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Amazon Rekognition Documentation

Amazon Rekognition makes it easy to add image and video analysis to your applications. You just provide an image or video to the Amazon Rekognition API, and the service can identify objects, people, text, scenes, and activities. It can detect any inappropriate content as well. Amazon Rekognition also provides highly accurate facial analysis and facial recognition. With Amazon Rekognition Custom Labels, you can create a machine learning model that finds the objects, scenes, and concepts that are specific to your business needs.

Getting started

  1. Amazon Rekognition Developer Guide

    Get started with Amazon Rekognition Image and Amazon Rekognition Video.
  2. Amazon Rekognition Custom Labels Developer Guide

    Get started with Amazon Rekognition Custom Labels by creating a model with an example dataset.
  3. What is Amazon Rekognition?

    A video introduction to Amazon Rekognition.

Documentation and SDKs

  1. Provides a conceptual overview of Amazon Rekognition, detailed instructions for using the various features, and a complete API reference for developers.
  2. Provides information about creating an Amazon Rekognition Custom Labels model that predicts the presence of objects, scenes, and concepts in images. It includes instructions for training a model, evaluating a model, and using the model to make predictions.
  3. Describes all the API operations for Amazon Rekognition in detail.
  4. Documents the AWS CLI commands for Amazon Rekognition.
  5. AWS SDKs for programming Amazon Rekognition.

    Using Amazon Rekognition

    1. Detect real users and deter bad actors using spoofs in seconds during facial verification.
    2. Detect thousands of objects and scenes, plus activities such as "delivering a package" or "playing soccer" in images, stored videos, and streaming videos.
    3. Detect custom objects in images such as brand logos using automated machine learning (AutoML) to train your models with as few as 10 images.
    4. Detect faces appearing in images and stored videos and recognize attributes such as open eyes, glasses, and facial hair for each.
    5. Determine the similarity of a face against another picture or from your private image repository.
    6. Identify well-known people to catalog photos and footage for media, marketing, and advertising in images and stored videos.
    7. Detect potentially unsafe, inappropriate, or unwanted content across images and stored videos.
    8. Extract skewed and distorted text from images and stored videos of street signs, social media posts, and product packaging.
    9. Detect key segments in stored videos, such as black frames, start or end credits, slates, color bars, and shots.
    10. Track the path people take in stored videos.
    11. Improve workplace safety practices by detecing personal protective equipment (PPE) worn by persons in an image.

    Tutorials and code examples

    1. Tutorials

      Tutorials for using Amazon Rekognition.
    2. Developer center code examples for using Amazon Rekognition.

    Resources

    1. Read the Amazon Rekognition blogs.
      • Find answers to frequently asked questions.
      • Responsible use of Amazon Rekognition face matching.
      • Find crowd-sourced, expert-reviewed answers to your Amazon Rekognition questions.
        • Get more information about Amazon Rekognition.
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