Label a Computer Vision Dataset with AWS Rekognition Custom Labels

AWS Rekognition is Amazon's prominent computer vision tool, designed to facilitate the labeling, training, and deployment of vision models, with a particular focus on custom datasets through AWS Rekognition Custom Labels. This guide outlines a step-by-step process for labeling a computer vision dataset using AWS Rekognition Custom Labels, starting with the creation of an S3 bucket to store data and moving on to importing and labeling an object detection dataset, specifically for a solar panel detection model. Users are guided through creating a project in AWS Rekognition, connecting data from the S3 bucket, and using various utilities for image annotation, such as drawing bounding boxes and adjusting image settings. Once the images are labeled, they can be used to train a model, with additional resources available for further training and model deployment through AWS Rekognition and Roboflow's supervision package, which offers tools for filtering predictions and drawing bounding boxes.