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_v1.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_v1.types import geometry
from google.cloud.automl_v1.types import io
from google.cloud.automl_v1.types import text_segment as gca_text_segment


__protobuf__ = proto.module(
    package="google.cloud.automl.v1",
    manifest={
        "Image",
        "TextSnippet",
        "DocumentDimensions",
        "Document",
        "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. thumbnail_uri (str): Output only. HTTP URI to the thumbnail image. """ image_bytes = proto.Field(proto.BYTES, number=1, oneof="data",) 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.v1.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.v1.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_v1.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_v1.types.DocumentInputConfig): An input config specifying the content of the document. document_text (google.cloud.automl_v1.types.TextSnippet): The plain text version of this document. layout (Sequence[google.cloud.automl_v1.types.Document.Layout]): Describes the layout of the document. Sorted by [page_number][]. document_dimensions (google.cloud.automl_v1.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.v1.Document.Layout.text_segment] in the document. Attributes: text_segment (google.cloud.automl_v1.types.TextSegment): Text Segment that represents a segment in [document_text][google.cloud.automl.v1p1beta.Document.document_text]. page_number (int): Page number of the [text_segment][google.cloud.automl.v1.Document.Layout.text_segment] in the original document, starts from 1. bounding_poly (google.cloud.automl_v1.types.BoundingPoly): The position of the [text_segment][google.cloud.automl.v1.Document.Layout.text_segment] in the page. Contains exactly 4 [normalized_vertices][google.cloud.automl.v1p1beta.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.v1p1beta.NormalizedVertex] are relative to the page. Coordinates are based on top-left as point (0,0). text_segment_type (google.cloud.automl_v1.types.Document.Layout.TextSegmentType): The type of the [text_segment][google.cloud.automl.v1.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 ExamplePayload(proto.Message): r"""Example data used for training or prediction. Attributes: image (google.cloud.automl_v1.types.Image): Example image. text_snippet (google.cloud.automl_v1.types.TextSnippet): Example text. document (google.cloud.automl_v1.types.Document): Example document. """ 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", )
__all__ = tuple(sorted(__protobuf__.manifest))