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Description
500,000 Images - Natural Scenes & Document Photograph Scenes & Electronic Scenes OCR Data of 21 Countries. The data covers 21 languages, with each language having a quantity ranging from 20,000 to 25,000 images. The data types include natural scenes, document photography scenes, and electronic scenes. The data diversity includes various data types, multiple shooting angles, and multiple languages. In terms of annotation, quadrilateral or polygonal at the row (column) level and content transcription at the row (column) level are adopted. The data can be used for multilingual OCR recognition tasks.
For more details, please refer to the link: https://www.nexdata.ai/datasets/ocr/1862?source=Huggingface
Specifications
Data size：
500,000 images, the quantity of each language is distributed between 20,000 and 25,000
Language distribution：
German, French, Portuguese, Italian, Spanish, Indonesian, Russian, Japanese, Korean, Vietnamese, Polish, Czech, Turkish, Filipino, Dutch, Hindi, Malay, Kazakh, Slovak, Romanian, Uzbek
Collection environment：
(1)Document photograph scenes: books, newspapers, various types of cards, receipts, etc. (2) Natural scenes: posters, warnings signs, road signs, food packaging, billboards, bus stops, signs, etc.(3) Electronic scenes: screenshots from mobile phones, computer screenshots, electronic documents
Document photograph scenes：
books, newspapers, various types of cards, receipts, etc.
Natural scenes：
posters, warnings signs, road signs, food packaging, billboards, bus stops, signs, etc.
Electronic scenes：
screenshots from mobile phones, computer screenshots, electronic documents
Diversity of collection：
multiple data types, various shooting angles, multiple languages
Collection equipment：
cellphone, computer
Data format：
the image format is .jpg and other common formats, the annotation document format is .json
Annotation content：
quadrilateral or polygonal annotation at the row (column) level, transcription of content at the row (column) level
Acuuracy rate：
the accuracy of the row-level detection boxes is no less than 97%. If the boxes are correctly arranged in rows and the deviation from the edges is no more than 5 pixels, they are considered as correctly labeled The transcribing accuracy at the row and character levels is no less than 97%
Licensing Information
Commercial License
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