Segments.ai

2D & 3D data labeling
for robotics and autonomous vehicles

The platform for fast and accurate multi-sensor data annotation.
Label in-house or with an external workforce.

Label all your sensor data
in one place

Intuitive labeling interfaces for images, videos, and 3D point clouds (lidar and RGBD). Obtain segmentation labels, vector labels, and more.

Label sequences of data fast with interpolation and ML assistance

Sensor fusion: visualize and label multiple modalities in the same interface

Consistent object IDs across time and modalities

Label merged 3D point clouds of unlimited size

Image
Point Cloud

Get annotations faster

Our labeling interfaces are set up to label fast and precise. Powerful ML assistance lets you label faster and reduce costs.

Pre-label your data with model-assisted labeling using your own ML models or pre-trained models

Speed up image labeling with our ML-powered Superpixel and Autosegment tools

Maximize efficiency by customizing any hotkey

Label 3D sequences faster with batch mode and merged point cloud view

Set up automated workflows

Integrate data labeling into your existing ML pipelines and workflows using our simple yet powerful Python SDK.

Upload data, download labels, and manage datasets programmatically

Automatically trigger actions using webhooks

Connect your cloud provider (AWS, Google Cloud, Azure)

Export to popular ML frameworks (PyTorch, TensorFlow, Hugging Face 🤗)


    from segments import SegmentsClient

    client = SegmentsClient("api_key")

    dataset = client.add_dataset(
      "dataset_name", 
      task_type, 
      task_attributes
    )

    sample = client.add_sample(
      "user/dataset_name", 
      "sample_name", 
      attributes
    )