As of January 1, 2020 this library no longer supports Python 2 on the latest released version.
Library versions released prior to that date will continue to be available. For more information please
visit Python 2 support on Google Cloud.
Source code for google.cloud.automl_v1beta1.types.data_items
# -*- coding: utf-8 -*-
# Copyright 2020 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
import proto # type: ignore
from google.cloud.automl_v1beta1.types import geometry
from google.cloud.automl_v1beta1.types import io
from google.cloud.automl_v1beta1.types import text_segment as gca_text_segment
from google.protobuf import struct_pb2 # type: ignore
__protobuf__ = proto.module(
package="google.cloud.automl.v1beta1",
manifest={
"Image",
"TextSnippet",
"DocumentDimensions",
"Document",
"Row",
"ExamplePayload",
},
)
[docs]class Image(proto.Message):
r"""A representation of an image.
Only images up to 30MB in size are supported.
Attributes:
image_bytes (bytes):
Image content represented as a stream of bytes. Note: As
with all ``bytes`` fields, protobuffers use a pure binary
representation, whereas JSON representations use base64.
input_config (google.cloud.automl_v1beta1.types.InputConfig):
An input config specifying the content of the
image.
thumbnail_uri (str):
Output only. HTTP URI to the thumbnail image.
"""
image_bytes = proto.Field(proto.BYTES, number=1, oneof="data",)
input_config = proto.Field(
proto.MESSAGE, number=6, oneof="data", message=io.InputConfig,
)
thumbnail_uri = proto.Field(proto.STRING, number=4,)
[docs]class TextSnippet(proto.Message):
r"""A representation of a text snippet.
Attributes:
content (str):
Required. The content of the text snippet as
a string. Up to 250000 characters long.
mime_type (str):
Optional. The format of
[content][google.cloud.automl.v1beta1.TextSnippet.content].
Currently the only two allowed values are "text/html" and
"text/plain". If left blank, the format is automatically
determined from the type of the uploaded
[content][google.cloud.automl.v1beta1.TextSnippet.content].
content_uri (str):
Output only. HTTP URI where you can download
the content.
"""
content = proto.Field(proto.STRING, number=1,)
mime_type = proto.Field(proto.STRING, number=2,)
content_uri = proto.Field(proto.STRING, number=4,)
[docs]class DocumentDimensions(proto.Message):
r"""Message that describes dimension of a document.
Attributes:
unit (google.cloud.automl_v1beta1.types.DocumentDimensions.DocumentDimensionUnit):
Unit of the dimension.
width (float):
Width value of the document, works together
with the unit.
height (float):
Height value of the document, works together
with the unit.
"""
[docs] class DocumentDimensionUnit(proto.Enum):
r"""Unit of the document dimension."""
DOCUMENT_DIMENSION_UNIT_UNSPECIFIED = 0
INCH = 1
CENTIMETER = 2
POINT = 3
unit = proto.Field(proto.ENUM, number=1, enum=DocumentDimensionUnit,)
width = proto.Field(proto.FLOAT, number=2,)
height = proto.Field(proto.FLOAT, number=3,)
[docs]class Document(proto.Message):
r"""A structured text document e.g. a PDF.
Attributes:
input_config (google.cloud.automl_v1beta1.types.DocumentInputConfig):
An input config specifying the content of the
document.
document_text (google.cloud.automl_v1beta1.types.TextSnippet):
The plain text version of this document.
layout (Sequence[google.cloud.automl_v1beta1.types.Document.Layout]):
Describes the layout of the document. Sorted by
[page_number][].
document_dimensions (google.cloud.automl_v1beta1.types.DocumentDimensions):
The dimensions of the page in the document.
page_count (int):
Number of pages in the document.
"""
[docs] class Layout(proto.Message):
r"""Describes the layout information of a
[text_segment][google.cloud.automl.v1beta1.Document.Layout.text_segment]
in the document.
Attributes:
text_segment (google.cloud.automl_v1beta1.types.TextSegment):
Text Segment that represents a segment in
[document_text][google.cloud.automl.v1beta1.Document.document_text].
page_number (int):
Page number of the
[text_segment][google.cloud.automl.v1beta1.Document.Layout.text_segment]
in the original document, starts from 1.
bounding_poly (google.cloud.automl_v1beta1.types.BoundingPoly):
The position of the
[text_segment][google.cloud.automl.v1beta1.Document.Layout.text_segment]
in the page. Contains exactly 4
[normalized_vertices][google.cloud.automl.v1beta1.BoundingPoly.normalized_vertices]
and they are connected by edges in the order provided, which
will represent a rectangle parallel to the frame. The
[NormalizedVertex-s][google.cloud.automl.v1beta1.NormalizedVertex]
are relative to the page. Coordinates are based on top-left
as point (0,0).
text_segment_type (google.cloud.automl_v1beta1.types.Document.Layout.TextSegmentType):
The type of the
[text_segment][google.cloud.automl.v1beta1.Document.Layout.text_segment]
in document.
"""
[docs] class TextSegmentType(proto.Enum):
r"""The type of TextSegment in the context of the original
document.
"""
TEXT_SEGMENT_TYPE_UNSPECIFIED = 0
TOKEN = 1
PARAGRAPH = 2
FORM_FIELD = 3
FORM_FIELD_NAME = 4
FORM_FIELD_CONTENTS = 5
TABLE = 6
TABLE_HEADER = 7
TABLE_ROW = 8
TABLE_CELL = 9
text_segment = proto.Field(
proto.MESSAGE, number=1, message=gca_text_segment.TextSegment,
)
page_number = proto.Field(proto.INT32, number=2,)
bounding_poly = proto.Field(
proto.MESSAGE, number=3, message=geometry.BoundingPoly,
)
text_segment_type = proto.Field(
proto.ENUM, number=4, enum="Document.Layout.TextSegmentType",
)
input_config = proto.Field(proto.MESSAGE, number=1, message=io.DocumentInputConfig,)
document_text = proto.Field(proto.MESSAGE, number=2, message="TextSnippet",)
layout = proto.RepeatedField(proto.MESSAGE, number=3, message=Layout,)
document_dimensions = proto.Field(
proto.MESSAGE, number=4, message="DocumentDimensions",
)
page_count = proto.Field(proto.INT32, number=5,)
[docs]class Row(proto.Message):
r"""A representation of a row in a relational table.
Attributes:
column_spec_ids (Sequence[str]):
The resource IDs of the column specs describing the columns
of the row. If set must contain, but possibly in a different
order, all input feature
[column_spec_ids][google.cloud.automl.v1beta1.TablesModelMetadata.input_feature_column_specs]
of the Model this row is being passed to. Note: The below
``values`` field must match order of this field, if this
field is set.
values (Sequence[google.protobuf.struct_pb2.Value]):
Required. The values of the row cells, given in the same
order as the column_spec_ids, or, if not set, then in the
same order as input feature
[column_specs][google.cloud.automl.v1beta1.TablesModelMetadata.input_feature_column_specs]
of the Model this row is being passed to.
"""
column_spec_ids = proto.RepeatedField(proto.STRING, number=2,)
values = proto.RepeatedField(proto.MESSAGE, number=3, message=struct_pb2.Value,)
[docs]class ExamplePayload(proto.Message):
r"""Example data used for training or prediction.
Attributes:
image (google.cloud.automl_v1beta1.types.Image):
Example image.
text_snippet (google.cloud.automl_v1beta1.types.TextSnippet):
Example text.
document (google.cloud.automl_v1beta1.types.Document):
Example document.
row (google.cloud.automl_v1beta1.types.Row):
Example relational table row.
"""
image = proto.Field(proto.MESSAGE, number=1, oneof="payload", message="Image",)
text_snippet = proto.Field(
proto.MESSAGE, number=2, oneof="payload", message="TextSnippet",
)
document = proto.Field(
proto.MESSAGE, number=4, oneof="payload", message="Document",
)
row = proto.Field(proto.MESSAGE, number=3, oneof="payload", message="Row",)
__all__ = tuple(sorted(__protobuf__.manifest))