What does OCR API return?

What does OCR API return?

Optical Character Recognition (OCR) detects text in an image and extracts the recognized characters into a machine-usable character stream. Upon success, the OCR results will be returned. Upon failure, the error code together with an error message will be returned.

How do you write an API?

You can do this through documentation; adhering to conceptual models; and using concise, symmetrical language.

1. Assume your users won’t read the documentation—until they need to.
2. Create a conceptual model of how your API works.
3. Use clear, consistent, and symmetrical language.
4. Practice the principle of least astonishment.

Is Cloudvision API free?

The Google Cloud Vision API is in general availability and there is a free tier, where you are allowed 1,000 units per Feature Request per month free. Beyond that there is a tiered pricing model based on the number of units that you use in a month.

Can a vision API detect text in an image?

Optical Character Recognition (OCR) The Vision API can detect and extract text from images. There are two annotation features that support optical character recognition (OCR): TEXT_DETECTION detects and extracts text from any image.

Which is the best API for OCR recognition?

Summary: Best OCR APIs OCR API Auto-detect language Text by regions Text annotation (all text as one string) Requests in Free Tier Google Cloud Vision Yes Yes Yes 1,000 Sema Media Data No Yes No 100 Taggun Yes No Yes (invoices) 50 Cloudmersive Yes No Yes 50,000

What can text recognition be used to do?

They can also be used to automate data-entry tasks such as processing credit cards, receipts, and business cards. Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies.

How does entity recognition work in text analytics?

Named entity recognition (NER) is the ability to identify different entities in text and categorize them into pre-defined classes. The supported classes of entities are listed below. In Text Analytics Version 2.1, both entity linking and named entity recognition (NER) are available for several languages.