Support Linux, Windows, MacOS and other systems.

Support user-defined training, provides rich predictive inference deployment solutions.

Data synthesis tool, i.e., Style-Text: easy to synthesize a large number of images which are similar to the target scene image.

Semi-automatic data annotation tool, i.e., PPOCRLabel: support fast and efficient data annotation.

support layout analysis and table recognition (support export to Excel).

PP-Structure: a document structurize system.

Support multi-language recognition: about 80 languages like Korean, Japanese, German, French, etc.

Support Chinese, English, and digit recognition, vertical text recognition, and long text recognition.

General PP-OCR server series models: detection (47.1M) + direction classifier (1.4M) + recognition (94.9M) = 143.4M.

Ultra lightweight PP-OCR mobile series models: detection (3.0M) + direction classifier (1.4M) + recognition (5.0M) = 9.4M.

Ultra lightweight PP-OCRv2 series models: detection (3.1M) + direction classifier (1.4M) + recognition 8.5M) = 13.0M.PP-OCR series of high-quality pre-trained models, comparable to commercial effects.Find tutorial here；release multi language recognition models, support more than 80 languages recognition especically, the performance of English recognition model is Optimized. The F-score of PP-OCRv2 is 7% higher than that of PP-OCR mobile.Ģ021.8.3 released PaddleOCR v2.2, add a new structured documents analysis toolkit, i.e., PP-Structure, support layout analysis and table recognition (One-key to export chart images to Excel files).Ģ021.4.8 release end-to-end text recognition algorithm PGNet which is published in AAAI 2021. The inference speed of PP-OCRv2 is 220% higher than that of PP-OCR server in CPU device. PaddleOCR R&D team would like to share the key points of PP-OCRv2, at 20:15 pm on September 8th, Course Address.Ģ021.9.7 release PaddleOCR v2.3, PP-OCRv2 is proposed. Free registration: Ģ021.12.21 release PaddleOCR v2.4, release 1 text detection algorithm (PSENet), 3 text recognition algorithms (NRTR、SEED、SAR), 1 key information extraction algorithm (SDMGR, tutorial) and 3 DocVQA algorithms (LayoutLM, LayoutLMv2, LayoutXLM, tutorial). The lesson starts at 8:30 every night and lasts for ten days. PaddleOCR aims to create multilingual, awesome, leading, and practical OCR tools that help users train better models and apply them into practice.Ģ021.12.21 OCR open source online course starts.

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