These examples provide quick walkthroughs to get you up and running with the labeling job workflow for Amazon SageMaker Ground Truth.
- Bring your own model for sagemaker labeling workflows with active learning is an end-to-end example that shows how to bring your custom training, inference logic and active learning to the Amazon SageMaker ecosystem.
- From Unlabeled Data to a Deployed Machine Learning Model: A SageMaker Ground Truth Demonstration for Image Classification is an end-to-end example that starts with an unlabeled dataset, labels it using the Ground Truth API, analyzes the results, trains an image classification neural net using the annotated dataset, and finally uses the trained model to perform batch and online inference.
- Ground Truth Object Detection Tutorial is a similar end-to-end example but for an object detection task.
- Basic Data Analysis of an Image Classification Output Manifest presents charts to visualize the number of annotations for each class, differentiating between human annotations and automatic labels (if your job used auto-labeling). It also displays sample images in each class, and creates a pdf which concisely displays the full results.
- Training a Machine Learning Model Using an Output Manifest introduces the concept of an "augmented manifest" and demonstrates that the output file of a labeling job can be immediately used as the input file to train a SageMaker machine learning model.
- Annotation Consolidation demonstrates Amazon SageMaker Ground Truth annotation consolidation techniques for image classification for a completed labeling job.
- Ground Truth Conversion Scripts provides a conversion script for the output of Ground Truth semantic segmentation manifest to Common Objects in Context (COCO) format
- 3D Point Cloud Demo demonstrates the Amazon SageMaker Ground Truth's annotation workflow for 3D point cloud data types.
- 3D Point Cloud Input Data Processing demonstrates how you can pre-process your 3D point cloud input data to create an object tracking job labeling job.
- Labeling Adjustment Job Adaptation is a utility script to help you remove individual unnecessary labels from manifest files so that you can successfully launch label adjustment jobs with SageMaker Ground Truth.