The multilingual support of dots.ocr has two notable features:
- Low Resource Language Optimization: Adopt special training strategy so that the model still maintains a high accuracy rate in Tibetan and other languages with scarce resources, solving the problem of insufficient support for small languages by traditional OCR tools.
- Hybrid Document Processing: automatically recognizes multi-language content in the same document (e.g., mixed contracts in English and Chinese) without the need to specify the language type in advance
- Analysis of Cultural Adaptation: automatically optimize reading order output for different languages (e.g. Arabic right-to-left typography)
The capability is based on training data containing 100 languages, in which the coverage of regional languages such as Southeast Asia and Africa has been especially strengthened, and the actual test shows that the recognition accuracy of low-resource languages is about 23% higher than that of general-purpose OCR tools.
This answer comes from the articledots.ocr: a unified visual-linguistic model for multilingual document layout parsingThe
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