Label sequences of point clouds, and optionally define the ego pose for each frame. Use keyframe interpolation to speed up bounding box labeling.Learn more
To speed up labeling of dynamic objects in point cloud sequences, you can use batch mode. Batch mode displays an object in all frames in a simple interface. That way, you can easily see where adjustments are needed.Learn more
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 )
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
Onboard your own workforce or use one of our workforce partners. Our management tools make it easy to label and review large datasets together.
Onboard an external workforce from our labeling service partners
Implement active learning by using your model predictions to find failure cases and to speed up labeling.
Label images and point clouds on Segments.ai
Train a model and keep it on your side. Only upload model predictions