Image and Video Ground Truth Labeling
Use the Image Labeler and Video Labeler apps to interactively label a collection of images, a video, or a sequence of images to create training data for deep learning. You can label rectangular regions of interest (ROIs) or polylines, pixels for semantic segmentation, polygons for instance segmentation, and scenes for image classification. The apps also include computer vision algorithms to automate the labeling of ground truth data for use with detection and tracking algorithms. They also provide an API and workflow that enables you to import your own algorithms to automate the labeling of ground truth data.
Image Labeler app also provides an interface for a collaborative multi-user team labeling workflow. You can distribute images for labeling between team members. You can also review the labeled images, provide feedback and track progress for all labeling and review tasks.
Categories
- Label Images and Video
Label images and video
- Automate Labeling
Use automation algorithms for ground truth labeling
- Create Team-Based Image Labeling Project
Collaborative image labeling workflow for distributed teams using the Image Labeler app
- Work with Ground Truth Data
Select, merge, and load training data for deep learning
- Ground Truth Data Applications
Applications for labeled and trained image and video ground truth data