Service that performs image detection and annotation for a batch of files.
asyncBatchAnnotate(body, x__xgafv=None)
Run asynchronous image detection and annotation for a list of generic
annotate(body, x__xgafv=None)
Service that performs image detection and annotation for a batch of files.
Now only "application/pdf", "image/tiff" and "image/gif" are supported.
This service will extract at most 5 (customers can specify which 5 in
AnnotateFileRequest.pages) frames (gif) or pages (pdf or tiff) from each
file provided and perform detection and annotation for each image
extracted.
Args:
body: object, The request body. (required)
The object takes the form of:
{ # A list of requests to annotate files using the BatchAnnotateFiles API.
"requests": [ # The list of file annotation requests. Right now we support only one
# AnnotateFileRequest in BatchAnnotateFilesRequest.
{ # A request to annotate one single file, e.g. a PDF, TIFF or GIF file.
"imageContext": { # Image context and/or feature-specific parameters. # Additional context that may accompany the image(s) in the file.
"latLongRect": { # Rectangle determined by min and max `LatLng` pairs. # Not used.
"minLatLng": { # An object representing a latitude/longitude pair. This is expressed as a pair # Min lat/long pair.
# of doubles representing degrees latitude and degrees longitude. Unless
# specified otherwise, this must conform to the
# WGS84
# standard. Values must be within normalized ranges.
"latitude": 3.14, # The latitude in degrees. It must be in the range [-90.0, +90.0].
"longitude": 3.14, # The longitude in degrees. It must be in the range [-180.0, +180.0].
},
"maxLatLng": { # An object representing a latitude/longitude pair. This is expressed as a pair # Max lat/long pair.
# of doubles representing degrees latitude and degrees longitude. Unless
# specified otherwise, this must conform to the
# WGS84
# standard. Values must be within normalized ranges.
"latitude": 3.14, # The latitude in degrees. It must be in the range [-90.0, +90.0].
"longitude": 3.14, # The longitude in degrees. It must be in the range [-180.0, +180.0].
},
},
"languageHints": [ # List of languages to use for TEXT_DETECTION. In most cases, an empty value
# yields the best results since it enables automatic language detection. For
# languages based on the Latin alphabet, setting `language_hints` is not
# needed. In rare cases, when the language of the text in the image is known,
# setting a hint will help get better results (although it will be a
# significant hindrance if the hint is wrong). Text detection returns an
# error if one or more of the specified languages is not one of the
# [supported languages](/vision/docs/languages).
"A String",
],
"productSearchParams": { # Parameters for a product search request. # Parameters for product search.
"productCategories": [ # The list of product categories to search in. Currently, we only consider
# the first category, and either "homegoods-v2", "apparel-v2", or "toys-v2"
# should be specified. The legacy categories "homegoods", "apparel", and
# "toys" are still supported but will be deprecated. For new products, please
# use "homegoods-v2", "apparel-v2", or "toys-v2" for better product search
# accuracy. It is recommended to migrate existing products to these
# categories as well.
"A String",
],
"filter": "A String", # The filtering expression. This can be used to restrict search results based
# on Product labels. We currently support an AND of OR of key-value
# expressions, where each expression within an OR must have the same key. An
# '=' should be used to connect the key and value.
#
# For example, "(color = red OR color = blue) AND brand = Google" is
# acceptable, but "(color = red OR brand = Google)" is not acceptable.
# "color: red" is not acceptable because it uses a ':' instead of an '='.
"productSet": "A String", # The resource name of a ProductSet to be searched for similar images.
#
# Format is:
# `projects/PROJECT_ID/locations/LOC_ID/productSets/PRODUCT_SET_ID`.
"boundingPoly": { # A bounding polygon for the detected image annotation. # The bounding polygon around the area of interest in the image.
# Optional. If it is not specified, system discretion will be applied.
"normalizedVertices": [ # The bounding polygon normalized vertices.
{ # A vertex represents a 2D point in the image.
# NOTE: the normalized vertex coordinates are relative to the original image
# and range from 0 to 1.
"y": 3.14, # Y coordinate.
"x": 3.14, # X coordinate.
},
],
"vertices": [ # The bounding polygon vertices.
{ # A vertex represents a 2D point in the image.
# NOTE: the vertex coordinates are in the same scale as the original image.
"y": 42, # Y coordinate.
"x": 42, # X coordinate.
},
],
},
},
"cropHintsParams": { # Parameters for crop hints annotation request. # Parameters for crop hints annotation request.
"aspectRatios": [ # Aspect ratios in floats, representing the ratio of the width to the height
# of the image. For example, if the desired aspect ratio is 4/3, the
# corresponding float value should be 1.33333. If not specified, the
# best possible crop is returned. The number of provided aspect ratios is
# limited to a maximum of 16; any aspect ratios provided after the 16th are
# ignored.
3.14,
],
},
"webDetectionParams": { # Parameters for web detection request. # Parameters for web detection.
"includeGeoResults": True or False, # Whether to include results derived from the geo information in the image.
},
},
"pages": [ # Pages of the file to perform image annotation.
#
# Pages starts from 1, we assume the first page of the file is page 1.
# At most 5 pages are supported per request. Pages can be negative.
#
# Page 1 means the first page.
# Page 2 means the second page.
# Page -1 means the last page.
# Page -2 means the second to the last page.
#
# If the file is GIF instead of PDF or TIFF, page refers to GIF frames.
#
# If this field is empty, by default the service performs image annotation
# for the first 5 pages of the file.
42,
],
"inputConfig": { # The desired input location and metadata. # Required. Information about the input file.
"mimeType": "A String", # The type of the file. Currently only "application/pdf", "image/tiff" and
# "image/gif" are supported. Wildcards are not supported.
"content": "A String", # File content, represented as a stream of bytes.
# Note: As with all `bytes` fields, protobuffers use a pure binary
# representation, whereas JSON representations use base64.
#
# Currently, this field only works for BatchAnnotateFiles requests. It does
# not work for AsyncBatchAnnotateFiles requests.
"gcsSource": { # The Google Cloud Storage location where the input will be read from. # The Google Cloud Storage location to read the input from.
"uri": "A String", # Google Cloud Storage URI for the input file. This must only be a
# Google Cloud Storage object. Wildcards are not currently supported.
},
},
"features": [ # Required. Requested features.
{ # The type of Google Cloud Vision API detection to perform, and the maximum
# number of results to return for that type. Multiple `Feature` objects can
# be specified in the `features` list.
"model": "A String", # Model to use for the feature.
# Supported values: "builtin/stable" (the default if unset) and
# "builtin/latest".
"type": "A String", # The feature type.
"maxResults": 42, # Maximum number of results of this type. Does not apply to
# `TEXT_DETECTION`, `DOCUMENT_TEXT_DETECTION`, or `CROP_HINTS`.
},
],
},
],
}
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # A list of file annotation responses.
"responses": [ # The list of file annotation responses, each response corresponding to each
# AnnotateFileRequest in BatchAnnotateFilesRequest.
{ # Response to a single file annotation request. A file may contain one or more
# images, which individually have their own responses.
"totalPages": 42, # This field gives the total number of pages in the file.
"responses": [ # Individual responses to images found within the file.
{ # Response to an image annotation request.
"safeSearchAnnotation": { # Set of features pertaining to the image, computed by computer vision # If present, safe-search annotation has completed successfully.
# methods over safe-search verticals (for example, adult, spoof, medical,
# violence).
"medical": "A String", # Likelihood that this is a medical image.
"violence": "A String", # Likelihood that this image contains violent content.
"spoof": "A String", # Spoof likelihood. The likelihood that an modification
# was made to the image's canonical version to make it appear
# funny or offensive.
"adult": "A String", # Represents the adult content likelihood for the image. Adult content may
# contain elements such as nudity, pornographic images or cartoons, or
# sexual activities.
"racy": "A String", # Likelihood that the request image contains racy content. Racy content may
# include (but is not limited to) skimpy or sheer clothing, strategically
# covered nudity, lewd or provocative poses, or close-ups of sensitive
# body areas.
},
"textAnnotations": [ # If present, text (OCR) detection has completed successfully.
{ # Set of detected entity features.
"confidence": 3.14, # **Deprecated. Use `score` instead.**
# The accuracy of the entity detection in an image.
# For example, for an image in which the "Eiffel Tower" entity is detected,
# this field represents the confidence that there is a tower in the query
# image. Range [0, 1].
"description": "A String", # Entity textual description, expressed in its `locale` language.
"locale": "A String", # The language code for the locale in which the entity textual
# `description` is expressed.
"topicality": 3.14, # The relevancy of the ICA (Image Content Annotation) label to the
# image. For example, the relevancy of "tower" is likely higher to an image
# containing the detected "Eiffel Tower" than to an image containing a
# detected distant towering building, even though the confidence that
# there is a tower in each image may be the same. Range [0, 1].
"mid": "A String", # Opaque entity ID. Some IDs may be available in
# [Google Knowledge Graph Search
# API](https://developers.google.com/knowledge-graph/).
"locations": [ # The location information for the detected entity. Multiple
# `LocationInfo` elements can be present because one location may
# indicate the location of the scene in the image, and another location
# may indicate the location of the place where the image was taken.
# Location information is usually present for landmarks.
{ # Detected entity location information.
"latLng": { # An object representing a latitude/longitude pair. This is expressed as a pair # lat/long location coordinates.
# of doubles representing degrees latitude and degrees longitude. Unless
# specified otherwise, this must conform to the
# WGS84
# standard. Values must be within normalized ranges.
"latitude": 3.14, # The latitude in degrees. It must be in the range [-90.0, +90.0].
"longitude": 3.14, # The longitude in degrees. It must be in the range [-180.0, +180.0].
},
},
],
"score": 3.14, # Overall score of the result. Range [0, 1].
"boundingPoly": { # A bounding polygon for the detected image annotation. # Image region to which this entity belongs. Not produced
# for `LABEL_DETECTION` features.
"normalizedVertices": [ # The bounding polygon normalized vertices.
{ # A vertex represents a 2D point in the image.
# NOTE: the normalized vertex coordinates are relative to the original image
# and range from 0 to 1.
"y": 3.14, # Y coordinate.
"x": 3.14, # X coordinate.
},
],
"vertices": [ # The bounding polygon vertices.
{ # A vertex represents a 2D point in the image.
# NOTE: the vertex coordinates are in the same scale as the original image.
"y": 42, # Y coordinate.
"x": 42, # X coordinate.
},
],
},
"properties": [ # Some entities may have optional user-supplied `Property` (name/value)
# fields, such a score or string that qualifies the entity.
{ # A `Property` consists of a user-supplied name/value pair.
"uint64Value": "A String", # Value of numeric properties.
"name": "A String", # Name of the property.
"value": "A String", # Value of the property.
},
],
},
],
"webDetection": { # Relevant information for the image from the Internet. # If present, web detection has completed successfully.
"fullMatchingImages": [ # Fully matching images from the Internet.
# Can include resized copies of the query image.
{ # Metadata for online images.
"url": "A String", # The result image URL.
"score": 3.14, # (Deprecated) Overall relevancy score for the image.
},
],
"pagesWithMatchingImages": [ # Web pages containing the matching images from the Internet.
{ # Metadata for web pages.
"url": "A String", # The result web page URL.
"pageTitle": "A String", # Title for the web page, may contain HTML markups.
"score": 3.14, # (Deprecated) Overall relevancy score for the web page.
"partialMatchingImages": [ # Partial matching images on the page.
# Those images are similar enough to share some key-point features. For
# example an original image will likely have partial matching for its
# crops.
{ # Metadata for online images.
"url": "A String", # The result image URL.
"score": 3.14, # (Deprecated) Overall relevancy score for the image.
},
],
"fullMatchingImages": [ # Fully matching images on the page.
# Can include resized copies of the query image.
{ # Metadata for online images.
"url": "A String", # The result image URL.
"score": 3.14, # (Deprecated) Overall relevancy score for the image.
},
],
},
],
"visuallySimilarImages": [ # The visually similar image results.
{ # Metadata for online images.
"url": "A String", # The result image URL.
"score": 3.14, # (Deprecated) Overall relevancy score for the image.
},
],
"partialMatchingImages": [ # Partial matching images from the Internet.
# Those images are similar enough to share some key-point features. For
# example an original image will likely have partial matching for its crops.
{ # Metadata for online images.
"url": "A String", # The result image URL.
"score": 3.14, # (Deprecated) Overall relevancy score for the image.
},
],
"webEntities": [ # Deduced entities from similar images on the Internet.
{ # Entity deduced from similar images on the Internet.
"entityId": "A String", # Opaque entity ID.
"score": 3.14, # Overall relevancy score for the entity.
# Not normalized and not comparable across different image queries.
"description": "A String", # Canonical description of the entity, in English.
},
],
"bestGuessLabels": [ # The service's best guess as to the topic of the request image.
# Inferred from similar images on the open web.
{ # Label to provide extra metadata for the web detection.
"languageCode": "A String", # The BCP-47 language code for `label`, such as "en-US" or "sr-Latn".
# For more information, see
# http://www.unicode.org/reports/tr35/#Unicode_locale_identifier.
"label": "A String", # Label for extra metadata.
},
],
},
"localizedObjectAnnotations": [ # If present, localized object detection has completed successfully.
# This will be sorted descending by confidence score.
{ # Set of detected objects with bounding boxes.
"languageCode": "A String", # The BCP-47 language code, such as "en-US" or "sr-Latn". For more
# information, see
# http://www.unicode.org/reports/tr35/#Unicode_locale_identifier.
"score": 3.14, # Score of the result. Range [0, 1].
"mid": "A String", # Object ID that should align with EntityAnnotation mid.
"boundingPoly": { # A bounding polygon for the detected image annotation. # Image region to which this object belongs. This must be populated.
"normalizedVertices": [ # The bounding polygon normalized vertices.
{ # A vertex represents a 2D point in the image.
# NOTE: the normalized vertex coordinates are relative to the original image
# and range from 0 to 1.
"y": 3.14, # Y coordinate.
"x": 3.14, # X coordinate.
},
],
"vertices": [ # The bounding polygon vertices.
{ # A vertex represents a 2D point in the image.
# NOTE: the vertex coordinates are in the same scale as the original image.
"y": 42, # Y coordinate.
"x": 42, # X coordinate.
},
],
},
"name": "A String", # Object name, expressed in its `language_code` language.
},
],
"fullTextAnnotation": { # TextAnnotation contains a structured representation of OCR extracted text. # If present, text (OCR) detection or document (OCR) text detection has
# completed successfully.
# This annotation provides the structural hierarchy for the OCR detected
# text.
# The hierarchy of an OCR extracted text structure is like this:
# TextAnnotation -> Page -> Block -> Paragraph -> Word -> Symbol
# Each structural component, starting from Page, may further have their own
# properties. Properties describe detected languages, breaks etc.. Please refer
# to the TextAnnotation.TextProperty message definition below for more
# detail.
"text": "A String", # UTF-8 text detected on the pages.
"pages": [ # List of pages detected by OCR.
{ # Detected page from OCR.
"width": 42, # Page width. For PDFs the unit is points. For images (including
# TIFFs) the unit is pixels.
"confidence": 3.14, # Confidence of the OCR results on the page. Range [0, 1].
"property": { # Additional information detected on the structural component. # Additional information detected on the page.
"detectedBreak": { # Detected start or end of a structural component. # Detected start or end of a text segment.
"isPrefix": True or False, # True if break prepends the element.
"type": "A String", # Detected break type.
},
"detectedLanguages": [ # A list of detected languages together with confidence.
{ # Detected language for a structural component.
"languageCode": "A String", # The BCP-47 language code, such as "en-US" or "sr-Latn". For more
# information, see
# http://www.unicode.org/reports/tr35/#Unicode_locale_identifier.
"confidence": 3.14, # Confidence of detected language. Range [0, 1].
},
],
},
"blocks": [ # List of blocks of text, images etc on this page.
{ # Logical element on the page.
"boundingBox": { # A bounding polygon for the detected image annotation. # The bounding box for the block.
# The vertices are in the order of top-left, top-right, bottom-right,
# bottom-left. When a rotation of the bounding box is detected the rotation
# is represented as around the top-left corner as defined when the text is
# read in the 'natural' orientation.
# For example:
#
# * when the text is horizontal it might look like:
#
# 0----1
# | |
# 3----2
#
# * when it's rotated 180 degrees around the top-left corner it becomes:
#
# 2----3
# | |
# 1----0
#
# and the vertex order will still be (0, 1, 2, 3).
"normalizedVertices": [ # The bounding polygon normalized vertices.
{ # A vertex represents a 2D point in the image.
# NOTE: the normalized vertex coordinates are relative to the original image
# and range from 0 to 1.
"y": 3.14, # Y coordinate.
"x": 3.14, # X coordinate.
},
],
"vertices": [ # The bounding polygon vertices.
{ # A vertex represents a 2D point in the image.
# NOTE: the vertex coordinates are in the same scale as the original image.
"y": 42, # Y coordinate.
"x": 42, # X coordinate.
},
],
},
"blockType": "A String", # Detected block type (text, image etc) for this block.
"property": { # Additional information detected on the structural component. # Additional information detected for the block.
"detectedBreak": { # Detected start or end of a structural component. # Detected start or end of a text segment.
"isPrefix": True or False, # True if break prepends the element.
"type": "A String", # Detected break type.
},
"detectedLanguages": [ # A list of detected languages together with confidence.
{ # Detected language for a structural component.
"languageCode": "A String", # The BCP-47 language code, such as "en-US" or "sr-Latn". For more
# information, see
# http://www.unicode.org/reports/tr35/#Unicode_locale_identifier.
"confidence": 3.14, # Confidence of detected language. Range [0, 1].
},
],
},
"confidence": 3.14, # Confidence of the OCR results on the block. Range [0, 1].
"paragraphs": [ # List of paragraphs in this block (if this blocks is of type text).
{ # Structural unit of text representing a number of words in certain order.
"boundingBox": { # A bounding polygon for the detected image annotation. # The bounding box for the paragraph.
# The vertices are in the order of top-left, top-right, bottom-right,
# bottom-left. When a rotation of the bounding box is detected the rotation
# is represented as around the top-left corner as defined when the text is
# read in the 'natural' orientation.
# For example:
# * when the text is horizontal it might look like:
# 0----1
# | |
# 3----2
# * when it's rotated 180 degrees around the top-left corner it becomes:
# 2----3
# | |
# 1----0
# and the vertex order will still be (0, 1, 2, 3).
"normalizedVertices": [ # The bounding polygon normalized vertices.
{ # A vertex represents a 2D point in the image.
# NOTE: the normalized vertex coordinates are relative to the original image
# and range from 0 to 1.
"y": 3.14, # Y coordinate.
"x": 3.14, # X coordinate.
},
],
"vertices": [ # The bounding polygon vertices.
{ # A vertex represents a 2D point in the image.
# NOTE: the vertex coordinates are in the same scale as the original image.
"y": 42, # Y coordinate.
"x": 42, # X coordinate.
},
],
},
"confidence": 3.14, # Confidence of the OCR results for the paragraph. Range [0, 1].
"property": { # Additional information detected on the structural component. # Additional information detected for the paragraph.
"detectedBreak": { # Detected start or end of a structural component. # Detected start or end of a text segment.
"isPrefix": True or False, # True if break prepends the element.
"type": "A String", # Detected break type.
},
"detectedLanguages": [ # A list of detected languages together with confidence.
{ # Detected language for a structural component.
"languageCode": "A String", # The BCP-47 language code, such as "en-US" or "sr-Latn". For more
# information, see
# http://www.unicode.org/reports/tr35/#Unicode_locale_identifier.
"confidence": 3.14, # Confidence of detected language. Range [0, 1].
},
],
},
"words": [ # List of words in this paragraph.
{ # A word representation.
"symbols": [ # List of symbols in the word.
# The order of the symbols follows the natural reading order.
{ # A single symbol representation.
"boundingBox": { # A bounding polygon for the detected image annotation. # The bounding box for the symbol.
# The vertices are in the order of top-left, top-right, bottom-right,
# bottom-left. When a rotation of the bounding box is detected the rotation
# is represented as around the top-left corner as defined when the text is
# read in the 'natural' orientation.
# For example:
# * when the text is horizontal it might look like:
# 0----1
# | |
# 3----2
# * when it's rotated 180 degrees around the top-left corner it becomes:
# 2----3
# | |
# 1----0
# and the vertice order will still be (0, 1, 2, 3).
"normalizedVertices": [ # The bounding polygon normalized vertices.
{ # A vertex represents a 2D point in the image.
# NOTE: the normalized vertex coordinates are relative to the original image
# and range from 0 to 1.
"y": 3.14, # Y coordinate.
"x": 3.14, # X coordinate.
},
],
"vertices": [ # The bounding polygon vertices.
{ # A vertex represents a 2D point in the image.
# NOTE: the vertex coordinates are in the same scale as the original image.
"y": 42, # Y coordinate.
"x": 42, # X coordinate.
},
],
},
"text": "A String", # The actual UTF-8 representation of the symbol.
"confidence": 3.14, # Confidence of the OCR results for the symbol. Range [0, 1].
"property": { # Additional information detected on the structural component. # Additional information detected for the symbol.
"detectedBreak": { # Detected start or end of a structural component. # Detected start or end of a text segment.
"isPrefix": True or False, # True if break prepends the element.
"type": "A String", # Detected break type.
},
"detectedLanguages": [ # A list of detected languages together with confidence.
{ # Detected language for a structural component.
"languageCode": "A String", # The BCP-47 language code, such as "en-US" or "sr-Latn". For more
# information, see
# http://www.unicode.org/reports/tr35/#Unicode_locale_identifier.
"confidence": 3.14, # Confidence of detected language. Range [0, 1].
},
],
},
},
],
"boundingBox": { # A bounding polygon for the detected image annotation. # The bounding box for the word.
# The vertices are in the order of top-left, top-right, bottom-right,
# bottom-left. When a rotation of the bounding box is detected the rotation
# is represented as around the top-left corner as defined when the text is
# read in the 'natural' orientation.
# For example:
# * when the text is horizontal it might look like:
# 0----1
# | |
# 3----2
# * when it's rotated 180 degrees around the top-left corner it becomes:
# 2----3
# | |
# 1----0
# and the vertex order will still be (0, 1, 2, 3).
"normalizedVertices": [ # The bounding polygon normalized vertices.
{ # A vertex represents a 2D point in the image.
# NOTE: the normalized vertex coordinates are relative to the original image
# and range from 0 to 1.
"y": 3.14, # Y coordinate.
"x": 3.14, # X coordinate.
},
],
"vertices": [ # The bounding polygon vertices.
{ # A vertex represents a 2D point in the image.
# NOTE: the vertex coordinates are in the same scale as the original image.
"y": 42, # Y coordinate.
"x": 42, # X coordinate.
},
],
},
"confidence": 3.14, # Confidence of the OCR results for the word. Range [0, 1].
"property": { # Additional information detected on the structural component. # Additional information detected for the word.
"detectedBreak": { # Detected start or end of a structural component. # Detected start or end of a text segment.
"isPrefix": True or False, # True if break prepends the element.
"type": "A String", # Detected break type.
},
"detectedLanguages": [ # A list of detected languages together with confidence.
{ # Detected language for a structural component.
"languageCode": "A String", # The BCP-47 language code, such as "en-US" or "sr-Latn". For more
# information, see
# http://www.unicode.org/reports/tr35/#Unicode_locale_identifier.
"confidence": 3.14, # Confidence of detected language. Range [0, 1].
},
],
},
},
],
},
],
},
],
"height": 42, # Page height. For PDFs the unit is points. For images (including
# TIFFs) the unit is pixels.
},
],
},
"labelAnnotations": [ # If present, label detection has completed successfully.
{ # Set of detected entity features.
"confidence": 3.14, # **Deprecated. Use `score` instead.**
# The accuracy of the entity detection in an image.
# For example, for an image in which the "Eiffel Tower" entity is detected,
# this field represents the confidence that there is a tower in the query
# image. Range [0, 1].
"description": "A String", # Entity textual description, expressed in its `locale` language.
"locale": "A String", # The language code for the locale in which the entity textual
# `description` is expressed.
"topicality": 3.14, # The relevancy of the ICA (Image Content Annotation) label to the
# image. For example, the relevancy of "tower" is likely higher to an image
# containing the detected "Eiffel Tower" than to an image containing a
# detected distant towering building, even though the confidence that
# there is a tower in each image may be the same. Range [0, 1].
"mid": "A String", # Opaque entity ID. Some IDs may be available in
# [Google Knowledge Graph Search
# API](https://developers.google.com/knowledge-graph/).
"locations": [ # The location information for the detected entity. Multiple
# `LocationInfo` elements can be present because one location may
# indicate the location of the scene in the image, and another location
# may indicate the location of the place where the image was taken.
# Location information is usually present for landmarks.
{ # Detected entity location information.
"latLng": { # An object representing a latitude/longitude pair. This is expressed as a pair # lat/long location coordinates.
# of doubles representing degrees latitude and degrees longitude. Unless
# specified otherwise, this must conform to the
# WGS84
# standard. Values must be within normalized ranges.
"latitude": 3.14, # The latitude in degrees. It must be in the range [-90.0, +90.0].
"longitude": 3.14, # The longitude in degrees. It must be in the range [-180.0, +180.0].
},
},
],
"score": 3.14, # Overall score of the result. Range [0, 1].
"boundingPoly": { # A bounding polygon for the detected image annotation. # Image region to which this entity belongs. Not produced
# for `LABEL_DETECTION` features.
"normalizedVertices": [ # The bounding polygon normalized vertices.
{ # A vertex represents a 2D point in the image.
# NOTE: the normalized vertex coordinates are relative to the original image
# and range from 0 to 1.
"y": 3.14, # Y coordinate.
"x": 3.14, # X coordinate.
},
],
"vertices": [ # The bounding polygon vertices.
{ # A vertex represents a 2D point in the image.
# NOTE: the vertex coordinates are in the same scale as the original image.
"y": 42, # Y coordinate.
"x": 42, # X coordinate.
},
],
},
"properties": [ # Some entities may have optional user-supplied `Property` (name/value)
# fields, such a score or string that qualifies the entity.
{ # A `Property` consists of a user-supplied name/value pair.
"uint64Value": "A String", # Value of numeric properties.
"name": "A String", # Name of the property.
"value": "A String", # Value of the property.
},
],
},
],
"imagePropertiesAnnotation": { # Stores image properties, such as dominant colors. # If present, image properties were extracted successfully.
"dominantColors": { # Set of dominant colors and their corresponding scores. # If present, dominant colors completed successfully.
"colors": [ # RGB color values with their score and pixel fraction.
{ # Color information consists of RGB channels, score, and the fraction of
# the image that the color occupies in the image.
"color": { # Represents a color in the RGBA color space. This representation is designed # RGB components of the color.
# for simplicity of conversion to/from color representations in various
# languages over compactness; for example, the fields of this representation
# can be trivially provided to the constructor of "java.awt.Color" in Java; it
# can also be trivially provided to UIColor's "+colorWithRed:green:blue:alpha"
# method in iOS; and, with just a little work, it can be easily formatted into
# a CSS "rgba()" string in JavaScript, as well.
#
# Note: this proto does not carry information about the absolute color space
# that should be used to interpret the RGB value (e.g. sRGB, Adobe RGB,
# DCI-P3, BT.2020, etc.). By default, applications SHOULD assume the sRGB color
# space.
#
# Example (Java):
#
# import com.google.type.Color;
#
# // ...
# public static java.awt.Color fromProto(Color protocolor) {
# float alpha = protocolor.hasAlpha()
# ? protocolor.getAlpha().getValue()
# : 1.0;
#
# return new java.awt.Color(
# protocolor.getRed(),
# protocolor.getGreen(),
# protocolor.getBlue(),
# alpha);
# }
#
# public static Color toProto(java.awt.Color color) {
# float red = (float) color.getRed();
# float green = (float) color.getGreen();
# float blue = (float) color.getBlue();
# float denominator = 255.0;
# Color.Builder resultBuilder =
# Color
# .newBuilder()
# .setRed(red / denominator)
# .setGreen(green / denominator)
# .setBlue(blue / denominator);
# int alpha = color.getAlpha();
# if (alpha != 255) {
# result.setAlpha(
# FloatValue
# .newBuilder()
# .setValue(((float) alpha) / denominator)
# .build());
# }
# return resultBuilder.build();
# }
# // ...
#
# Example (iOS / Obj-C):
#
# // ...
# static UIColor* fromProto(Color* protocolor) {
# float red = [protocolor red];
# float green = [protocolor green];
# float blue = [protocolor blue];
# FloatValue* alpha_wrapper = [protocolor alpha];
# float alpha = 1.0;
# if (alpha_wrapper != nil) {
# alpha = [alpha_wrapper value];
# }
# return [UIColor colorWithRed:red green:green blue:blue alpha:alpha];
# }
#
# static Color* toProto(UIColor* color) {
# CGFloat red, green, blue, alpha;
# if (![color getRed:&red green:&green blue:&blue alpha:&alpha]) {
# return nil;
# }
# Color* result = [[Color alloc] init];
# [result setRed:red];
# [result setGreen:green];
# [result setBlue:blue];
# if (alpha <= 0.9999) {
# [result setAlpha:floatWrapperWithValue(alpha)];
# }
# [result autorelease];
# return result;
# }
# // ...
#
# Example (JavaScript):
#
# // ...
#
# var protoToCssColor = function(rgb_color) {
# var redFrac = rgb_color.red || 0.0;
# var greenFrac = rgb_color.green || 0.0;
# var blueFrac = rgb_color.blue || 0.0;
# var red = Math.floor(redFrac * 255);
# var green = Math.floor(greenFrac * 255);
# var blue = Math.floor(blueFrac * 255);
#
# if (!('alpha' in rgb_color)) {
# return rgbToCssColor_(red, green, blue);
# }
#
# var alphaFrac = rgb_color.alpha.value || 0.0;
# var rgbParams = [red, green, blue].join(',');
# return ['rgba(', rgbParams, ',', alphaFrac, ')'].join('');
# };
#
# var rgbToCssColor_ = function(red, green, blue) {
# var rgbNumber = new Number((red << 16) | (green << 8) | blue);
# var hexString = rgbNumber.toString(16);
# var missingZeros = 6 - hexString.length;
# var resultBuilder = ['#'];
# for (var i = 0; i < missingZeros; i++) {
# resultBuilder.push('0');
# }
# resultBuilder.push(hexString);
# return resultBuilder.join('');
# };
#
# // ...
"blue": 3.14, # The amount of blue in the color as a value in the interval [0, 1].
"alpha": 3.14, # The fraction of this color that should be applied to the pixel. That is,
# the final pixel color is defined by the equation:
#
# pixel color = alpha * (this color) + (1.0 - alpha) * (background color)
#
# This means that a value of 1.0 corresponds to a solid color, whereas
# a value of 0.0 corresponds to a completely transparent color. This
# uses a wrapper message rather than a simple float scalar so that it is
# possible to distinguish between a default value and the value being unset.
# If omitted, this color object is to be rendered as a solid color
# (as if the alpha value had been explicitly given with a value of 1.0).
"green": 3.14, # The amount of green in the color as a value in the interval [0, 1].
"red": 3.14, # The amount of red in the color as a value in the interval [0, 1].
},
"pixelFraction": 3.14, # The fraction of pixels the color occupies in the image.
# Value in range [0, 1].
"score": 3.14, # Image-specific score for this color. Value in range [0, 1].
},
],
},
},
"faceAnnotations": [ # If present, face detection has completed successfully.
{ # A face annotation object contains the results of face detection.
"sorrowLikelihood": "A String", # Sorrow likelihood.
"landmarkingConfidence": 3.14, # Face landmarking confidence. Range [0, 1].
"underExposedLikelihood": "A String", # Under-exposed likelihood.
"detectionConfidence": 3.14, # Detection confidence. Range [0, 1].
"joyLikelihood": "A String", # Joy likelihood.
"landmarks": [ # Detected face landmarks.
{ # A face-specific landmark (for example, a face feature).
"position": { # A 3D position in the image, used primarily for Face detection landmarks. # Face landmark position.
# A valid Position must have both x and y coordinates.
# The position coordinates are in the same scale as the original image.
"y": 3.14, # Y coordinate.
"x": 3.14, # X coordinate.
"z": 3.14, # Z coordinate (or depth).
},
"type": "A String", # Face landmark type.
},
],
"surpriseLikelihood": "A String", # Surprise likelihood.
"blurredLikelihood": "A String", # Blurred likelihood.
"tiltAngle": 3.14, # Pitch angle, which indicates the upwards/downwards angle that the face is
# pointing relative to the image's horizontal plane. Range [-180,180].
"angerLikelihood": "A String", # Anger likelihood.
"boundingPoly": { # A bounding polygon for the detected image annotation. # The bounding polygon around the face. The coordinates of the bounding box
# are in the original image's scale.
# The bounding box is computed to "frame" the face in accordance with human
# expectations. It is based on the landmarker results.
# Note that one or more x and/or y coordinates may not be generated in the
# `BoundingPoly` (the polygon will be unbounded) if only a partial face
# appears in the image to be annotated.
"normalizedVertices": [ # The bounding polygon normalized vertices.
{ # A vertex represents a 2D point in the image.
# NOTE: the normalized vertex coordinates are relative to the original image
# and range from 0 to 1.
"y": 3.14, # Y coordinate.
"x": 3.14, # X coordinate.
},
],
"vertices": [ # The bounding polygon vertices.
{ # A vertex represents a 2D point in the image.
# NOTE: the vertex coordinates are in the same scale as the original image.
"y": 42, # Y coordinate.
"x": 42, # X coordinate.
},
],
},
"rollAngle": 3.14, # Roll angle, which indicates the amount of clockwise/anti-clockwise rotation
# of the face relative to the image vertical about the axis perpendicular to
# the face. Range [-180,180].
"panAngle": 3.14, # Yaw angle, which indicates the leftward/rightward angle that the face is
# pointing relative to the vertical plane perpendicular to the image. Range
# [-180,180].
"headwearLikelihood": "A String", # Headwear likelihood.
"fdBoundingPoly": { # A bounding polygon for the detected image annotation. # The `fd_bounding_poly` bounding polygon is tighter than the
# `boundingPoly`, and encloses only the skin part of the face. Typically, it
# is used to eliminate the face from any image analysis that detects the
# "amount of skin" visible in an image. It is not based on the
# landmarker results, only on the initial face detection, hence
# the fd (face detection) prefix.
"normalizedVertices": [ # The bounding polygon normalized vertices.
{ # A vertex represents a 2D point in the image.
# NOTE: the normalized vertex coordinates are relative to the original image
# and range from 0 to 1.
"y": 3.14, # Y coordinate.
"x": 3.14, # X coordinate.
},
],
"vertices": [ # The bounding polygon vertices.
{ # A vertex represents a 2D point in the image.
# NOTE: the vertex coordinates are in the same scale as the original image.
"y": 42, # Y coordinate.
"x": 42, # X coordinate.
},
],
},
},
],
"productSearchResults": { # Results for a product search request. # If present, product search has completed successfully.
"productGroupedResults": [ # List of results grouped by products detected in the query image. Each entry
# corresponds to one bounding polygon in the query image, and contains the
# matching products specific to that region. There may be duplicate product
# matches in the union of all the per-product results.
{ # Information about the products similar to a single product in a query
# image.
"results": [ # List of results, one for each product match.
{ # Information about a product.
"image": "A String", # The resource name of the image from the product that is the closest match
# to the query.
"score": 3.14, # A confidence level on the match, ranging from 0 (no confidence) to
# 1 (full confidence).
"product": { # A Product contains ReferenceImages. # The Product.
"productLabels": [ # Key-value pairs that can be attached to a product. At query time,
# constraints can be specified based on the product_labels.
#
# Note that integer values can be provided as strings, e.g. "1199". Only
# strings with integer values can match a range-based restriction which is
# to be supported soon.
#
# Multiple values can be assigned to the same key. One product may have up to
# 100 product_labels.
{ # A product label represented as a key-value pair.
"value": "A String", # The value of the label attached to the product. Cannot be empty and
# cannot exceed 128 bytes.
"key": "A String", # The key of the label attached to the product. Cannot be empty and cannot
# exceed 128 bytes.
},
],
"displayName": "A String", # The user-provided name for this Product. Must not be empty. Must be at most
# 4096 characters long.
"name": "A String", # The resource name of the product.
#
# Format is:
# `projects/PROJECT_ID/locations/LOC_ID/products/PRODUCT_ID`.
#
# This field is ignored when creating a product.
"productCategory": "A String", # The category for the product identified by the reference image. This should
# be either "homegoods-v2", "apparel-v2", or "toys-v2". The legacy categories
# "homegoods", "apparel", and "toys" are still supported, but these should
# not be used for new products.
#
# This field is immutable.
"description": "A String", # User-provided metadata to be stored with this product. Must be at most 4096
# characters long.
},
},
],
"boundingPoly": { # A bounding polygon for the detected image annotation. # The bounding polygon around the product detected in the query image.
"normalizedVertices": [ # The bounding polygon normalized vertices.
{ # A vertex represents a 2D point in the image.
# NOTE: the normalized vertex coordinates are relative to the original image
# and range from 0 to 1.
"y": 3.14, # Y coordinate.
"x": 3.14, # X coordinate.
},
],
"vertices": [ # The bounding polygon vertices.
{ # A vertex represents a 2D point in the image.
# NOTE: the vertex coordinates are in the same scale as the original image.
"y": 42, # Y coordinate.
"x": 42, # X coordinate.
},
],
},
},
],
"results": [ # List of results, one for each product match.
{ # Information about a product.
"image": "A String", # The resource name of the image from the product that is the closest match
# to the query.
"score": 3.14, # A confidence level on the match, ranging from 0 (no confidence) to
# 1 (full confidence).
"product": { # A Product contains ReferenceImages. # The Product.
"productLabels": [ # Key-value pairs that can be attached to a product. At query time,
# constraints can be specified based on the product_labels.
#
# Note that integer values can be provided as strings, e.g. "1199". Only
# strings with integer values can match a range-based restriction which is
# to be supported soon.
#
# Multiple values can be assigned to the same key. One product may have up to
# 100 product_labels.
{ # A product label represented as a key-value pair.
"value": "A String", # The value of the label attached to the product. Cannot be empty and
# cannot exceed 128 bytes.
"key": "A String", # The key of the label attached to the product. Cannot be empty and cannot
# exceed 128 bytes.
},
],
"displayName": "A String", # The user-provided name for this Product. Must not be empty. Must be at most
# 4096 characters long.
"name": "A String", # The resource name of the product.
#
# Format is:
# `projects/PROJECT_ID/locations/LOC_ID/products/PRODUCT_ID`.
#
# This field is ignored when creating a product.
"productCategory": "A String", # The category for the product identified by the reference image. This should
# be either "homegoods-v2", "apparel-v2", or "toys-v2". The legacy categories
# "homegoods", "apparel", and "toys" are still supported, but these should
# not be used for new products.
#
# This field is immutable.
"description": "A String", # User-provided metadata to be stored with this product. Must be at most 4096
# characters long.
},
},
],
"indexTime": "A String", # Timestamp of the index which provided these results. Products added to the
# product set and products removed from the product set after this time are
# not reflected in the current results.
},
"logoAnnotations": [ # If present, logo detection has completed successfully.
{ # Set of detected entity features.
"confidence": 3.14, # **Deprecated. Use `score` instead.**
# The accuracy of the entity detection in an image.
# For example, for an image in which the "Eiffel Tower" entity is detected,
# this field represents the confidence that there is a tower in the query
# image. Range [0, 1].
"description": "A String", # Entity textual description, expressed in its `locale` language.
"locale": "A String", # The language code for the locale in which the entity textual
# `description` is expressed.
"topicality": 3.14, # The relevancy of the ICA (Image Content Annotation) label to the
# image. For example, the relevancy of "tower" is likely higher to an image
# containing the detected "Eiffel Tower" than to an image containing a
# detected distant towering building, even though the confidence that
# there is a tower in each image may be the same. Range [0, 1].
"mid": "A String", # Opaque entity ID. Some IDs may be available in
# [Google Knowledge Graph Search
# API](https://developers.google.com/knowledge-graph/).
"locations": [ # The location information for the detected entity. Multiple
# `LocationInfo` elements can be present because one location may
# indicate the location of the scene in the image, and another location
# may indicate the location of the place where the image was taken.
# Location information is usually present for landmarks.
{ # Detected entity location information.
"latLng": { # An object representing a latitude/longitude pair. This is expressed as a pair # lat/long location coordinates.
# of doubles representing degrees latitude and degrees longitude. Unless
# specified otherwise, this must conform to the
# WGS84
# standard. Values must be within normalized ranges.
"latitude": 3.14, # The latitude in degrees. It must be in the range [-90.0, +90.0].
"longitude": 3.14, # The longitude in degrees. It must be in the range [-180.0, +180.0].
},
},
],
"score": 3.14, # Overall score of the result. Range [0, 1].
"boundingPoly": { # A bounding polygon for the detected image annotation. # Image region to which this entity belongs. Not produced
# for `LABEL_DETECTION` features.
"normalizedVertices": [ # The bounding polygon normalized vertices.
{ # A vertex represents a 2D point in the image.
# NOTE: the normalized vertex coordinates are relative to the original image
# and range from 0 to 1.
"y": 3.14, # Y coordinate.
"x": 3.14, # X coordinate.
},
],
"vertices": [ # The bounding polygon vertices.
{ # A vertex represents a 2D point in the image.
# NOTE: the vertex coordinates are in the same scale as the original image.
"y": 42, # Y coordinate.
"x": 42, # X coordinate.
},
],
},
"properties": [ # Some entities may have optional user-supplied `Property` (name/value)
# fields, such a score or string that qualifies the entity.
{ # A `Property` consists of a user-supplied name/value pair.
"uint64Value": "A String", # Value of numeric properties.
"name": "A String", # Name of the property.
"value": "A String", # Value of the property.
},
],
},
],
"landmarkAnnotations": [ # If present, landmark detection has completed successfully.
{ # Set of detected entity features.
"confidence": 3.14, # **Deprecated. Use `score` instead.**
# The accuracy of the entity detection in an image.
# For example, for an image in which the "Eiffel Tower" entity is detected,
# this field represents the confidence that there is a tower in the query
# image. Range [0, 1].
"description": "A String", # Entity textual description, expressed in its `locale` language.
"locale": "A String", # The language code for the locale in which the entity textual
# `description` is expressed.
"topicality": 3.14, # The relevancy of the ICA (Image Content Annotation) label to the
# image. For example, the relevancy of "tower" is likely higher to an image
# containing the detected "Eiffel Tower" than to an image containing a
# detected distant towering building, even though the confidence that
# there is a tower in each image may be the same. Range [0, 1].
"mid": "A String", # Opaque entity ID. Some IDs may be available in
# [Google Knowledge Graph Search
# API](https://developers.google.com/knowledge-graph/).
"locations": [ # The location information for the detected entity. Multiple
# `LocationInfo` elements can be present because one location may
# indicate the location of the scene in the image, and another location
# may indicate the location of the place where the image was taken.
# Location information is usually present for landmarks.
{ # Detected entity location information.
"latLng": { # An object representing a latitude/longitude pair. This is expressed as a pair # lat/long location coordinates.
# of doubles representing degrees latitude and degrees longitude. Unless
# specified otherwise, this must conform to the
# WGS84
# standard. Values must be within normalized ranges.
"latitude": 3.14, # The latitude in degrees. It must be in the range [-90.0, +90.0].
"longitude": 3.14, # The longitude in degrees. It must be in the range [-180.0, +180.0].
},
},
],
"score": 3.14, # Overall score of the result. Range [0, 1].
"boundingPoly": { # A bounding polygon for the detected image annotation. # Image region to which this entity belongs. Not produced
# for `LABEL_DETECTION` features.
"normalizedVertices": [ # The bounding polygon normalized vertices.
{ # A vertex represents a 2D point in the image.
# NOTE: the normalized vertex coordinates are relative to the original image
# and range from 0 to 1.
"y": 3.14, # Y coordinate.
"x": 3.14, # X coordinate.
},
],
"vertices": [ # The bounding polygon vertices.
{ # A vertex represents a 2D point in the image.
# NOTE: the vertex coordinates are in the same scale as the original image.
"y": 42, # Y coordinate.
"x": 42, # X coordinate.
},
],
},
"properties": [ # Some entities may have optional user-supplied `Property` (name/value)
# fields, such a score or string that qualifies the entity.
{ # A `Property` consists of a user-supplied name/value pair.
"uint64Value": "A String", # Value of numeric properties.
"name": "A String", # Name of the property.
"value": "A String", # Value of the property.
},
],
},
],
"context": { # If an image was produced from a file (e.g. a PDF), this message gives # If present, contextual information is needed to understand where this image
# comes from.
# information about the source of that image.
"pageNumber": 42, # If the file was a PDF or TIFF, this field gives the page number within
# the file used to produce the image.
"uri": "A String", # The URI of the file used to produce the image.
},
"error": { # The `Status` type defines a logical error model that is suitable for # If set, represents the error message for the operation.
# Note that filled-in image annotations are guaranteed to be
# correct, even when `error` is set.
# different programming environments, including REST APIs and RPC APIs. It is
# used by [gRPC](https://github.com/grpc). Each `Status` message contains
# three pieces of data: error code, error message, and error details.
#
# You can find out more about this error model and how to work with it in the
# [API Design Guide](https://cloud.google.com/apis/design/errors).
"message": "A String", # A developer-facing error message, which should be in English. Any
# user-facing error message should be localized and sent in the
# google.rpc.Status.details field, or localized by the client.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of
# message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
},
"cropHintsAnnotation": { # Set of crop hints that are used to generate new crops when serving images. # If present, crop hints have completed successfully.
"cropHints": [ # Crop hint results.
{ # Single crop hint that is used to generate a new crop when serving an image.
"confidence": 3.14, # Confidence of this being a salient region. Range [0, 1].
"boundingPoly": { # A bounding polygon for the detected image annotation. # The bounding polygon for the crop region. The coordinates of the bounding
# box are in the original image's scale.
"normalizedVertices": [ # The bounding polygon normalized vertices.
{ # A vertex represents a 2D point in the image.
# NOTE: the normalized vertex coordinates are relative to the original image
# and range from 0 to 1.
"y": 3.14, # Y coordinate.
"x": 3.14, # X coordinate.
},
],
"vertices": [ # The bounding polygon vertices.
{ # A vertex represents a 2D point in the image.
# NOTE: the vertex coordinates are in the same scale as the original image.
"y": 42, # Y coordinate.
"x": 42, # X coordinate.
},
],
},
"importanceFraction": 3.14, # Fraction of importance of this salient region with respect to the original
# image.
},
],
},
},
],
"inputConfig": { # The desired input location and metadata. # Information about the file for which this response is generated.
"mimeType": "A String", # The type of the file. Currently only "application/pdf", "image/tiff" and
# "image/gif" are supported. Wildcards are not supported.
"content": "A String", # File content, represented as a stream of bytes.
# Note: As with all `bytes` fields, protobuffers use a pure binary
# representation, whereas JSON representations use base64.
#
# Currently, this field only works for BatchAnnotateFiles requests. It does
# not work for AsyncBatchAnnotateFiles requests.
"gcsSource": { # The Google Cloud Storage location where the input will be read from. # The Google Cloud Storage location to read the input from.
"uri": "A String", # Google Cloud Storage URI for the input file. This must only be a
# Google Cloud Storage object. Wildcards are not currently supported.
},
},
},
],
}
asyncBatchAnnotate(body, x__xgafv=None)
Run asynchronous image detection and annotation for a list of generic
files, such as PDF files, which may contain multiple pages and multiple
images per page. Progress and results can be retrieved through the
`google.longrunning.Operations` interface.
`Operation.metadata` contains `OperationMetadata` (metadata).
`Operation.response` contains `AsyncBatchAnnotateFilesResponse` (results).
Args:
body: object, The request body. (required)
The object takes the form of:
{ # Multiple async file annotation requests are batched into a single service
# call.
"requests": [ # Individual async file annotation requests for this batch.
{ # An offline file annotation request.
"imageContext": { # Image context and/or feature-specific parameters. # Additional context that may accompany the image(s) in the file.
"latLongRect": { # Rectangle determined by min and max `LatLng` pairs. # Not used.
"minLatLng": { # An object representing a latitude/longitude pair. This is expressed as a pair # Min lat/long pair.
# of doubles representing degrees latitude and degrees longitude. Unless
# specified otherwise, this must conform to the
# WGS84
# standard. Values must be within normalized ranges.
"latitude": 3.14, # The latitude in degrees. It must be in the range [-90.0, +90.0].
"longitude": 3.14, # The longitude in degrees. It must be in the range [-180.0, +180.0].
},
"maxLatLng": { # An object representing a latitude/longitude pair. This is expressed as a pair # Max lat/long pair.
# of doubles representing degrees latitude and degrees longitude. Unless
# specified otherwise, this must conform to the
# WGS84
# standard. Values must be within normalized ranges.
"latitude": 3.14, # The latitude in degrees. It must be in the range [-90.0, +90.0].
"longitude": 3.14, # The longitude in degrees. It must be in the range [-180.0, +180.0].
},
},
"languageHints": [ # List of languages to use for TEXT_DETECTION. In most cases, an empty value
# yields the best results since it enables automatic language detection. For
# languages based on the Latin alphabet, setting `language_hints` is not
# needed. In rare cases, when the language of the text in the image is known,
# setting a hint will help get better results (although it will be a
# significant hindrance if the hint is wrong). Text detection returns an
# error if one or more of the specified languages is not one of the
# [supported languages](/vision/docs/languages).
"A String",
],
"productSearchParams": { # Parameters for a product search request. # Parameters for product search.
"productCategories": [ # The list of product categories to search in. Currently, we only consider
# the first category, and either "homegoods-v2", "apparel-v2", or "toys-v2"
# should be specified. The legacy categories "homegoods", "apparel", and
# "toys" are still supported but will be deprecated. For new products, please
# use "homegoods-v2", "apparel-v2", or "toys-v2" for better product search
# accuracy. It is recommended to migrate existing products to these
# categories as well.
"A String",
],
"filter": "A String", # The filtering expression. This can be used to restrict search results based
# on Product labels. We currently support an AND of OR of key-value
# expressions, where each expression within an OR must have the same key. An
# '=' should be used to connect the key and value.
#
# For example, "(color = red OR color = blue) AND brand = Google" is
# acceptable, but "(color = red OR brand = Google)" is not acceptable.
# "color: red" is not acceptable because it uses a ':' instead of an '='.
"productSet": "A String", # The resource name of a ProductSet to be searched for similar images.
#
# Format is:
# `projects/PROJECT_ID/locations/LOC_ID/productSets/PRODUCT_SET_ID`.
"boundingPoly": { # A bounding polygon for the detected image annotation. # The bounding polygon around the area of interest in the image.
# Optional. If it is not specified, system discretion will be applied.
"normalizedVertices": [ # The bounding polygon normalized vertices.
{ # A vertex represents a 2D point in the image.
# NOTE: the normalized vertex coordinates are relative to the original image
# and range from 0 to 1.
"y": 3.14, # Y coordinate.
"x": 3.14, # X coordinate.
},
],
"vertices": [ # The bounding polygon vertices.
{ # A vertex represents a 2D point in the image.
# NOTE: the vertex coordinates are in the same scale as the original image.
"y": 42, # Y coordinate.
"x": 42, # X coordinate.
},
],
},
},
"cropHintsParams": { # Parameters for crop hints annotation request. # Parameters for crop hints annotation request.
"aspectRatios": [ # Aspect ratios in floats, representing the ratio of the width to the height
# of the image. For example, if the desired aspect ratio is 4/3, the
# corresponding float value should be 1.33333. If not specified, the
# best possible crop is returned. The number of provided aspect ratios is
# limited to a maximum of 16; any aspect ratios provided after the 16th are
# ignored.
3.14,
],
},
"webDetectionParams": { # Parameters for web detection request. # Parameters for web detection.
"includeGeoResults": True or False, # Whether to include results derived from the geo information in the image.
},
},
"outputConfig": { # The desired output location and metadata. # Required. The desired output location and metadata (e.g. format).
"batchSize": 42, # The max number of response protos to put into each output JSON file on
# Google Cloud Storage.
# The valid range is [1, 100]. If not specified, the default value is 20.
#
# For example, for one pdf file with 100 pages, 100 response protos will
# be generated. If `batch_size` = 20, then 5 json files each
# containing 20 response protos will be written under the prefix
# `gcs_destination`.`uri`.
#
# Currently, batch_size only applies to GcsDestination, with potential future
# support for other output configurations.
"gcsDestination": { # The Google Cloud Storage location where the output will be written to. # The Google Cloud Storage location to write the output(s) to.
"uri": "A String", # Google Cloud Storage URI prefix where the results will be stored. Results
# will be in JSON format and preceded by its corresponding input URI prefix.
# This field can either represent a gcs file prefix or gcs directory. In
# either case, the uri should be unique because in order to get all of the
# output files, you will need to do a wildcard gcs search on the uri prefix
# you provide.
#
# Examples:
#
# * File Prefix: gs://bucket-name/here/filenameprefix The output files
# will be created in gs://bucket-name/here/ and the names of the
# output files will begin with "filenameprefix".
#
# * Directory Prefix: gs://bucket-name/some/location/ The output files
# will be created in gs://bucket-name/some/location/ and the names of the
# output files could be anything because there was no filename prefix
# specified.
#
# If multiple outputs, each response is still AnnotateFileResponse, each of
# which contains some subset of the full list of AnnotateImageResponse.
# Multiple outputs can happen if, for example, the output JSON is too large
# and overflows into multiple sharded files.
},
},
"inputConfig": { # The desired input location and metadata. # Required. Information about the input file.
"mimeType": "A String", # The type of the file. Currently only "application/pdf", "image/tiff" and
# "image/gif" are supported. Wildcards are not supported.
"content": "A String", # File content, represented as a stream of bytes.
# Note: As with all `bytes` fields, protobuffers use a pure binary
# representation, whereas JSON representations use base64.
#
# Currently, this field only works for BatchAnnotateFiles requests. It does
# not work for AsyncBatchAnnotateFiles requests.
"gcsSource": { # The Google Cloud Storage location where the input will be read from. # The Google Cloud Storage location to read the input from.
"uri": "A String", # Google Cloud Storage URI for the input file. This must only be a
# Google Cloud Storage object. Wildcards are not currently supported.
},
},
"features": [ # Required. Requested features.
{ # The type of Google Cloud Vision API detection to perform, and the maximum
# number of results to return for that type. Multiple `Feature` objects can
# be specified in the `features` list.
"model": "A String", # Model to use for the feature.
# Supported values: "builtin/stable" (the default if unset) and
# "builtin/latest".
"type": "A String", # The feature type.
"maxResults": 42, # Maximum number of results of this type. Does not apply to
# `TEXT_DETECTION`, `DOCUMENT_TEXT_DETECTION`, or `CROP_HINTS`.
},
],
},
],
}
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # This resource represents a long-running operation that is the result of a
# network API call.
"metadata": { # Service-specific metadata associated with the operation. It typically
# contains progress information and common metadata such as create time.
# Some services might not provide such metadata. Any method that returns a
# long-running operation should document the metadata type, if any.
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
"error": { # The `Status` type defines a logical error model that is suitable for # The error result of the operation in case of failure or cancellation.
# different programming environments, including REST APIs and RPC APIs. It is
# used by [gRPC](https://github.com/grpc). Each `Status` message contains
# three pieces of data: error code, error message, and error details.
#
# You can find out more about this error model and how to work with it in the
# [API Design Guide](https://cloud.google.com/apis/design/errors).
"message": "A String", # A developer-facing error message, which should be in English. Any
# user-facing error message should be localized and sent in the
# google.rpc.Status.details field, or localized by the client.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of
# message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
},
"done": True or False, # If the value is `false`, it means the operation is still in progress.
# If `true`, the operation is completed, and either `error` or `response` is
# available.
"response": { # The normal response of the operation in case of success. If the original
# method returns no data on success, such as `Delete`, the response is
# `google.protobuf.Empty`. If the original method is standard
# `Get`/`Create`/`Update`, the response should be the resource. For other
# methods, the response should have the type `XxxResponse`, where `Xxx`
# is the original method name. For example, if the original method name
# is `TakeSnapshot()`, the inferred response type is
# `TakeSnapshotResponse`.
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
"name": "A String", # The server-assigned name, which is only unique within the same service that
# originally returns it. If you use the default HTTP mapping, the
# `name` should be a resource name ending with `operations/{unique_id}`.
}