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
Label training data faster by leveraging your model. Upload model predictions for new data and correct the predictions in the labeling interface.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 )
Collaborate with your team or onboard an external workforce. Our management tools make it easy to build 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, point clouds, and text on Segments.ai
Train a model and keep it on your side. Only upload model predictions