Main concepts
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Segments.ai is built around the concept of datasets. A dataset contains a collection of samples.
When you create a dataset, you have to choose the sample and label type. For example, images with segmentation labels, or 3D point clouds with cuboid labels.
A sample is a data point you want to label, like an image, 3D point cloud, or a . The different sample types are defined in Sample formats.
When you label a sample and press the save button, you've created a label for that sample. Labels also come in different types (segmentation labels, vector labels, cuboid labels, ...), with the available options determined by the sample type. The different label types are specified in Label formats.
A label is linked to a sample in relation to a label set. When you label a sample and press the save button, the label is saved in the default ground-truth label set.
You can optionally create additional label sets to .
A release is a snapshot of a dataset at a specific point in time. Create a new release if you want to .