Rilka Li

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.

Per-Annotation Attributes & Labelling for Image Annotations

Metadata to Enrich Image Annotations

You can now be a part of a team on Scale! Until recently, only the original creator of a task could access its history, visually inspect responses, and provide direct feedback on quality. It was a hurdle to our users getting the fullest possible value out of our platform. That's why we're excited to announce Teams, which will allow multiple users to have access to the same set of tasks.<h2>Inviting team members</h2> To take advantage of Teams, head over to “Your Team” in your settings menu. As a team administrator, you can invite new team members, manage existing teammates, and update your team name and payment information.<h2>Shared task history</h2> All members in a team will have access to the team's full Task History on the Scale dashboard. Team members can also quickly access team API keys and create new tasks as part of the team.<img src="https://cdn.builder.io/api/v1/image/assets%2Fe0438815ba51486bbb6a202747122d4b%2F84b4897a723f43fb97a56b46f2b51335" alt="Scale's Dashboard"> <h2>Quality assurance audit</h2> All team members have access to our Quality Assurance tool, where you can grab a random sample of completed tasks (filterable by task type, completion date, and more) and audit task responses using the same interface that our workers use to complete tasks.<img src="https://cdn.builder.io/api/v1/image/assets%2Fe0438815ba51486bbb6a202747122d4b%2Fd04705d0f82d49ca9a220a15ee97866d" alt="Scale's Quality Assurance"> We hope that this improves your Scale experience! If you have questions or other feedback, <a href="https://twitter.com/scale_ai" rel="noopener noreferrer" target="_blank">we'd love to hear from you</a>.

Rilka Li

Metadata to Enrich Image Annotations

Introducing Teams