AWS DeepLens
Developer Guide

Creating and Deploying an AWS DeepLens Sample Project

To help you get started with AWS DeepLens, we provide a number of sample AWS DeepLens project templates that you can use to create projects and get you up and going quickly. For more information, see AWS DeepLens Sample Projects Overview.

In this walkthrough, you create the Object Detection project. The Object Detection project analyzes images within a video stream on your AWS DeepLens device to identify objects. It can recognize as many as 20 types of objects.

Though the instructions here are specific to the Object Detection project, you can follow the same steps to create and deploy any of the sample projects. When creating a sample project, the fields in the console are pre-populated for you so you can accept the defaults. In the Project content portion of the screen, you need to know the project's model and function. That information is available for the individual projects in the AWS DeepLens Sample Projects Overview topic.

Your web browser is the interface between you and your AWS DeepLens device. You perform all of the following activities on the AWS DeepLens console using your browser.


            Image: Workflow for creating and deploying a sample project

Step 1: Create Your Project

The following procedure creates the Object Detection sample project.

To create an AWS DeepLens project using a sample project

The steps for creating a project encompass two screens. On the first screen you select your project. On the second screen, you specify the project's details.

  1. Using your browser, open the AWS DeepLens console at https://console.aws.amazon.com/deeplens/.

  2. Choose Projects, then choose Create new project.

  3. On the Choose project type screen

    1. Choose Use a project template, then choose the sample project you want to create. For this exercise, choose Object detection.

    2. Scroll to the bottom of the screen, then choose Next.

  4. On the Specify project details screen

    1. In the Project information section:

      1. Either accept the default name for the project, or type a name you prefer.

      2. Either accept the default description for the project, or type a description you prefer.

    2. In the Project content section:

      1. Model—make sure the model is the correct model for the project you're creating. For this exercise it should be deeplens-object-detection. If it isn't, remove the current model then choose Add model. From the list of models, choose deeplens-object-detection.

      2. Function—make sure the functiion is the correct function for the project you're creating. For this exercise it should be deeplens-object-detection. If it isn't, remove the current function then choose Add function. From the list of functions, choose deeplens-object-detection.

    3. Choose Create.

      This returns you to the Projects screen where the project you just created is listed with your other projects.

Step 2: Deploy Your Project

In this walkthrough, you deploy the Object Detection project.

Your web browser is the interface between you and your AWS DeepLens device. You perform all of the following activities on your browser after logging on to AWS:

  1. On the Projects screen, choose the radio button to the left of your project name, then choose Deploy to device.

  2. On the Target device screen, from the list of AWS DeepLens devices, choose the radio button to the left of the device that you want to deploy this project to. An AWS DeepLens device can have only one project deployed to it at a time.

  3. Choose Review.

    If a project is already deployed to the device, you will see an error message that deploying this project will overwrite the project that is already running on the device. Choose Continue project.

    This will take you to the Review and deploy screen.

  4. On the Review and deploy screen, review your project and choose either Previous to go back and make changes, or Deploy to deploy the project.

    Important

    Deploying a project incurs costs for the AWS services that are used to run the project.

For instructions on viewing your project's output, see Viewing AWS DeepLens Output Streams.