Main Purpose
The main purpose of Superb AI is to provide an all-in-one computer vision data training platform. It aims to empower teams and companies worldwide to build, manage, and curate computer vision datasets more efficiently.
Key Features
- Adaptable Automation: Superb AI focuses on adaptable automation, allowing users to streamline and automate various tasks involved in training data for computer vision models.
- Annotation Types: The platform supports multiple annotation types for image data, including Bounding Box, Rotated Box, Polyline, Polygon Segmentation, Keypoint, Image Category, and 2D Cuboid. For video data, it supports annotation types excluding Rotated Box and 2D Cuboid.
- Data Management: Superb AI provides tools for managing and organizing large volumes of training data, ensuring easy access, version control, and collaboration among team members.
- Collaboration and Workflow: The platform offers features that facilitate collaboration and workflow management, allowing teams to work together efficiently and track progress throughout the data training process.
Use Case
- Data Scientists and Engineers: Superb AI is designed for data scientists and engineers who work on computer vision projects and need a comprehensive platform for managing and curating training data.
- ML Engineers: ML engineers can benefit from Superb AI's automation capabilities and data management tools to streamline the process of training computer vision models.
- Product Leaders: Superb AI provides product leaders with a platform to oversee and manage the data training pipeline, ensuring efficient collaboration and faster model development.
- Labelers: Superb AI can be used by labelers who are responsible for annotating and labeling training data for computer vision models.
