PaddleOCRv2.6.0

Release Note

• Release PP-Structurev2，with functions and performance fully upgraded, adapted to Chinese scenes, and new support for Layout Recovery and one line command to convert PDF to Word;
• Layout Analysis optimization: model storage reduced by 95%, while speed increased by 11 times, and the average CPU time-cost is only 41ms;
• Table Recognition optimization: 3 optimization strategies are designed, and the model accuracy is improved by 6% under comparable time consumption;
• Key Information Extraction optimization：a visual-independent model structure is designed, the accuracy of semantic entity recognition is increased by 2.8%, and the accuracy of relation extraction is increased by 9.1%.

PaddleOCRv2.5.0

Release Note

• Release PP-OCRv3: With comparable speed, the effect of Chinese scene is further improved by 5% compared with PP-OCRv2, the effect of English scene is improved by 11%, and the average recognition accuracy of 80 language multilingual models is improved by more than 5%.
• Release PPOCRLabelv2: Add the annotation function for table recognition task, key information extraction task and irregular text image.
• Release interactive e-book "Dive into OCR", covers the cutting-edge theory and code practice of OCR full stack technology.

PaddleOCRv2.1.1

Release Note

1. Newly release model pruning and model quantization tools based on PaddleSlim. Path
2. Newly release mobile deployment tools based on Paddle-Lite. Path
3. Newly release Android demo of ppocr system. path
4. Newly release service deployment based on Paddle Serving. path

PaddleOCRv2.1.0

Release Note

1. Newly release end-to-end text recognition algorithm PGNet which is published in AAAI 2021. Find tutorial here.
2. Newly release multi language recognition model, support more than 80 languages recognition. Find tutorial here.
3. Optimize the performance of English recognition model.

PaddleOCRv2.0

Release Note

一、Support dynamic graph programming paradigm, adapted to Paddle 2.0, including:

1. Detection algorithm: DB, EAST, SAST
2. Recognition algorithm: Rosetta, CRNN, RARE, SRN, STAR-Net
3. PPOCR Chinese models：
   (1) Detection models: mobile, server
   (2) Text direction classification models: mobile
   (3) Recognition models: mobile, server
4. Multilingual models:
   (1) English: mobile
   (2) Japanese, Korean, French, German, etc. 25 languages in total: mobile

二、The related works on deployment have been well adapted, including Inference(Python, C++) , whl, and serving

三、Release the annotation and synthesis tools:

1. Release a new data synthesis tool, i.e., Style-Text，easy to synthesize a large number of images which are similar to the target scene image.
2. Release a new data annotation tool, i.e., PPOCRLabel, which is helpful to improve the labeling efficiency. Moreover, the labeling results can be used in training of the PP-OCR system directly.

PaddleOCRv1.1

3.5M practical ultra lightweight OCR system, support training and deployment among server, mobile, embedded and IoT devices