Visualization#
If you have an image Document (with possible image data in .uri
/.tensor
), you can directly visualize it via display()
.

To better see the Documentβs nested structure, you can use summary()
.
import numpy as np
from docarray import Document
d0 = Document(id='π²', embedding=np.array([0, 0]))
d1 = Document(id='π¦', embedding=np.array([1, 0]))
d2 = Document(id='π’', embedding=np.array([0, 1]))
d3 = Document(id='π―', embedding=np.array([1, 1]))
d0.chunks.append(d1)
d0.chunks[0].chunks.append(d2)
d0.matches.append(d3)
d0.summary()
<Document ('id', 'embedding', 'chunks', 'matches') at π²>
ββ matches
ββ <Document ('id', 'adjacency', 'embedding') at π―>
ββ chunks
ββ <Document ('id', 'parent_id', 'granularity', 'embedding', 'chunks') at π¦>
ββ chunks
ββ <Document ('id', 'parent_id', 'granularity', 'embedding') at π’>
When using Notebook/Colab, this is auto-rendered.
