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Both Rekognition and Textract possess the ability to detect text within images, yet they are optimized for differing applications.
Rekognition specializes in identifying text located spatially within an image, for instance, words displayed on street signs, t-shirts, or license plates. Its typical use cases encompass visual search, content filtering, deriving insights from content, among others. However, it's not the ideal choice for images containing more than 100 words, as this exceeds its limitation.
On the other hand, Textract is tailored more towards processing documents and PDFs, offering a comprehensive suite for Optical Character Recognition (OCR). It proves useful in scenarios involving financial reports, medical records, receipts, ID documents, and more.
When it comes to the question of accuracy, it would depend on the use case that is at hand.
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