Amazon Rekognition vs Google Cloud Vision API vs Tesseract OCR

Amazon Rekognition

+ 1
Google Cloud Vision API

+ 1
Tesseract OCR

+ 1
Decisions about Amazon Rekognition, Google Cloud Vision API, and Tesseract OCR
Vladyslav Holubiev
Software Enginieer at Shelf · | 1 upvotes · 7K views
to add
Tesseract OCR
and to remove
Amazon Rekognition

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.

Worth mentioning that we run Tesseract in AWS Lambda via aws-lambda-tesseract library.

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      - No public GitHub repository available -
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      What is Amazon Rekognition?

      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.

      What is Google Cloud Vision API?

      Google Cloud Vision API enables developers to understand the content of an image by encapsulating powerful machine learning models in an easy to use REST API.

      What is Tesseract OCR?

      Tesseract was originally developed at Hewlett-Packard Laboratories Bristol and at Hewlett-Packard Co, Greeley Colorado between 1985 and 1994, with some more changes made in 1996 to port to Windows, and some C++izing in 1998. In 2005 Tesseract was open sourced by HP. Since 2006 it is developed by Google.
      What companies use Amazon Rekognition?
      What companies use Google Cloud Vision API?
      What companies use Tesseract OCR?

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      What are some alternatives to Amazon Rekognition, Google Cloud Vision API, and Tesseract OCR?
      TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.
      OpenCV was designed for computational efficiency and with a strong focus on real-time applications. Written in optimized C/C++, the library can take advantage of multi-core processing. Enabled with OpenCL, it can take advantage of the hardware acceleration of the underlying heterogeneous compute platform.
      This library supports over 60 languages, automatic text orientation and script detection, a simple interface for reading paragraph, word, and character bounding boxes. Tesseract.js can run either in a browser and on a server with NodeJS.
      It is ready-to-use OCR with 40+ languages supported including Chinese, Japanese, Korean and Thai.
      scanR is a simple OCR API service that supports 32 languages and can extract text from images or PDF files.
      See all alternatives
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