Segments.ai

Segments.ai is a state-of-the-art data labeling platform engineered to handle the complexities of multi-sensor data, making it an indispensable tool for teams in the robotics and autonomous vehicle (AV) industries. The platform is built to deliver consistent, accurate, and high-quality annotations across various data types, including 2D images and 3D point clouds. By unifying the labeling process for multiple sensors, Segments.ai significantly reduces the time spent on quality checks and manual corrections, allowing engineering teams to focus on model development.

The platform's core philosophy is to fuse information from different sensors, such as cameras and LiDAR, providing labelers with a comprehensive context. This synchronized view improves annotation quality and consistency, especially for dynamic scenes. With powerful automation and ML-assisted features, Segments.ai transforms a traditionally tedious process into an efficient, scalable workflow, supporting projects from the initial proof-of-concept stage to full-scale production.

How to use Segments.ai

Using Segments.ai is designed to be an intuitive and seamless experience. The typical workflow is as follows:

1. Setup and Data Upload: Get started quickly with a 14-day free trial. Upload your data, including unlimited-size point clouds and high-resolution images, directly to the platform or integrate with your cloud storage buckets.
2. Configure Your Project: Define your taxonomy and labeling instructions. The platform provides guides and templates to ensure clarity and consistency for your labeling team.
3. Label with Smart Tools: Use the unified interface to view and annotate 2D and 3D data simultaneously. Leverage ML-powered tools like Superpixel 2.0 for image segmentation, auto-segmentation, and one-click 3D-to-2D label projection. For sequences, use automated object tracking and real-time interpolation.
4. Quality Assurance: Utilize built-in QA workflows and issue tracking to review annotations, provide feedback, and ensure the highest data quality.
5. Integrate and Export: Use the powerful Python SDK and API to integrate Segments.ai into your existing MLOps pipeline for active learning and model-assisted labeling. Export your finished annotations in formats compatible with popular frameworks like PyTorch, TensorFlow, and Hugging Face.
6. Scale Your Team: Easily onboard your in-house labeling team or outsource the work to trusted labeling agencies partnered with Segments.ai.

Core Features of Segments.ai

• Multi-Sensor Fusion: Label across multiple sensors (e.g., LiDAR and cameras) at the same time with synchronized views and consistent track IDs.
• Advanced 3D Point Cloud Labeling: Annotate unlimited-size point clouds with cuboids in a few clicks. Features include Merged Point Cloud mode for stationary objects and Batch Mode for dynamic objects.
• ML-Powered 2D Annotation: Accelerate image labeling with tools like Superpixel 2.0, which uses ML to recognize shapes for faster, more accurate segmentation, as well as hover-and-click and pre-labeling models.
• Automated Sequence Labeling: Effortlessly label moving objects with ML-powered object tracking and real-time interpolation, which propagates adjustments across frames.
• One-Click Projection: Project a single 3D cuboid label to all corresponding 2D images where the object appears, saving significant time and effort.
• Developer-First Integration: A robust Python SDK, API, and webhooks allow for deep integration into custom MLOps and active learning pipelines.
• Scalable Workforce Management: Onboard and manage your own team or connect with professional labeling service partners directly through the platform.

Use Cases for Segments.ai

Segments.ai is ideal for any project requiring high-quality labeled data for computer vision, particularly:

• Autonomous Driving: Training perception models for self-driving cars by labeling LiDAR point clouds and camera imagery for object detection, tracking, and semantic segmentation.
• Robotics: Developing navigation and interaction models for robots in logistics, manufacturing, or exploration by annotating sensor data from their environment.
• Academic Research: Providing students and researchers with a powerful, free platform to create high-quality datasets for novel computer vision research.
• Geospatial Analysis: Annotating aerial or satellite imagery combined with 3D data for mapping, agriculture, and environmental monitoring.

Advantages of Segments.ai

The platform offers a clear competitive edge through:

• Enhanced Efficiency: ML-assisted tools and automation features drastically reduce manual labeling time.
• Superior Data Quality: The sensor fusion interface ensures high consistency and accuracy across all data modalities.
• Scalability: The platform is designed to support teams and projects of all sizes, from startups to large enterprises.
• Flexibility and Control: Users have full control over their labeling workflows via a user-friendly UI and a powerful API, with the option to outsource when needed.
• Seamless Integration: Easily connects with existing ML stacks and popular frameworks, streamlining the entire data pipeline.

Pricing and Plans

Segments.ai offers a flexible pricing structure to suit different needs:

• Academic License: 100% free for non-commercial academic research, used by over 130 universities.
• Core Plan: Starts at $9,600 per year. Ideal for companies building their first datasets with separate sensor data. Includes 3,600 hours/year of labeling usage, unlimited seats, and ML-powered tools.
• Fusion Plan: Custom quote. Designed for advanced setups requiring multi-sensor labeling. Starts at 20,000 hours/year and includes all Core features plus sensor fusion interfaces, webhooks, and priority support.
• Enterprise Plan: Custom quote. A comprehensive solution for large-scale operations needing advanced automation and custom solutions. Includes over 150,000 hours/year, custom interfaces, SSO, and a dedicated solutions engineer.

A 14-day free trial is available to test the platform's capabilities.