export
imerit_ango.sdk.SDK.
export(project_id, batches, stage, export_format, export_type, include_key_frames_only, zip_file_path, filters)
Export annotated assets together with labels and metadata. Use assignee, completed_at, updated_at, or batch filters to export specific parts of the dataset.
Parameters
project_id: string
The unique identifier for the project. You can find the project ID in the user interface or retrieve it using the
list_projects
function.
batches: List[string], optional, default None
You may choose to only export assets pertaining to one or more specific batches.
Example:
['0000000aa0a00a0000aaaa0a']
stage: List[string], optional, default None
You may choose to only export assets pertaining to one or more specific stages.
Example:
['Complete']
export_format: string, default "json", {"json", "ndjson"}
Select the format of the export output
Example: "
ndjson"
export_type: string, optional, default None, {"issue"}
You may choose to only export issues by passing
export_type="issue"
.
include_key_frames_only: bool, default False
You may choose to only export key frames for video assets.
zip_file_path: string, optional, default None
If included, the export will be directly downloaded as a .zip file instead of being returned as a Python dictionary. This prevents our server from having to unzip and dict-ify the export, reducing loading times.
Example:
"/Users/lorenzo/Downloads/my_export.zip"
filters: Dict{string:string}
You may filter the export by including a filters dict here.
If you do not include it, by default, the export will not be filtered and it will contain all information.
Here is what you can include in the filters dict (picking true or false as necessary):
Returns:
output: dict
Example
See also
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