Alternatives to Amazon Rekognition logo

Alternatives to Amazon Rekognition

TensorFlow, OpenCV, Google Cloud Vision API, Tesseract OCR, and Tesseract.js are the most popular alternatives and competitors to Amazon Rekognition.
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What is Amazon Rekognition and what are its top alternatives?

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.
Amazon Rekognition is a tool in the Image Analysis API category of a tech stack.

Top Alternatives to Amazon Rekognition

  • TensorFlow

    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

    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. ...

  • Google Cloud Vision API

    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. ...

  • Tesseract OCR

    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

    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. ...

  • EasyOCR

    EasyOCR

    It is ready-to-use OCR with 40+ languages supported including Chinese, Japanese, Korean and Thai. ...

  • ZXing

    ZXing

    It is a barcode scanning library for Java, Android. Decode a 1D or 2D barcode from an image on the web. ...

  • scanR

    scanR

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

Amazon Rekognition alternatives & related posts

TensorFlow logo

TensorFlow

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Open Source Software Library for Machine Intelligence
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PROS OF TENSORFLOW
  • 25
    High Performance
  • 16
    Connect Research and Production
  • 13
    Deep Flexibility
  • 9
    Auto-Differentiation
  • 9
    True Portability
  • 2
    Easy to use
  • 2
    High level abstraction
  • 1
    Powerful
CONS OF TENSORFLOW
  • 9
    Hard
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    Hard to debug
  • 1
    Documentation not very helpful

related TensorFlow posts

Conor Myhrvold
Tech Brand Mgr, Office of CTO at Uber · | 8 upvotes · 1.3M views

Why we built an open source, distributed training framework for TensorFlow , Keras , and PyTorch:

At Uber, we apply deep learning across our business; from self-driving research to trip forecasting and fraud prevention, deep learning enables our engineers and data scientists to create better experiences for our users.

TensorFlow has become a preferred deep learning library at Uber for a variety of reasons. To start, the framework is one of the most widely used open source frameworks for deep learning, which makes it easy to onboard new users. It also combines high performance with an ability to tinker with low-level model details—for instance, we can use both high-level APIs, such as Keras, and implement our own custom operators using NVIDIA’s CUDA toolkit.

Uber has introduced Michelangelo (https://eng.uber.com/michelangelo/), an internal ML-as-a-service platform that democratizes machine learning and makes it easy to build and deploy these systems at scale. In this article, we pull back the curtain on Horovod, an open source component of Michelangelo’s deep learning toolkit which makes it easier to start—and speed up—distributed deep learning projects with TensorFlow:

https://eng.uber.com/horovod/

(Direct GitHub repo: https://github.com/uber/horovod)

See more

In mid-2015, Uber began exploring ways to scale ML across the organization, avoiding ML anti-patterns while standardizing workflows and tools. This effort led to Michelangelo.

Michelangelo consists of a mix of open source systems and components built in-house. The primary open sourced components used are HDFS, Spark, Samza, Cassandra, MLLib, XGBoost, and TensorFlow.

!

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OpenCV logo

OpenCV

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Open Source Computer Vision Library
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PROS OF OPENCV
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    Computer Vision
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    Open Source
  • 11
    Imaging
  • 9
    Machine Learning
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    Face Detection
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    Great community
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    Realtime Image Processing
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    Image Augmentation
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    Helping almost CV problem
CONS OF OPENCV
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    Shared insights
    on
    FFMPEG
    OpenCV

    Hi Team,

    Could you please suggest which one need to be used in between OpenCV and FFMPEG.

    Thank you in Advance.

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    Google Cloud Vision API logo

    Google Cloud Vision API

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    Understand the content of an image by encapsulating powerful machine learning models
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    PROS OF GOOGLE CLOUD VISION API
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      Built by Google
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      Image Recognition
    CONS OF GOOGLE CLOUD VISION API
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      Tesseract OCR logo

      Tesseract OCR

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      Tesseract Open Source OCR Engine
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      PROS OF TESSERACT OCR
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        Very lightweight library
      • 1
        Building training set is easy
      CONS OF TESSERACT OCR
      • 1
        Works best with white background and black text

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      Aicha Mahfoudh
      Shared insights
      on
      Tesseract OCR
      TensorFlow

      Can I use both TensorFlow and Tesseract OCR to create a model that detects text out of a document pdf

      See more
      Tesseract.js logo

      Tesseract.js

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      Pure JavaScript OCR for 60 Languages
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      PROS OF TESSERACT.JS
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        Graph Recognization
      CONS OF TESSERACT.JS
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        EasyOCR logo

        EasyOCR

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        Ready-to-use OCR with 40 languages
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        PROS OF EASYOCR
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          CONS OF EASYOCR
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            ZXing logo

            ZXing

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            Decode a 1D or 2D barcode from an image on the web
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            PROS OF ZXING
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              CONS OF ZXING
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                scanR logo

                scanR

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                API to detect text in images, built for developers.
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                PROS OF SCANR
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