Amazon Rekognition APIs

In this tutorial, you will learn about different APIs of Amazon Rekognition.

Pre-requisite

You will be launching a Amazon SageMaker Notebook to make API calls. Download the following CloudFormation template file to launch the notebook in your account.

Amazon SageMaker Notebook is not a requirement to use Amazon Rekognition APIs. For the labs, it provides an environment to run python code and make API calls.

Launch Amazon SageMaker Notebook Instance

Here are the one-time steps for launching Amazon SageMaker Notebook instance using CFN template:

  1. Launch CloudFormation stack in appropriate region

    • US East (N. Virginia) (us-east-1)
    • US West (Oregon) (us-west-2)
    • EU (Ireland) (eu-west-1)
  2. Click “Next” and provide a stack name

  3. Click “Next” and select the box “I acknowledge that AWS CloudFormation might create IAM resources.”

  4. Click “Create stack”

  5. Wait till the status of the stack is “CREATE_COMPLETE”

Download necessary notebooks

  1. Under services search for “Amazon SageMaker”

  2. Click on “Notebook instances”

  3. Look for an instance with name “RekNotebookInstance-” prefix and wait till the status is “InService”

  4. Under Actions, click on “Open Jupyter”

  5. Under the “Files” tab, Open “New” dropdown and click on “Terminal”

  6. In the terminal tab, type

cd SageMaker/
  1. Type
git clone https://github.com/aws-samples/amazon-rekognition-code-samples.git
  1. Open the “rekognition-apis” folder within “amazon-rekognition-code-samples” created under “Files” tab

  2. You should see multiple jupyter notebooks which we will use in the rest of the lab

If you receive Kernel not found, select “conda_python3” from the dropdown.