection | ch_det_mv3_db_v2.0.yml | 3M | inference model / trained model |
| ch_ppocr_server_v2.0_det | General model, which is larger than the lightweight model, but achieved better performance | ch_det_res18_db_v2.0.yml | 47M | inference model / trained model |
| model name | description | config | model size | download |
|---|---|---|---|---|
| ch_PP-OCRv2_rec_slim | [New] Slim qunatization with distillation lightweight model, supporting Chinese, English, multilingual text recognition | ch_PP-OCRv2_rec.yml | 9M | inference model / trained model |
| ch_PP-OCRv2_rec | [New] Original lightweight model, supporting Chinese, English, multilingual text recognition | ch_PP-OCRv2_rec_distillation.yml | 8.5M | inference model / trained model |
| ch_ppocr_mobile_slim_v2.0_rec | Slim pruned and quantized lightweight model, supporting Chinese, English and number recognition | rec_chinese_lite_train_v2.0.yml | 6M | inference model / trained model |
| ch_ppocr_mobile_v2.0_rec | Original lightweight model, supporting Chinese, English and number recognition | rec_chinese_lite_train_v2.0.yml | 5.2M | inference model / trained model / pre-trained model |
| ch_ppocr_server_v2.0_rec | General model, supporting Chinese, English and number recognition | rec_chinese_common_train_v2.0.yml | 94.8M | inference model / trained model / pre-trained model |
Note: The trained model is finetuned on the pre-trained model with real data and synthsized vertical text data, which achieved better performance in real scene. The pre-trained model is directly trained on the full amount of real data and synthsized data, which is more suitable for finetune on your own dataset.
| model name | description | config | model size | download |
|---|---|---|---|---|
| en_number_mobile_slim_v2.0_rec | Slim pruned and quantized lightweight model, supporting English and number recognition | rec_en_number_lite_train.yml | 2.7M | inference model / trained model |
| en_number_mobile_v2.0_rec | Original lightweight model, supporting English and number recognition | rec_en_number_lite_train.yml | 2.6M | inference model / trained model |
| model name | dict file | description | config | model size | download |
|---|---|---|---|---|---|
| french_mobile_v2.0_rec | ppocr/utils/dict/french_dict.txt | Lightweight model for French recognition | rec_french_lite_train.yml | 2.65M | inference model / trained model |
| german_mobile_v2.0_rec | ppocr/utils/dict/german_dict.txt | Lightweight model for German recognition | rec_german_lite_train.yml | 2.65M | inference model / trained model |
| korean_mobile_v2.0_rec | ppocr/utils/dict/korean_dict.txt | Lightweight model for Korean recognition | rec_korean_lite_train.yml | 3.9M | inference model / trained model |
| japan_mobile_v2.0_rec | ppocr/utils/dict/japan_dict.txt | Lightweight model for Japanese recognition | rec_japan_lite_train.yml | 4.23M | inference model / trained model |
| chinese_cht_mobile_v2.0_rec | ppocr/utils/dict/chinese_cht_dict.txt | Lightweight model for chinese cht recognition | rec_chinese_cht_lite_train.yml | 5.63M | inference model / trained model |
| te_mobile_v2.0_rec | ppocr/utils/dict/te_dict.txt | Lightweight model for Telugu recognition | rec_te_lite_train.yml | 2.63M | inference model / trained model |
| ka_mobile_v2.0_rec | ppocr/utils/dict/ka_dict.txt | Lightweight model for Kannada recognition | rec_ka_lite_train.yml | 2.63M | inference model / trained model |
| ta_mobile_v2.0_rec | ppocr/utils/dict/ta_dict.txt | Lightweight model for Tamil recognition | rec_ta_lite_train.yml | 2.63M | inference model / trained model |
| latin_mobile_v2.0_rec | ppocr/utils/dict/latin_dict.txt | Lightweight model for latin recognition | rec_latin_lite_train.yml | 2.6M | inference model / trained model |
| arabic_mobile_v2.0_rec | ppocr/utils/dict/arabic_dict.txt | Lightweight model for arabic recognition | rec_arabic_lite_train.yml | 2.6M | inference model / trained model |
| cyrillic_mobile_v2.0_rec | ppocr/utils/dict/cyrillic_dict.txt | Lightweight model for cyrillic recognition | rec_cyrillic_lite_train.yml | 2.6M | inference model / trained model |
| devanagari_mobile_v2.0_rec | ppocr/utils/dict/devanagari_dict.txt | Lightweight model for devanagari recognition | rec_devanagari_lite_train.yml | 2.6M | inference model / trained model |
For more supported languages, please refer to : Multi-language model
| model name | description | config | model size | download |
|---|---|---|---|---|
| ch_ppocr_mobile_slim_v2.0_cls | Slim quantized model for text angle classification | cls_mv3.yml | 2.1M | inference model / trained model |
| ch_ppocr_mobile_v2.0_cls | Original model for text angle classification | cls_mv3.yml | 1.38M | inference model / trained model |
| Version | Introduction | Model size | Detection model | Text Direction model | Recognition model | Paddle-Lite branch |
|---|---|---|---|---|---|---|
| PP-OCRv2 | extra-lightweight chinese OCR optimized model | 11M | download link | download link | download link | v2.9 |
| PP-OCRv2(slim) | extra-lightweight chinese OCR optimized model | 4.9M | download link | download link | download link | v2.9 |
| V2.0 | ppocr_v2.0 extra-lightweight chinese OCR optimized model | 7.8M | download link | download link | download link | v2.9 |
| V2.0(slim) | ppovr_v2.0 extra-lightweight chinese OCR optimized model | 3.3M | download link | download link | download link | v2.9 |