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 pre-order 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 tutorial or if you're looking to do more with your device take a look at the Extending Your AWS DeepLens Project tutorial.
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.
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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)
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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.
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c. Accept the default values in the Project name and Description fields.
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d. On the Project Content sceen, accept the default values for the Model and the Function, and select Create.
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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.
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b. Choose the radio button for the project and select Deploy to device.
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c. On the Target device screen, choose your device from the list, and select Review.
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d. Now it's time to review the details of the deployment and select Deploy.
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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.
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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.
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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.
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c. You should now see the output from AWS DeepLens on the moitor. 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.
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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.
Now that you have deployed a model to AWS DeepLens, pick one of the following options to further expand your knowledge.
Dive deeper
Get even more info on how to use AWS DeepLens. Check out the full Getting Started Guide »
Learn more
Take the next 10-Minute Tutorial in the series and learn how to extend your AWS Deeplens project. View the tutorial here»
Build a project
Get an overview of training a model with Amazon SageMaker and extending it with AWS Lambda. Read the blog here»
