@@ -19,6 +19,10 @@ PaddleOCR aims to create multilingual, awesome, leading, and practical OCR tools
**Recent updates**
- 2022.5.9 release PaddleOCR v2.5, including:
-[PP-OCRv3](./doc/doc_en/ppocr_introduction_en.md#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%.
-[PPOCRLabelv2](./PPOCRLabel): Add the annotation function for table recognition task, key information extraction task and irregular text image.
- Interactive e-book [*"Dive into OCR"*](./doc/doc_en/ocr_book_en.md), covers the cutting-edge theory and code practice of OCR full stack technology.
- 2021.12.21 release PaddleOCR v2.4, release 1 text detection algorithm (PSENet), 3 text recognition algorithms (NRTR、SEED、SAR), 1 key information extraction algorithm (SDMGR, [tutorial](./ppstructure/docs/kie_en.md)) and 3 DocVQA algorithms (LayoutLM, LayoutLMv2, LayoutXLM, [tutorial](./ppstructure/vqa)).
- 2021.9.7 release PaddleOCR v2.3, [PP-OCRv2](./doc/doc_en/ppocr_introduction_en.md#pp-ocrv2) is proposed. The inference speed of PP-OCRv2 is 220% higher than that of PP-OCR server in CPU device. The F-score of PP-OCRv2 is 7% higher than that of PP-OCR mobile.
- 2021.8.3 released PaddleOCR v2.2, add a new structured documents analysis toolkit, i.e., [PP-Structure](./ppstructure/README.md), support layout analysis and table recognition (One-key to export chart images to Excel files).
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@@ -122,6 +126,9 @@ PaddleOCR support a variety of cutting-edge algorithms related to OCR, and devel
[GTC](https://arxiv.org/pdf/2002.01276.pdf)(Guided Training of CTC),利用Attention模块以及损失,指导CTC损失训练,融合多种文本特征的表达,是一种有效的提升文本识别的策略。使用该策略,预测时完全去除 Attention 模块,在推理阶段不增加任何耗时,识别模型的准确率进一步提升到75.8%(+1.82%)。训练流程如下所示:
[GTC](https://arxiv.org/pdf/2002.01276.pdf)(Guided Training of CTC),利用Attention模块CTC训练,融合多种文本特征的表达,是一种有效的提升文本识别的策略。使用该策略,预测时完全去除 Attention 模块,在推理阶段不增加任何耗时,识别模型的准确率进一步提升到75.8%(+1.82%)。训练流程如下所示:
-[PP-OCRv3](./doc/doc_en/ppocr_introduction_en.md#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%.
-[PPOCRLabelv2](./PPOCRLabel): Add the annotation function for table recognition task, key information extraction task and irregular text image.
- Interactive e-book [*"Dive into OCR"*](./doc/doc_en/ocr_book_en.md), covers the cutting-edge theory and code practice of OCR full stack technology.
- 2022.5.7 Add support for metric and model logging during training to [Weights & Biases](https://docs.wandb.ai/).
- 2021.12.21 OCR open source online course starts. The lesson starts at 8:30 every night and lasts for ten days. Free registration: https://aistudio.baidu.com/aistudio/course/introduce/25207
- 2021.12.21 release PaddleOCR v2.4, release 1 text detection algorithm (PSENet), 3 text recognition algorithms (NRTR、SEED、SAR), 1 key information extraction algorithm (SDMGR) and 3 DocVQA algorithms (LayoutLM、LayoutLMv2,LayoutXLM).