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500K Multilingual OCR Dataset – Document & Scene Text

multilingual OCR dataset
scene text dataset
document OCR images
Chinese OCR
Japanese OCR dataset
Thai text recognition
OCR dataset with annotation
multi-language OCR
document image dataset
OCR training data

500,000 high-resolution images featuring multilingual Optical Character Recognition (OCR) data across both natural scenes and various document types. This dataset spans 20 languages, including Traditional Chinese, Simplified Chinese, Japanese, Korean, Thai, Vietnamese, Indonesian, Malay, Polish, and more. The data covers a wide range of real-world conditions—natural scenes, printed documents, handwritten notes, signs, and posters—captured from multiple countries and environments, with varied backgrounds, lighting conditions, and camera angles. All images are annotated for OCR tasks, making this dataset highly suitable for training deep learning models for text detection, recognition, and layout analysis in multi-language scenarios. The dataset complies with global data protection standards (GDPR, CCPA, PIPL), and is validated by leading AI enterprises for commercial and research applications.

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SpecificationsSpecifications
Data size
500,000 images. For each language, there are 25,000 images in total, including 12,500 natural scene images and 12,500 document images
Language distribution
traditional Chinese, Japanese, Korean, Indonesian, Malay, Thai, Vietnamese, French, German, Italian, Portuguese, Russian, Spanish, Arabic, Turkish, Polish, Dutch, Greek, Czech, Filipino (Tagalog)
Collecting environment
Natural scene: including slogan, receipt, poster, warning sign, road sign, food packaging, billboard, station sign and signboard, etc. Document: electronic documents, meeting minutes, reports, manuals, user manuals, books, newspapers, teaching materials, etc.
Data diversity
including a variety of natural scenes, multiple shooting angles
Device
cellphone, scanner
Photographic angle
looking up angle, looking down angle, eye-level angle
Accuracy rate
according to the collection requirements, the collection accuracy is not less than 97%
Sample Sample
  • 500K Multilingual OCR Dataset – Document & Scene Text
  • 500K Multilingual OCR Dataset – Document & Scene Text
  • 500K Multilingual OCR Dataset – Document & Scene Text
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