PaddleOCR/doc/doc_en/models_list_en.md

OCR Model List（V3, updated on 2022.4.28）

Note

1. Compared with model v2, the 3rd version of the detection model has an improvement in accuracy, and the 2.1 version of the recognition model has optimizations in accuracy and speed with CPU.
2. Compared with models 1.1, which are trained with static graph programming paradigm, models 2.0 or higher are the dynamic graph trained version and achieve close performance.
3. All models in this tutorial are from the PaddleOCR series, for more introduction to algorithms and models based on the public dataset, you can refer to algorithm overview tutorial.

• OCR Model List（V3, updated on 2022.4.28）
  • 1. Text Detection Model
    • 1.1 Chinese Detection Model
    • 2.2 English Detection Model
    • 1.3 Multilingual Detection Model
  • 2. Text Recognition Model
    • 2.1 Chinese Recognition Model
    • 2.2 English Recognition Model
    • 2.3 Multilingual Recognition Model（Updating...）
  • 3. Text Angle Classification Model
  • 4. Paddle-Lite Model

The downloadable models provided by PaddleOCR include the inference model, trained model, pre-trained model and nb 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, is mostly used for model evaluation and continuous training.
nb model	*.nb	Model optimized by Paddle-Lite, which is suitable for mobile-side deployment scenarios (Paddle-Lite is needed for nb model deployment).

The relationship of the above models is as follows.

1. Text Detection Model

1. Chinese Detection Model

model name	description	config	model size	download
ch_PP-OCRv3_det_slim	[New] slim quantization with distillation lightweight model, supporting Chinese, English, multilingual text detection	ch_PP-OCRv3_det_cml.yml	1.1M	inference model / trained model / nb model
ch_PP-OCRv3_det	[New] Original lightweight model, supporting Chinese, English, multilingual text detection	ch_PP-OCRv3_det_cml.yml	3.8M	inference model / trained model
ch_PP-OCRv2_det_slim	[New] slim quantization with distillation lightweight model, supporting Chinese, English, multilingual text detection	ch_PP-OCRv2_det_cml.yml	3.0M	inference model
ch_PP-OCRv2_det	[New] Original lightweight model, supporting Chinese, English, multilingual text detection	ch_PP-OCRv2_det_cml.yml	3.0M	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	3.0M	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	47.0M	inference model / trained model

1.2 English Detection Model

model name	description	config	model size	download
en_PP-OCRv3_det_slim	[New] Slim quantization with distillation lightweight detection model, supporting English	ch_PP-OCRv3_det_cml.yml	1.1M	inference model / trained model / nb model
en_PP-OCRv3_det	[New] Original lightweight detection model, supporting English	ch_PP-OCRv3_det_cml.yml	3.8M	inference model / trained model

• Note: English configuration file is the same as Chinese except for training data, here we only provide one configuration file.

1.3 Multilingual Detection Model

model name	description	config	model size	download
ml_PP-OCRv3_det_slim	[New] Slim quantization with distillation lightweight detection model, supporting English	ch_PP-OCRv3_det_cml.yml	1.1M	inference model / trained model / nb model
ml_PP-OCRv3_det	[New] Original lightweight detection model, supporting English	ch_PP-OCRv3_det_cml.yml	3.8M	inference model / trained model

• Note: English configuration file is the same as Chinese except for training data, here we only provide one configuration file.

2. Text Recognition Model

2.1 Chinese Recognition Model

model name	description	config	model size	download
ch_PP-OCRv3_rec_slim	[New] Slim quantization with distillation lightweight model, supporting Chinese, English text recognition	ch_PP-OCRv3_rec_distillation.yml	4.9M	inference model / trained model / nb model
ch_PP-OCRv3_rec	[New] Original lightweight model, supporting Chinese, English, multilingual text recognition	ch_PP-OCRv3_rec_distillation.yml	12.4M	inference model / trained model
ch_PP-OCRv2_rec_slim	Slim quantization with distillation lightweight model, supporting Chinese, English text recognition	ch_PP-OCRv2_rec.yml	9.0M	inference model / trained model
ch_PP-OCRv2_rec	Original lightweight model, supporting Chinese, English, and 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	6.0M	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 fine-tuned on the pre-trained model with real data and synthesized vertical text data, which achieved better performance in the real scene. The pre-trained model is directly trained on the full amount of real data and synthesized data, which is more suitable for fine-tuning your dataset.

2.2 English Recognition Model

model name	description	config	model size	download
en_PP-OCRv3_rec_slim	[New] Slim quantization with distillation lightweight model, supporting English, English text recognition	en_PP-OCRv3_rec.yml	3.2M	inference model / trained model / nb model
en_PP-OCRv3_rec	[New] Original lightweight model, supporting English, English, multilingual text recognition	en_PP-OCRv3_rec.yml	9.6M	inference model / trained model
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

Note: Dictionary file of all English recognition models is ppocr/utils/en_dict.txt.

2.3 Multilingual Recognition Model（Updating...）

model name	dict file	description	config	model size	download
korean_PP-OCRv3_rec	ppocr/utils/dict/korean_dict.txt	Lightweight model for Korean recognition	korean_PP-OCRv3_rec.yml	11.0M	inference model / trained model
japan_PP-OCRv3_rec	ppocr/utils/dict/japan_dict.txt	Lightweight model for Japanese recognition	japan_PP-OCRv3_rec.yml	11.0M	inference model / trained model
chinese_cht_PP-OCRv3_rec	ppocr/utils/dict/chinese_cht_dict.txt	Lightweight model for chinese cht	chinese_cht_PP-OCRv3_rec.yml	12.0M	inference model / trained model
te_PP-OCRv3_rec	ppocr/utils/dict/te_dict.txt	Lightweight model for Telugu recognition	te_PP-OCRv3_rec.yml	9.6M	inference model / trained model
ka_PP-OCRv3_rec	ppocr/utils/dict/ka_dict.txt	Lightweight model for Kannada recognition	ka_PP-OCRv3_rec.yml	9.9M	inference model / trained model
ta_PP-OCRv3_rec	ppocr/utils/dict/ta_dict.txt	Lightweight model for Tamil recognition	ta_PP-OCRv3_rec.yml	9.6M	inference model / trained model
latin_PP-OCRv3_rec	ppocr/utils/dict/latin_dict.txt	Lightweight model for latin recognition	latin_PP-OCRv3_rec.yml	9.7M	inference model / trained model
arabic_PP-OCRv3_rec	ppocr/utils/dict/arabic_dict.txt	Lightweight model for arabic recognition	arabic_PP-OCRv3_rec.yml	9.6M	inference model / trained model
cyrillic_PP-OCRv3_rec	ppocr/utils/dict/cyrillic_dict.txt	Lightweight model for cyrillic recognition	cyrillic_PP-OCRv3_rec.yml	9.6M	inference model / trained model
devanagari_PP-OCRv3_rec	ppocr/utils/dict/devanagari_dict.txt	Lightweight model for devanagari recognition	devanagari_PP-OCRv3_rec.yml	9.9M	inference model / trained model

For a complete list of languages ​​and tutorials, please refer to Multi-language model

3. Text Angle Classification 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 / nb model
ch_ppocr_mobile_v2.0_cls	Original model for text angle classification	cls_mv3.yml	1.38M	inference model / trained model

4. Paddle-Lite Model

Paddle Lite is an updated version of Paddle-Mobile, an open-open source deep learning framework designed to make it easy to perform inference on mobile, embedded, and IoT devices. It can further optimize the inference model and generate the nb model used for edge devices. It's suggested to optimize the quantization model using Paddle-Lite because the INT8 format is used for the model storage and inference.

This chapter lists OCR nb models with PP-OCRv2 or earlier versions. You can access the latest nb models from the above tables.

Version	Introduction	Model size	Detection model	Text Direction model	Recognition model	Paddle-Lite branch
PP-OCRv2	extra-lightweight chinese OCR optimized model	11.0M	download link	download link	download link	v2.10
PP-OCRv2(slim)	extra-lightweight chinese OCR optimized model	4.6M	download link	download link	download link	v2.10
PP-OCRv2	extra-lightweight chinese OCR optimized model	11.0M	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