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Amazon Rekognition vs scanR: What are the differences?
Developers describe Amazon Rekognition as "Image Detection and Recognition Powered by Deep Learning". Amazon Rekognition is a service that makes it easy to add image analysis to your applications. With Rekognition, you can detect objects, scenes, and faces in images. You can also search and compare faces. Rekognition’s API enables you to quickly add sophisticated deep learning-based visual search and image classification to your applications. On the other hand, scanR is detailed as "API to detect text in images, built for developers". scanR is a simple OCR API service that supports 32 languages and can extract text from images or PDF files.
Amazon Rekognition and scanR belong to "Image Analysis API" category of the tech stack.
AWS Rekognition has an OCR feature but can recognize only up to 50 words per image, which is a deal-breaker for us. (see my tweet).
Also, we discovered fantastic speed and quality improvements in the 4.x versions of Tesseract. Meanwhile, the quality of AWS Rekognition's OCR remains to be mediocre in comparison.
We run Tesseract serverlessly in AWS Lambda via aws-lambda-tesseract library that we made open-source.
Pros of Amazon Rekognition
- Integrate easily with AWS4
Pros of scanR
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Cons of Amazon Rekognition
- AWS1
