Create Lidar Segmentation Annotation

This endpoint creates a lidarsegmentation task. In this task, one of our Scalers views outputs from a series of LIDAR frames, along with optional camera data, and annotates where different objects exist in the 3D space by assigning a class to each LidarPoint.

The required parameters for this task are callback_url, labels, attachments, and attachment_type.

  • The callback_url is the URL which will be POSTed on task completion, and is described in more detail in the callbacks section.
  • The labels array lists the object classes for which semantic information is desired.
    Instance labels are supported, by specifying instance_label: true when defining the label. For example, ['Road', {'choice': 'Pedestrian', 'instance_label': true}].
    Nested labels are also supported for these labels, and may be specified in the same format as noted in our documentation. For example, ['Vehicle', {'choice': 'Pedestrian', 'subchoices': ['Adult', 'Child']}].
  • The attachments will be a list of links to external JSON files, each following the definition of a Frame as specified here.

You should provide additional markdown-enabled instructions via the instruction parameter.

It is strongly recommended for you to flesh out your Markdown instructions with many examples of tasks being done correctly and incorrectly.

If successful, Scale will immediately return the generated task object, of which you should at least store the task_id

Language
Authentication
Basic
base64
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