ocr

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PaddleOCR Model Deployment

PaddleOCR contains a series of tasks with multiple models, including

• Text detection DBDetector
• [Optional] Direction classification Classifer is used to adjust the direction of images before text recognition
• Character recognition Recognizer is used to recognize characters from images

According to different scenarios, FastDeploy provides the following OCR task deployment. Users need to download three models and dictionary files (or two, optional classifier) simultaneously to complete the entire OCR prediction process

PP-OCR Model in English and Chinese Scenarios

The model download links in the following table are provided by PaddleOCR model library. Refer to PP-OCR Model List for details

OCR version	Text box detection	Direction classification model	Character recognition	Dictionary file	Note
ch_PP-OCRv3[Recommended]	ch_PP-OCRv3_det	ch_ppocr_mobile_v2.0_cls	ch_PP-OCRv3_rec	ppocr_keys_v1.txt	OCRv3 Original Ultra-Lightweight Model supports text detection in Chinese, English and multiple languages
en_PP-OCRv3[Recommended]	en_PP-OCRv3_det	ch_ppocr_mobile_v2.0_cls	en_PP-OCRv3_rec	en_dict.txt	OCRv3 Original Ultra-Lightweight Model supports English and digital recognition. Its training data of detection model and recognition model is different from that of Chinese model, and no other differences can be detected
ch_PP-OCRv2	ch_PP-OCRv2_det	ch_ppocr_mobile_v2.0_cls	ch_PP-OCRv2_rec	ppocr_keys_v1.txt	OCRv2 Original Ultra-Lightweight Model supports text detection in Chinese, English and multiple languages
ch_PP-OCRv2_mobile	ch_ppocr_mobile_v2.0_det	ch_ppocr_mobile_v2.0_cls	ch_ppocr_mobile_v2.0_rec	ppocr_keys_v1.txt	OCRv2 Original Ultra-Lightweight Model Supports text detection in Chinese, English and multiple languages with lighter weight than PPOCRv2
ch_PP-OCRv2_server	ch_ppocr_server_v2.0_det	ch_ppocr_mobile_v2.0_cls	ch_ppocr_server_v2.0_rec	ppocr_keys_v1.txt	OCRv2 Server Model supports text detection in Chinese, English and multiple languages. It has better effects though being larger than the ultra-lightweight model