In this tutorial, you will learn about different APIs of Amazon Rekognition.
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.
Here are the one-time steps for launching Amazon SageMaker Notebook instance using CFN template:
Launch CloudFormation stack in appropriate region
Click “Next” and provide a stack name
Click “Next” and select the box “I acknowledge that AWS CloudFormation might create IAM resources.”
Click “Create stack”
Wait till the status of the stack is “CREATE_COMPLETE”
Under services search for “Amazon SageMaker”
Click on “Notebook instances”
Look for an instance with name “RekNotebookInstance-” prefix and wait till the status is “InService”
Under Actions, click on “Open Jupyter”
Under the “Files” tab, Open “New” dropdown and click on “Terminal”
In the terminal tab, type
git clone https://github.com/aws-samples/amazon-rekognition-code-samples.git
Open the “rekognition-apis” folder within “amazon-rekognition-code-samples” created under “Files” tab
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.