Creating and Deploying an AWS DeepLens Project

Introduction

This step-by-step tutorial will guide you through creating and deploying your first deep learning model with AWS DeepLens. AWS DeepLens is a programmable video camera designed to expand deep learning development skills. It comes with tutorials, code, and pre-trained models. In this tutorial, you will create a project, then deploy and view the project output directly from the device

You will need an AWS DeepLens device in order to complete this tutorial. You can order one now on amazon.com

If you want to view the project output on a monitor you will also need: USB keyboard, USB mouse, monitor with Micro HDMI cable and a USB hub. 

If this is your first time using your AWS DeepLens, start with the Configure Your New AWS DeepLens video tutorial or if you're looking to do more with your device take a look at the Extending Your AWS DeepLens Project tutorial.

 Services Used

Completing AWS DeepLens set up requires an AWS Account

Implementation

  • Enter the AWS DeepLens Console

    Open the AWS Management Console in a new browser window, so you can keep this step-by-step guide open.  When the screen loads, enter your user name and password to get started. Then type DeepLens in the search bar and select AWS DeepLens to open the console.

    Enter the AWS DeepLens Console
  • Create your project

    In this step, you will create a new project in the AWS DeepLens Console using one of the pre-populated project templates.

    a. The console should open on the Projects screen where you'll see an empty project list, select Create new project on the top right (if you don’t see the project list view, click on the hamburger menu on the left and select Projects)

    Create a new project

    b. Choose, Use a project template as the Project type, and select Object detection from the project templates list.

    Scroll down the screen and select Next.

    Choose project type

    c. Accept the default values in the Project name and Description fields.

    Accept the default values in the Project name and Description fields

    d. On the Project Content sceen, accept the default values for the Model and the Function, and select Create.

    On the Project Content sceen, accept the default values for the Model and the Function, and select Create
  • Deploy it to the device

    In this step, you will deploy the Object detection project to your AWS DeepLens device.

    a. Verify that the project was created successfully, and select it from the list to start the deployment flow.

    Verify that the project was created successfully, and select it from the list to start the deployment flow

    b. Choose the radio button for the project and select Deploy to device.

    Choose the radio button for the project and select Deploy to device

    c. On the Target device screen, choose your device from the list, and select Review.

    On the Target device screen, choose your device from the list, and select Review

    d. Now it's time to review the details of the deployment and select Deploy.

    Now it's time to review the details of the deployment and select Deploy

    e. On the AWS DeepLens console, you can track the progress of the deployment. It can take a few minutes to transfer a large model file to the device.

    On the AWS DeepLens console, you can track the progress of the deployment
  • View the project output

    In this final step, you will configure a media player to view the project output from the AWS DeepLens device.

    a. Select View project stream on the MyDevice page.

    Select View project stream on the MyDevice page

    b. Follow the step-by-step instructions provided in the console, including entering the command: mplayer -demuxer lavf -lavfdopts format=mjpeg:probesize=32 /tmp/results.mjpeg to start a media player and watch your project's video stream.

    Follow the step-by-step instructions provided in the console, including entering the command

    c. You should now see the output from AWS DeepLens on the monitor.  You're all set to go start detecting objects! Get started by pointing the AWS DeepLens at your laptop or water bottle to see what happens.

    You should now see the output from AWS DeepLens on the monitor

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Congratulations!

You have created your first deep learning computer vision project!

You can now play around the other project templates, try extending your project functionality with AWS Lambda or train a deep learning model using Amazon SageMaker.