The idea behind this solution is to allow customers to migrate their Amazon Rekognition face collections to the newest FaceModelVersion available.

The solution is already packaged into an Amazon CloudFormation template. AWS CloudFormation is a service that helps you model and set up your AWS resources so that you can spend less time managing those resources and more time focusing on your applications that run in AWS. You only have to worry about providing your existing data in the correct format.

To configure and deploy the solution we have created a Jupyter Notebook containing all the needed steps. Amazon Sagemaker Studio allows you to access fully managed Jupyter notebooks. If you don't have an existing Studio environment, you can follow the instructions in this guide.

When you have your environment ready, open a new Terminal and type the following command:

git clone https://github.com/DanyStinson/rekognition-collection-reindex.git

In the File Browser you should see an assets folder and a notebook named 0-Data-Preparation.ipynb.

Open the notebook to prepare your face collection dataset, once finished, open 1-ReIndex-Solution.ipynb to deploy and launch the reindex solution.