#Apple ocr series
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 - A series of high-quality pre-trained models, comparable to commercial products.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. 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.Ģ022.3 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).Ģ021.12.21 release PaddleOCR v2.4, OCR open source online course starts.
0 kommentar(er)
