In this tutorial, we will show how you can use Amazon A2I directly within your API calls to Amazon Rekognition’s Detect Moderation Labels API. Use the Amazon SageMaker Notebook launched in Lab 1.
To run this lab, you need to complete prerequisite section from Lab 1
On AWS Management Console, under services search for “Amazon SageMaker”, look for an instance with name “RekNotebookInstance-” prefix
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-a2i-sample-jupyter-notebooks.git
Open “amazon-a2i-sample-jupyter-notebooks” folder created under “Files” tab
Navigate to “Amazon-A2I-and-Rekognition-DetectModerationLabels.ipynb” notebook. Click on the notebook
Follow the instructions in the notebook to understand how you can integrate human review with Amazon Rekognition
In order to execute each cell, click on the “Run” button at the top or press “Shift+Enter”
Make sure you use “conda_python3” kernel and execute all cells in order.