Built-in SageMaker AI Algorithms for Computer Vision - Amazon SageMaker AI

Built-in SageMaker AI Algorithms for Computer Vision

SageMaker AI provides image processing algorithms that are used for image classification, object detection, and computer vision.

  • Image Classification - MXNet—uses example data with answers (referred to as a supervised algorithm). Use this algorithm to classify images.

  • Image Classification - TensorFlow—uses pretrained TensorFlow Hub models to fine-tune for specific tasks (referred to as a supervised algorithm). Use this algorithm to classify images.

  • Object Detection - MXNet—detects and classifies objects in images using a single deep neural network. It is a supervised learning algorithm that takes images as input and identifies all instances of objects within the image scene.

  • Object Detection - TensorFlow—detects bounding boxes and object labels in an image. It is a supervised learning algorithm that supports transfer learning with available pretrained TensorFlow models.

  • Semantic Segmentation Algorithm—provides a fine-grained, pixel-level approach to developing computer vision applications.

Algorithm name Channel name Training input mode File type Instance class Parallelizable
Image Classification - MXNet train and validation, (optionally) train_lst, validation_lst, and model File or Pipe recordIO or image files (.jpg or .png) GPU Yes
Image Classification - TensorFlow training and validation File image files (.jpg, .jpeg, or .png) CPU or GPU Yes (only across multiple GPUs on a single instance)
Object Detection train and validation, (optionally) train_annotation, validation_annotation, and model File or Pipe recordIO or image files (.jpg or .png) GPU Yes
Object Detection - TensorFlow training and validation File image files (.jpg, .jpeg, or .png) GPU Yes (only across multiple GPUs on a single instance)
Semantic Segmentation train and validation, train_annotation, validation_annotation, and (optionally) label_map and model File or Pipe Image files GPU (single instance only) No