At Scale, we pride ourselves in developing superior tooling and implementing forward-looking solutions for problems our customers on the cutting edge of computer vision, including self-driving cars, AR/VR, and drones encounter. For example, our 2D image annotation endpoints now support both per-annotation attributes and label hierarchies, allowing you to get richer labeled data out of Scale.This post will briefly outline the differences between the two. <h2>Per-Annotation Attributes</h2> Defining per-annotation attributes for a task helps you extract additional structured information about individual annotations, beyond what a single selected label can provide. The attribute interface can also adapt dynamically to previously-selected attribute choices. For example, only if workers answer “No” to “Is the car currently parked?” will they be asked “ Which direction is the car heading?” If they answer “yes” to “Is the car currently parked?” the interface will skip the question “Which direction is the car heading?”<img src="https://imagedelivery.net/wLbZE4_NzVVdgHc15St55g/ee91d053-5b42-42f4-32e8-a819c3849300/public" alt="Dashboard selection"> <h2>Label Hierarchies</h2> Nesting labels can also help you extract additional structured information from your data. By default, 2D annotation tasks sent to Scale have a limit of 7 flat labels to reduce the cognitive load on our human labelers and keep their accuracy high. But using subchoices, a worker can, for example, first categorize an object as pedestrian or vehicle, and based on that choice select the specific type of pedestrian or vehicle.<img src="https://imagedelivery.net/wLbZE4_NzVVdgHc15St55g/2a97419c-f9e2-492b-c46d-34c0e8528a00/public" alt="Dashboard selection"> Ready to get started? Take a look at our <a href="https://docs.scale.ai/#annotation-attributes" rel="noopener noreferrer" target="_blank">Annotation Attributes</a> documentation for how to include attributes in your tasks, and for how to use attribute conditions to dynamically request specific attributes. Or see our <a href="https://docs.scale.ai/#nested-annotation-labels" rel="noopener noreferrer" target="_blank">Nested Labels documentation</a> to learn how to specify large lists of labels on annotation tasks.

At Scale, we pride ourselves in developing superior tooling and implementing forward-looking solutions for problems our customers.