Amazon Rekognition vs Google Cloud Vision API vs scanR

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Amazon Rekognition

78
150
+ 1
4
Google Cloud Vision API

132
274
+ 1
16
scanR

2
44
+ 1
0
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Pros of Amazon Rekognition
Pros of Google Cloud Vision API
Pros of scanR
  • 4
    Integrate easily with AWS
  • 9
    Image Recognition
  • 7
    Built by Google
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    Cons of Amazon Rekognition
    Cons of Google Cloud Vision API
    Cons of scanR
    • 1
      AWS
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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 scanR?

        scanR is a simple OCR API service that supports 32 languages and can extract text from images or PDF files.

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        What companies use Amazon Rekognition?
        What companies use Google Cloud Vision API?
        What companies use scanR?
          No companies found

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          What tools integrate with Amazon Rekognition?
          What tools integrate with Google Cloud Vision API?
          What tools integrate with scanR?
            No integrations found
            What are some alternatives to Amazon Rekognition, Google Cloud Vision API, and scanR?
            TensorFlow
            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
            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.
            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.
            Tesseract.js
            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.
            libpng
            It is the official Portable Network Graphics (PNG) reference library. It is a platform-independent library that contains C functions for handling PNG images. It supports almost all of PNG's features, is extensible, and has been widely used and tested.
            See all alternatives