What is Segments.ai?
Segments.ai is a data labeling platform designed for computer vision teams working on robotics, autonomous vehicles, and related fields. It supports multi-sensor labeling, allowing users to annotate 2D images and 3D point clouds simultaneously within a single interface. This approach ensures consistency across modalities and reduces time spent on quality checks and corrections.
The platform offers a range of AI-powered tools including superpixel segmentation, auto-segmentation, hover-and-click labeling, and model-assisted pre-labeling. It provides features for dynamic object tracking, batch mode for labeling moving objects, and merged point cloud mode for stationary objects. Segments.ai integrates with popular machine learning frameworks like PyTorch, TensorFlow, and Hugging Face, and offers a Python SDK for workflow automation.
The platform offers a range of AI-powered tools including superpixel segmentation, auto-segmentation, hover-and-click labeling, and model-assisted pre-labeling. It provides features for dynamic object tracking, batch mode for labeling moving objects, and merged point cloud mode for stationary objects. Segments.ai integrates with popular machine learning frameworks like PyTorch, TensorFlow, and Hugging Face, and offers a Python SDK for workflow automation.
Features
- Multi-Sensor Labeling: Label 2D images and 3D point clouds simultaneously in a single interface
- AI-Assisted Labeling Tools: Includes superpixel 2.0, auto-segment, hover-and-click, and pre-labels for faster annotation
- 3D Point Cloud Labeling: Supports segmentation, cuboids, keypoints, polygons, and polylines with batch mode and merged point cloud mode
- 2D Image Labeling: Supports segmentation, bounding boxes, polygons, polylines, and keypoints with ML-assisted tools
- Model-Assisted Labeling: Generate pre-labels from your own models or public models and verify/correct them
- Python SDK & API: Integrate with existing machine learning workflows and automate labeling pipelines
- Cloud Bucket Integrations: Connect directly to cloud storage for seamless data management
- Export to Popular ML Frameworks: Direct export to PyTorch, TensorFlow, and Hugging Face
Use Cases
- Annotating 3D point clouds and 2D images for autonomous vehicle perception systems
- Labeling multi-sensor data for robotics applications (delivery, off-road, maritime)
- Creating high-quality training datasets for computer vision models
- Accelerating data labeling workflows with AI-assisted tools
- Outsourcing data labeling with quality control via the platform's labeling services
FAQs
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What types of data can I label on Segments.ai?
Segments.ai supports 2D images (segmentation, bounding boxes, polygons, polylines, keypoints) and 3D point clouds (segmentation, cuboids, keypoints, polygons, polylines) with multi-sensor labeling capabilities. -
Does Segments.ai offer a free trial?
Yes, a 14-day free trial is available to test the platform. -
Can I integrate Segments.ai with my existing ML workflow?
Yes, Segments.ai provides a Python SDK and API for integration, and supports export to popular ML frameworks like PyTorch, TensorFlow, and Hugging Face. -
What pricing plans are available?
Segments.ai offers Core ($9,600/year for up to 3,600 hours of labeling usage), Fusion (custom quote for multi-sensor labeling), and Enterprise (custom quote for advanced automation). Free academic licenses are available for students and researchers.
