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AWS DeepLens

AWS DeepLens

AWS DeepLens Cheat Sheet

  • A deep learning-enabled camera for developers
  • A wireless-enabled camera integrated with AWS Cloud
  • Capable of delivering 100GFLOPS of computing power (1 billion operations per second)
  • Contains sample projects at launch to get you started
  • Optimized for Apache MXNet, TensorFlow, and Caffe
  • Integrates with Amazon Rekognition for advanced image analysis
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Common use cases

  • Developing computer vision applications such as:
    • Face Detection
    • Activity Detection
    • Object Detection
    • Bird Classification 
    • Artistic Style Transfer

AWS DeepLens needs 3 AWS services to create a project:

  • Amazon SageMaker 
    • Train/validate custom or pre-trained models 
  • AWS Lambda
    • Preprocessing 
    • Capturing inference
    • Displaying output
  • AWS IoT Greengrass
    • Deploys application project and Lambda runtime to AWS DeepLens 
    • Handles software and configuration updates

AWS DeepLens Device Library

  • awscam module
      • Runs inference code based on a project’s model.
  • mo module
      • Converts Caffe, Apache MXNet, or TensorFlow deep-learning model artifacts into AWS DeepLens model artifacts.
      • Provides optimizations for AWS DeepLens model artifacts.
  • DeepLens_Kinesis_Video module
    • Can send video feeds from the AWS DeepLens device to Amazon Kinesis Video Streams.

Note: If you are studying for the AWS Certified Machine Learning Specialty exam, we highly recommend that you take our AWS Certified Machine Learning – Specialty Practice Exams and read our Machine Learning Specialty exam study guide.

AWS Certified Machine Learning Specialty Practice Exams

AWS DeepLens Cheat Sheet References:


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Written by: Carlo Acebedo

Carlo is a cloud engineer and a content creator at Tutorials Dojo. He's also a member of the AWS Community builder and holds 5 AWS Certifications. Carlo specializes in building and automating solutions in the Amazon Web Services Cloud.

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