Explore the platform

Segments.ai makes it easy to manage, label and improve datasets.
Discover the different interfaces and features yourself.

Image segmentation

Cityscapes

The Cityscapes dataset focuses on semantic understanding of urban street scenes.

Image bounding boxes

VOC

The Pascal Visual Object Classes (VOC) challenge is a benchmark in visual object category recognition and detection.

Point cloud segmentation

SemanticKITTI

SemanticKITTI is a dataset of LiDAR sequences for semantic scene understanding.

Point cloud cuboids

nuScenes

The nuScenes dataset is a large-scale autonomous driving dataset with 3D cuboid annotations.

Why ML teams choose Segments.ai


    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
    )
                  
TensorFlow, AWS, Hugging Face, and PyTorch logo

Easy to set up and integrate

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

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

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

Manage your workforce

Collaborate with your team or onboard an external workforce. Our management tools make it easy to build and review large datasets together.

Give collaborators access to specific datasets and choose their permissions

Onboard an external workforce from our labeling service partners

Set up a reviewing step and communicate with labelers via issues

Track labeling performance through metrics and custom dashboards.

Model predictions vs. corrected labels
Model predictions vs. corrected labels

Set up advanced workflows

Implement active learning by using your model predictions to find failure cases and to speed up labeling.

1

Label images, point clouds, and text on Segments.ai

2

Train a model and keep it on your side. Only upload model predictions

3

Compare predictions with ground-truth labels and use our search syntax to find failure cases

4

Use model predictions as prelabels to speed up labeling

Start building better datasets today

Try Segments.ai free for 14 days. No credit card required.

Start free trial