Source code for docarray.dataclasses.setter
from typing import TYPE_CHECKING
import numpy as np
from docarray.dataclasses.enums import DocumentMetadata, ImageType
if TYPE_CHECKING: # pragma: no cover
from docarray import Document
[docs]def image_setter(value) -> 'Document':
from docarray import Document
doc = Document(modality='image')
if isinstance(value, str):
doc.uri = value
doc._metadata[DocumentMetadata.IMAGE_TYPE] = ImageType.URI
doc.load_uri_to_image_tensor()
elif isinstance(value, np.ndarray):
doc.tensor = value
doc._metadata[DocumentMetadata.IMAGE_TYPE] = ImageType.NDARRAY
else:
from PIL.Image import Image
if isinstance(value, Image):
doc.tensor = np.array(value)
doc._metadata[DocumentMetadata.IMAGE_TYPE] = ImageType.PIL
return doc
[docs]def text_setter(value) -> 'Document':
from docarray import Document
return Document(text=value, modality='text')
[docs]def audio_setter(value) -> 'Document':
from docarray import Document
if isinstance(value, np.ndarray):
return Document(
tensor=value, _metadata={DocumentMetadata.AUDIO_TYPE: 'ndarray'}
)
else:
return Document(
uri=value, modality='audio', _metadata={DocumentMetadata.AUDIO_TYPE: 'uri'}
).load_uri_to_audio_tensor()
[docs]def video_setter(value) -> 'Document':
from docarray import Document
if isinstance(value, np.ndarray):
return Document(
tensor=value, _metadata={DocumentMetadata.VIDEO_TYPE: 'ndarray'}
)
else:
return Document(
uri=value, modality='video', _metadata={DocumentMetadata.VIDEO_TYPE: 'uri'}
).load_uri_to_video_tensor()
[docs]def mesh_setter(value) -> 'Document':
from docarray import Document
if isinstance(value, np.ndarray):
return Document(tensor=value, _metadata={DocumentMetadata.MESH_TYPE: 'ndarray'})
else:
return Document(
uri=value, modality='mesh', _metadata={DocumentMetadata.MESH_TYPE: 'uri'}
).load_uri_to_point_cloud_tensor(1000)
[docs]def blob_setter(value) -> 'Document':
from docarray import Document
if isinstance(value, bytes):
return Document(blob=value, _metadata={DocumentMetadata.BLOB_TYPE: 'bytes'})
else:
return Document(
uri=value, _metadata={DocumentMetadata.BLOB_TYPE: 'uri'}
).load_uri_to_blob()
[docs]def json_setter(value) -> 'Document':
from docarray import Document
return Document(modality='json', tags=value)
[docs]def tabular_setter(value) -> 'Document':
from docarray import Document, DocumentArray
return Document(uri=value, chunks=DocumentArray.from_csv(value), modality='tabular')