Containers are great for specific security and data governance requirements. Azure and the Computer Vision service handle scale, performance, data security, and compliance needs while you focus on meeting your customers' needs.įor on-premises deployment, the Read Docker container enables you to deploy the Computer Vision v3.2 generally available OCR capabilities in your own local environment. The cloud APIs are the preferred option for most customers because of their ease of integration and fast productivity out of the box. Use the OCR cloud APIs or deploy on-premises Available as Distroless Docker container for on-premises deployment.Support for mixed languages, mixed mode (print and handwritten).Pages, text lines and words with location and confidence scores.Printed and handwritten text extraction in supported languages.The following list summarizes the common features: The Read OCR model is available in Computer Vision and Form Recognizer with common baseline capabilities while optimizing for respective scenarios.
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Refer to the full list of OCR-supported languages.
OCR for handwritten text supports English, Chinese Simplified, French, German, Italian, Japanese, Korean, Portuguese, and Spanish languages. OCR for printed text supports English, French, German, Italian, Portuguese, Spanish, Chinese, Japanese, Korean, Russian, Arabic, Hindi, and other international languages that use Latin, Cyrillic, Arabic, and Devanagari scripts. Then follow one of the links to the Read edition that best meet your requirements.īoth Read versions available today in Computer Vision support several languages for printed and handwritten text. To continue, see the Computer Vision v3.2 GA Read overview and quickstart. There will be no further updates to the Computer Vision v3.2.
Looking for the most recent Computer Vision v3.2 GA Read? Note that all future Read OCR enhancements will be part of the two new services listed above. Optimized for text-heavy scanned and digital documents with an asynchronous API to help automate intelligent document processing at scale. Optimized for general, non-document images with a performance-enhanced synchronous API that makes it easier to embed OCR in your user experience scenarios.ĭocuments: Digital and scanned, including images Select the Read edition that best fits your requirements. With the latest preview, it's also available as a synchronous API for single, non-document, image-only scenarios with performance enhancements that make it easier to implement OCR-assisted user experiences. Read is available as cloud service and on-premises container for deployment flexibility. It can extract printed and handwritten text including mixed languages and writing styles. Microsoft's Read OCR engine is composed of multiple advanced machine-learning based models supporting global languages. If you're extracting text from scanned and digital documents, use Form Recognizer Read OCR. Form Recognizer includes a document-optimized version of Read as its OCR engine while delegating to other models for higher-end insights. Intelligent Document Processing (IDP) uses OCR as its foundational technology to additionally extract structure, relationships, key-values, entities, and other document-centric insights with an advanced machine-learning based AI service like Form Recognizer. How is OCR related to Intelligent Document Processing (IDP)?
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This eliminates or significantly reduces the need for manual data entry. The text is typically extracted as words, text lines, and paragraphs or text blocks, enabling access to digital version of the scanned text. Machine-learning-based OCR techniques allow you to extract printed or handwritten text from images such as posters, street signs and product labels, as well as from documents like articles, reports, forms, and invoices. OCR or Optical Character Recognition is also referred to as text recognition or text extraction.
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