Train a Computer Vision Model with AWS Rekognition Custom Labels

AWS Rekognition is a computer vision platform by Amazon Web Services that allows users to label data, train, and deploy computer vision models, integrating seamlessly with S3 and accepting data in SageMaker Studio format. The guide outlines a step-by-step process for training a computer vision model using AWS Rekognition Custom Labels, starting with labeling data on the Roboflow platform, importing and preprocessing it, and applying augmentations such as a 90-degree rotation to improve model performance with aerial imagery. It details creating an AWS Rekognition project and dataset, setting up programmatic access via IAM policies, and exporting labeled datasets from Roboflow to AWS Rekognition. Once the data is prepared, users can train the model, evaluate its performance using metrics like F1 score and average precision, and deploy it, with considerations for cost and training time. The guide also mentions Roboflow's open-source package, supervision, which offers utilities for working with computer vision models, including filtering predictions and drawing bounding boxes.