nucleus.dataset_item#

DatasetItem

A dataset item is an image or pointcloud that has associated metadata.

DatasetItemType

Generic enumeration.
class nucleus.dataset_item.DatasetItem#

A dataset item is an image or pointcloud that has associated metadata.

Note: for 3D data, please include a CameraParams object under a key named “camera_params” within the metadata dictionary. This will allow for projecting 3D annotations to any image within a scene.

Parameters:

  • image_location (Optional[str]) – Required if pointcloud_location is not present: The location containing the image for the given row of data. This can be a local path, or a remote URL. Remote formats supported include any URL (http:// or https://) or URIs for AWS S3, Azure, or GCS (i.e. s3://, gcs://).

  • pointcloud_location (Optional[str]) – Required if image_location is not present: The remote URL containing the pointcloud JSON. Remote formats supported include any URL (http:// or https://) or URIs for AWS S3, Azure, or GCS (i.e. s3://, gcs://).

  • reference_id (Optional[str]) – A user-specified identifier to reference the item.

  • metadata (Optional[dict]) –

    Extra information about the particular dataset item. ints, floats, string values will be made searchable in the query bar by the key in this dict. For example, {"animal": "dog"} will become searchable via metadata.animal = "dog".

    Categorical data can be passed as a string and will be treated categorically by Nucleus if there are less than 250 unique values in the dataset. This means histograms of values in the “Insights” section and autocomplete within the query bar.

    Numerical metadata will generate histograms in the “Insights” section, allow for sorting the results of any query, and can be used with the modulo operator For example: metadata.frame_number % 5 = 0

    All other types of metadata will be visible from the dataset item detail view.

    It is important that string and numerical metadata fields are consistent - if a metadata field has a string value, then all metadata fields with the same key should also have string values, and vice versa for numerical metadata. If conflicting types are found, Nucleus will return an error during upload!

    The recommended way of adding or updating existing metadata is to re-run the ingestion (dataset.append) with update=True, which will replace any existing metadata with whatever your new ingestion run uses. This will delete any metadata keys that are not present in the new ingestion run. We have a cache based on image_location that will skip the need for a re-upload of the images, so your second ingestion will be faster than your first.

    For 3D (sensor fusion) data, it is highly recommended to include camera intrinsics the metadata of your camera image items. Nucleus requires these intrinsics to create visualizations such as cuboid projections. Refer to our guide to uploading 3D data for more info.

    Coordinate metadata may be provided to enable the Map Chart in the Nucleus Dataset charts page. These values can be specified as { “lat”: 52.5, “lon”: 13.3, … }.

    Context Attachments may be provided to display the attachments side by side with the dataset item in the Detail View by specifying { “context_attachments”: [ { “attachment”: ‘https://example.com/1’ }, { “attachment”: ‘https://example.com/2’ }, … ] }.

classmethod from_json(payload)#

Instantiates dataset item object from schematized JSON dict payload.

Parameters:

payload (dict) –

to_json()#

Serializes dataset item object to schematized JSON string.

Return type:

str

to_payload(is_scene=False)#

Serializes dataset item object to schematized JSON dict.

Return type:

dict

class nucleus.dataset_item.DatasetItemType#

Generic enumeration.

Derive from this class to define new enumerations.

name()#

The name of the Enum member.

value()#

The value of the Enum member.