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<h1><a href="vision_v1p2beta1.html">Cloud Vision API</a> . <a href="vision_v1p2beta1.projects.html">projects</a> . <a href="vision_v1p2beta1.projects.images.html">images</a></h1>

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<h2>Instance Methods</h2>

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<code><a href="#annotate">annotate(parent, body=None, x__xgafv=None)</a></code></p>

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<p class="firstline">Run image detection and annotation for a batch of images.</p>

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<code><a href="#asyncBatchAnnotate">asyncBatchAnnotate(parent, body=None, x__xgafv=None)</a></code></p>

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<p class="firstline">Run asynchronous image detection and annotation for a list of images.</p>

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<h3>Method Details</h3>

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<code class="details" id="annotate">annotate(parent, body=None, x__xgafv=None)</code>

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<pre>Run image detection and annotation for a batch of images.

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Args:

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parent: string, Optional. Target project and location to make a call.

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Format: `projects/{project-id}/locations/{location-id}`.

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If no parent is specified, a region will be chosen automatically.

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Supported location-ids:

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`us`: USA country only,

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`asia`: East asia areas, like Japan, Taiwan,

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`eu`: The European Union.

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Example: `projects/project-A/locations/eu`. (required)

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body: object, The request body.

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The object takes the form of:

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{ # Multiple image annotation requests are batched into a single service call.

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"parent": "A String", # Optional. Target project and location to make a call.

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#

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# Format: `projects/{project-id}/locations/{location-id}`.

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#

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# If no parent is specified, a region will be chosen automatically.

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#

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# Supported location-ids:

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# `us`: USA country only,

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# `asia`: East asia areas, like Japan, Taiwan,

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# `eu`: The European Union.

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#

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# Example: `projects/project-A/locations/eu`.

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"requests": [ # Required. Individual image annotation requests for this batch.

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{ # Request for performing Google Cloud Vision API tasks over a user-provided

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# image, with user-requested features, and with context information.

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"image": { # Client image to perform Google Cloud Vision API tasks over. # The image to be processed.

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"content": "A String", # Image content, represented as a stream of bytes.

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# Note: As with all `bytes` fields, protobuffers use a pure binary

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# representation, whereas JSON representations use base64.

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"source": { # External image source (Google Cloud Storage or web URL image location). # Google Cloud Storage image location, or publicly-accessible image

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# URL. If both `content` and `source` are provided for an image, `content`

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# takes precedence and is used to perform the image annotation request.

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"imageUri": "A String", # The URI of the source image. Can be either:

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#

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# 1. A Google Cloud Storage URI of the form

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# `gs://bucket_name/object_name`. Object versioning is not supported. See

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# [Google Cloud Storage Request

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# URIs](https://cloud.google.com/storage/docs/reference-uris) for more

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# info.

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#

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# 2. A publicly-accessible image HTTP/HTTPS URL. When fetching images from

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# HTTP/HTTPS URLs, Google cannot guarantee that the request will be

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# completed. Your request may fail if the specified host denies the

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# request (e.g. due to request throttling or DOS prevention), or if Google

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# throttles requests to the site for abuse prevention. You should not

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# depend on externally-hosted images for production applications.

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#

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# When both `gcs_image_uri` and `image_uri` are specified, `image_uri` takes

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# precedence.

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"gcsImageUri": "A String", # **Use `image_uri` instead.**

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#

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# The Google Cloud Storage URI of the form

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# `gs://bucket_name/object_name`. Object versioning is not supported. See

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# [Google Cloud Storage Request

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# URIs](https://cloud.google.com/storage/docs/reference-uris) for more info.

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},

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},

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"features": [ # Requested features.

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{ # The type of Google Cloud Vision API detection to perform, and the maximum

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# number of results to return for that type. Multiple `Feature` objects can

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# be specified in the `features` list.

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"type": "A String", # The feature type.

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"maxResults": 42, # Maximum number of results of this type. Does not apply to

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# `TEXT_DETECTION`, `DOCUMENT_TEXT_DETECTION`, or `CROP_HINTS`.

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"model": "A String", # Model to use for the feature.

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# Supported values: "builtin/stable" (the default if unset) and

# "builtin/latest".

},

],

"imageContext": { # Image context and/or feature-specific parameters. # Additional context that may accompany the image.

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"languageHints": [ # List of languages to use for TEXT_DETECTION. In most cases, an empty value

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# yields the best results since it enables automatic language detection. For

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# languages based on the Latin alphabet, setting `language_hints` is not

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# needed. In rare cases, when the language of the text in the image is known,

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# setting a hint will help get better results (although it will be a

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# significant hindrance if the hint is wrong). Text detection returns an

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# error if one or more of the specified languages is not one of the

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# [supported languages](https://cloud.google.com/vision/docs/languages).

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"A String",

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],

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"webDetectionParams": { # Parameters for web detection request. # Parameters for web detection.

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"includeGeoResults": True or False, # Whether to include results derived from the geo information in the image.

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},

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"latLongRect": { # Rectangle determined by min and max `LatLng` pairs. # Not used.

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"minLatLng": { # An object representing a latitude/longitude pair. This is expressed as a pair # Min lat/long pair.

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# of doubles representing degrees latitude and degrees longitude. Unless

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# specified otherwise, this must conform to the

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# <a href="http://www.unoosa.org/pdf/icg/2012/template/WGS_84.pdf">WGS84

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# standard</a>. Values must be within normalized ranges.

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"latitude": 3.14, # The latitude in degrees. It must be in the range [-90.0, +90.0].

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"longitude": 3.14, # The longitude in degrees. It must be in the range [-180.0, +180.0].

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},

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"maxLatLng": { # An object representing a latitude/longitude pair. This is expressed as a pair # Max lat/long pair.

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# of doubles representing degrees latitude and degrees longitude. Unless

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# specified otherwise, this must conform to the

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# <a href="http://www.unoosa.org/pdf/icg/2012/template/WGS_84.pdf">WGS84

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# standard</a>. Values must be within normalized ranges.

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"latitude": 3.14, # The latitude in degrees. It must be in the range [-90.0, +90.0].

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"longitude": 3.14, # The longitude in degrees. It must be in the range [-180.0, +180.0].

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},

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},

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"cropHintsParams": { # Parameters for crop hints annotation request. # Parameters for crop hints annotation request.

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"aspectRatios": [ # Aspect ratios in floats, representing the ratio of the width to the height

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# of the image. For example, if the desired aspect ratio is 4/3, the

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# corresponding float value should be 1.33333. If not specified, the

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# best possible crop is returned. The number of provided aspect ratios is

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# limited to a maximum of 16; any aspect ratios provided after the 16th are

# ignored.

3.14,

],

},

"productSearchParams": { # Parameters for a product search request. # Parameters for product search.

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"productSet": "A String", # The resource name of a ProductSet to be searched for similar images.

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#

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# Format is:

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# `projects/PROJECT_ID/locations/LOC_ID/productSets/PRODUCT_SET_ID`.

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"boundingPoly": { # A bounding polygon for the detected image annotation. # The bounding polygon around the area of interest in the image.

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# If it is not specified, system discretion will be applied.

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"normalizedVertices": [ # The bounding polygon normalized vertices.

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{ # A vertex represents a 2D point in the image.

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# NOTE: the normalized vertex coordinates are relative to the original image

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# and range from 0 to 1.

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"y": 3.14, # Y coordinate.

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"x": 3.14, # X coordinate.

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},

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],

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"vertices": [ # The bounding polygon vertices.

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{ # A vertex represents a 2D point in the image.

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# NOTE: the vertex coordinates are in the same scale as the original image.

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"y": 42, # Y coordinate.

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"x": 42, # X coordinate.

},

],

},

"productCategories": [ # The list of product categories to search in. Currently, we only consider

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# the first category, and either "homegoods-v2", "apparel-v2", "toys-v2",

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# "packagedgoods-v1", or "general-v1" should be specified. The legacy

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# categories "homegoods", "apparel", and "toys" are still supported but will

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# be deprecated. For new products, please use "homegoods-v2", "apparel-v2",

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# or "toys-v2" for better product search accuracy. It is recommended to

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# migrate existing products to these categories as well.

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"A String",

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],

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"filter": "A String", # The filtering expression. This can be used to restrict search results based

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# on Product labels. We currently support an AND of OR of key-value

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# expressions, where each expression within an OR must have the same key. An

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# '=' should be used to connect the key and value.

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#

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# For example, "(color = red OR color = blue) AND brand = Google" is

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# acceptable, but "(color = red OR brand = Google)" is not acceptable.

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# "color: red" is not acceptable because it uses a ':' instead of an '='.

},

},

},

],

}

x__xgafv: string, V1 error format.

Allowed values

1 - v1 error format

2 - v2 error format

Returns:

An object of the form:

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{ # Response to a batch image annotation request.

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"responses": [ # Individual responses to image annotation requests within the batch.

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{ # Response to an image annotation request.

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"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

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# comes from.

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# information about the source of that image.

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"uri": "A String", # The URI of the file used to produce the image.

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"pageNumber": 42, # If the file was a PDF or TIFF, this field gives the page number within

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# the file used to produce the image.

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},

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"logoAnnotations": [ # If present, logo detection has completed successfully.

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{ # Set of detected entity features.

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"properties": [ # Some entities may have optional user-supplied `Property` (name/value)

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# fields, such a score or string that qualifies the entity.

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{ # A `Property` consists of a user-supplied name/value pair.

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"uint64Value": "A String", # Value of numeric properties.

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"name": "A String", # Name of the property.

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"value": "A String", # Value of the property.

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},

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],

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"score": 3.14, # Overall score of the result. Range [0, 1].

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"locations": [ # The location information for the detected entity. Multiple

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# `LocationInfo` elements can be present because one location may

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# indicate the location of the scene in the image, and another location

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# may indicate the location of the place where the image was taken.

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# Location information is usually present for landmarks.

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{ # Detected entity location information.

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"latLng": { # An object representing a latitude/longitude pair. This is expressed as a pair # lat/long location coordinates.

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# of doubles representing degrees latitude and degrees longitude. Unless

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# specified otherwise, this must conform to the

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# <a href="http://www.unoosa.org/pdf/icg/2012/template/WGS_84.pdf">WGS84

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# standard</a>. Values must be within normalized ranges.

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"latitude": 3.14, # The latitude in degrees. It must be in the range [-90.0, +90.0].

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"longitude": 3.14, # The longitude in degrees. It must be in the range [-180.0, +180.0].

},

},

],

"mid": "A String", # Opaque entity ID. Some IDs may be available in

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# [Google Knowledge Graph Search

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# API](https://developers.google.com/knowledge-graph/).

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"confidence": 3.14, # **Deprecated. Use `score` instead.**

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# The accuracy of the entity detection in an image.

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# For example, for an image in which the "Eiffel Tower" entity is detected,

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# this field represents the confidence that there is a tower in the query

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# image. Range [0, 1].

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"locale": "A String", # The language code for the locale in which the entity textual

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# `description` is expressed.

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"boundingPoly": { # A bounding polygon for the detected image annotation. # Image region to which this entity belongs. Not produced

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# for `LABEL_DETECTION` features.

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"normalizedVertices": [ # The bounding polygon normalized vertices.

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{ # A vertex represents a 2D point in the image.

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# NOTE: the normalized vertex coordinates are relative to the original image

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# and range from 0 to 1.

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"y": 3.14, # Y coordinate.

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"x": 3.14, # X coordinate.

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},

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],

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"vertices": [ # The bounding polygon vertices.

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{ # A vertex represents a 2D point in the image.

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# NOTE: the vertex coordinates are in the same scale as the original image.

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"y": 42, # Y coordinate.

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"x": 42, # X coordinate.

},

],

},

"description": "A String", # Entity textual description, expressed in its `locale` language.

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"topicality": 3.14, # The relevancy of the ICA (Image Content Annotation) label to the

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# image. For example, the relevancy of "tower" is likely higher to an image

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# containing the detected "Eiffel Tower" than to an image containing a

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# detected distant towering building, even though the confidence that

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# there is a tower in each image may be the same. Range [0, 1].

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},

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],

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"webDetection": { # Relevant information for the image from the Internet. # If present, web detection has completed successfully.

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"webEntities": [ # Deduced entities from similar images on the Internet.

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{ # Entity deduced from similar images on the Internet.

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"entityId": "A String", # Opaque entity ID.

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"description": "A String", # Canonical description of the entity, in English.

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"score": 3.14, # Overall relevancy score for the entity.

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# Not normalized and not comparable across different image queries.

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},

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],

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"pagesWithMatchingImages": [ # Web pages containing the matching images from the Internet.

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{ # Metadata for web pages.

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"score": 3.14, # (Deprecated) Overall relevancy score for the web page.

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"partialMatchingImages": [ # Partial matching images on the page.

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# Those images are similar enough to share some key-point features. For

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# example an original image will likely have partial matching for its

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# crops.

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{ # Metadata for online images.

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"score": 3.14, # (Deprecated) Overall relevancy score for the image.

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"url": "A String", # The result image URL.

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},

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],

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"url": "A String", # The result web page URL.

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"pageTitle": "A String", # Title for the web page, may contain HTML markups.

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"fullMatchingImages": [ # Fully matching images on the page.

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# Can include resized copies of the query image.

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{ # Metadata for online images.

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"score": 3.14, # (Deprecated) Overall relevancy score for the image.

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"url": "A String", # The result image URL.

},

],

},

],

"partialMatchingImages": [ # Partial matching images from the Internet.

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# Those images are similar enough to share some key-point features. For

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# example an original image will likely have partial matching for its crops.

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{ # Metadata for online images.

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"score": 3.14, # (Deprecated) Overall relevancy score for the image.

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"url": "A String", # The result image URL.

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},

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],

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"visuallySimilarImages": [ # The visually similar image results.

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{ # Metadata for online images.

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"score": 3.14, # (Deprecated) Overall relevancy score for the image.

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"url": "A String", # The result image URL.

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},

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],

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"bestGuessLabels": [ # The service's best guess as to the topic of the request image.

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# Inferred from similar images on the open web.

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{ # Label to provide extra metadata for the web detection.

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"label": "A String", # Label for extra metadata.

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"languageCode": "A String", # The BCP-47 language code for `label`, such as "en-US" or "sr-Latn".

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# For more information, see

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# http://www.unicode.org/reports/tr35/#Unicode_locale_identifier.

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},

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],

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"fullMatchingImages": [ # Fully matching images from the Internet.

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# Can include resized copies of the query image.

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{ # Metadata for online images.

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"score": 3.14, # (Deprecated) Overall relevancy score for the image.

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"url": "A String", # The result image URL.

},

],

},

"safeSearchAnnotation": { # Set of features pertaining to the image, computed by computer vision # If present, safe-search annotation has completed successfully.

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# methods over safe-search verticals (for example, adult, spoof, medical,

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# violence).

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"racy": "A String", # Likelihood that the request image contains racy content. Racy content may

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# include (but is not limited to) skimpy or sheer clothing, strategically

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# covered nudity, lewd or provocative poses, or close-ups of sensitive

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# body areas.

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"violence": "A String", # Likelihood that this image contains violent content.

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"adult": "A String", # Represents the adult content likelihood for the image. Adult content may

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# contain elements such as nudity, pornographic images or cartoons, or

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# sexual activities.

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"spoof": "A String", # Spoof likelihood. The likelihood that an modification

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# was made to the image's canonical version to make it appear

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# funny or offensive.

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"medical": "A String", # Likelihood that this is a medical image.

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},

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"landmarkAnnotations": [ # If present, landmark detection has completed successfully.

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{ # Set of detected entity features.

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"properties": [ # Some entities may have optional user-supplied `Property` (name/value)

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# fields, such a score or string that qualifies the entity.

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{ # A `Property` consists of a user-supplied name/value pair.

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"uint64Value": "A String", # Value of numeric properties.

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"name": "A String", # Name of the property.

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"value": "A String", # Value of the property.

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},

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],

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"score": 3.14, # Overall score of the result. Range [0, 1].

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"locations": [ # The location information for the detected entity. Multiple

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# `LocationInfo` elements can be present because one location may

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# indicate the location of the scene in the image, and another location

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# may indicate the location of the place where the image was taken.

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# Location information is usually present for landmarks.

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{ # Detected entity location information.

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"latLng": { # An object representing a latitude/longitude pair. This is expressed as a pair # lat/long location coordinates.

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# of doubles representing degrees latitude and degrees longitude. Unless

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# specified otherwise, this must conform to the

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# <a href="http://www.unoosa.org/pdf/icg/2012/template/WGS_84.pdf">WGS84

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# standard</a>. Values must be within normalized ranges.

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"latitude": 3.14, # The latitude in degrees. It must be in the range [-90.0, +90.0].

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"longitude": 3.14, # The longitude in degrees. It must be in the range [-180.0, +180.0].

},

},

],

"mid": "A String", # Opaque entity ID. Some IDs may be available in

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# [Google Knowledge Graph Search

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# API](https://developers.google.com/knowledge-graph/).

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"confidence": 3.14, # **Deprecated. Use `score` instead.**

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# The accuracy of the entity detection in an image.

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# For example, for an image in which the "Eiffel Tower" entity is detected,

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# this field represents the confidence that there is a tower in the query

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# image. Range [0, 1].

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"locale": "A String", # The language code for the locale in which the entity textual

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# `description` is expressed.

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"boundingPoly": { # A bounding polygon for the detected image annotation. # Image region to which this entity belongs. Not produced

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# for `LABEL_DETECTION` features.

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"normalizedVertices": [ # The bounding polygon normalized vertices.

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{ # A vertex represents a 2D point in the image.

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# NOTE: the normalized vertex coordinates are relative to the original image

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# and range from 0 to 1.

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"y": 3.14, # Y coordinate.

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"x": 3.14, # X coordinate.

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},

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],

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"vertices": [ # The bounding polygon vertices.

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{ # A vertex represents a 2D point in the image.

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# NOTE: the vertex coordinates are in the same scale as the original image.

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"y": 42, # Y coordinate.

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"x": 42, # X coordinate.

},

],

},

"description": "A String", # Entity textual description, expressed in its `locale` language.

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"topicality": 3.14, # The relevancy of the ICA (Image Content Annotation) label to the

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# image. For example, the relevancy of "tower" is likely higher to an image

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# containing the detected "Eiffel Tower" than to an image containing a

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# detected distant towering building, even though the confidence that

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# there is a tower in each image may be the same. Range [0, 1].

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},

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],

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"faceAnnotations": [ # If present, face detection has completed successfully.

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{ # A face annotation object contains the results of face detection.

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"boundingPoly": { # A bounding polygon for the detected image annotation. # The bounding polygon around the face. The coordinates of the bounding box

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# are in the original image's scale.

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# The bounding box is computed to "frame" the face in accordance with human

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# expectations. It is based on the landmarker results.

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# Note that one or more x and/or y coordinates may not be generated in the

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# `BoundingPoly` (the polygon will be unbounded) if only a partial face

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# appears in the image to be annotated.

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"normalizedVertices": [ # The bounding polygon normalized vertices.

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{ # A vertex represents a 2D point in the image.

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# NOTE: the normalized vertex coordinates are relative to the original image

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# and range from 0 to 1.

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"y": 3.14, # Y coordinate.

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"x": 3.14, # X coordinate.

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},

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],

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"vertices": [ # The bounding polygon vertices.

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{ # A vertex represents a 2D point in the image.

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# NOTE: the vertex coordinates are in the same scale as the original image.

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"y": 42, # Y coordinate.

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"x": 42, # X coordinate.

},

],

},

"rollAngle": 3.14, # Roll angle, which indicates the amount of clockwise/anti-clockwise rotation

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# of the face relative to the image vertical about the axis perpendicular to

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# the face. Range [-180,180].

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"sorrowLikelihood": "A String", # Sorrow likelihood.

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"tiltAngle": 3.14, # Pitch angle, which indicates the upwards/downwards angle that the face is

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# pointing relative to the image's horizontal plane. Range [-180,180].

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"fdBoundingPoly": { # A bounding polygon for the detected image annotation. # The `fd_bounding_poly` bounding polygon is tighter than the

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# `boundingPoly`, and encloses only the skin part of the face. Typically, it

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# is used to eliminate the face from any image analysis that detects the

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# "amount of skin" visible in an image. It is not based on the

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# landmarker results, only on the initial face detection, hence

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# the <code>fd</code> (face detection) prefix.

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"normalizedVertices": [ # The bounding polygon normalized vertices.

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{ # A vertex represents a 2D point in the image.

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# NOTE: the normalized vertex coordinates are relative to the original image

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# and range from 0 to 1.

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"y": 3.14, # Y coordinate.

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"x": 3.14, # X coordinate.

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},

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],

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"vertices": [ # The bounding polygon vertices.

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{ # A vertex represents a 2D point in the image.

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# NOTE: the vertex coordinates are in the same scale as the original image.

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"y": 42, # Y coordinate.

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"x": 42, # X coordinate.

},

],

},

"angerLikelihood": "A String", # Anger likelihood.

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"landmarks": [ # Detected face landmarks.

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{ # A face-specific landmark (for example, a face feature).

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"position": { # A 3D position in the image, used primarily for Face detection landmarks. # Face landmark position.

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# A valid Position must have both x and y coordinates.

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# The position coordinates are in the same scale as the original image.

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"y": 3.14, # Y coordinate.

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"x": 3.14, # X coordinate.

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"z": 3.14, # Z coordinate (or depth).

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},

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"type": "A String", # Face landmark type.

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},

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],

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"surpriseLikelihood": "A String", # Surprise likelihood.

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"landmarkingConfidence": 3.14, # Face landmarking confidence. Range [0, 1].

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"joyLikelihood": "A String", # Joy likelihood.

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"underExposedLikelihood": "A String", # Under-exposed likelihood.

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"panAngle": 3.14, # Yaw angle, which indicates the leftward/rightward angle that the face is

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# pointing relative to the vertical plane perpendicular to the image. Range

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# [-180,180].

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"detectionConfidence": 3.14, # Detection confidence. Range [0, 1].

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"blurredLikelihood": "A String", # Blurred likelihood.

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"headwearLikelihood": "A String", # Headwear likelihood.

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},

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],

553

"cropHintsAnnotation": { # Set of crop hints that are used to generate new crops when serving images. # If present, crop hints have completed successfully.

554

"cropHints": [ # Crop hint results.

555

{ # Single crop hint that is used to generate a new crop when serving an image.

556

"confidence": 3.14, # Confidence of this being a salient region. Range [0, 1].

557

"importanceFraction": 3.14, # Fraction of importance of this salient region with respect to the original

558

# image.

559

"boundingPoly": { # A bounding polygon for the detected image annotation. # The bounding polygon for the crop region. The coordinates of the bounding

560

# box are in the original image's scale.

561

"normalizedVertices": [ # The bounding polygon normalized vertices.

562

{ # A vertex represents a 2D point in the image.

563

# NOTE: the normalized vertex coordinates are relative to the original image

564

# and range from 0 to 1.

565

"y": 3.14, # Y coordinate.

566

"x": 3.14, # X coordinate.

567

},

568

],

569

"vertices": [ # The bounding polygon vertices.

570

{ # A vertex represents a 2D point in the image.

571

# NOTE: the vertex coordinates are in the same scale as the original image.

572

"y": 42, # Y coordinate.

573

"x": 42, # X coordinate.

},

],

},

},

],

},

"labelAnnotations": [ # If present, label detection has completed successfully.

581

{ # Set of detected entity features.

582

"properties": [ # Some entities may have optional user-supplied `Property` (name/value)

583

# fields, such a score or string that qualifies the entity.

584

{ # A `Property` consists of a user-supplied name/value pair.

585

"uint64Value": "A String", # Value of numeric properties.

586

"name": "A String", # Name of the property.

587

"value": "A String", # Value of the property.

588

},

589

],

590

"score": 3.14, # Overall score of the result. Range [0, 1].

591

"locations": [ # The location information for the detected entity. Multiple

592

# `LocationInfo` elements can be present because one location may

593

# indicate the location of the scene in the image, and another location

594

# may indicate the location of the place where the image was taken.

595

# Location information is usually present for landmarks.

596

{ # Detected entity location information.

597

"latLng": { # An object representing a latitude/longitude pair. This is expressed as a pair # lat/long location coordinates.

598

# of doubles representing degrees latitude and degrees longitude. Unless

599

# specified otherwise, this must conform to the

600

# <a href="http://www.unoosa.org/pdf/icg/2012/template/WGS_84.pdf">WGS84

601

# standard</a>. Values must be within normalized ranges.

602

"latitude": 3.14, # The latitude in degrees. It must be in the range [-90.0, +90.0].

603

"longitude": 3.14, # The longitude in degrees. It must be in the range [-180.0, +180.0].

},

},

],

"mid": "A String", # Opaque entity ID. Some IDs may be available in

608

# [Google Knowledge Graph Search

609

# API](https://developers.google.com/knowledge-graph/).

610

"confidence": 3.14, # **Deprecated. Use `score` instead.**

611

# The accuracy of the entity detection in an image.

612

# For example, for an image in which the "Eiffel Tower" entity is detected,

613

# this field represents the confidence that there is a tower in the query

614

# image. Range [0, 1].

615

"locale": "A String", # The language code for the locale in which the entity textual

616

# `description` is expressed.

617

"boundingPoly": { # A bounding polygon for the detected image annotation. # Image region to which this entity belongs. Not produced

618

# for `LABEL_DETECTION` features.

619

"normalizedVertices": [ # The bounding polygon normalized vertices.

620

{ # A vertex represents a 2D point in the image.

621

# NOTE: the normalized vertex coordinates are relative to the original image

622

# and range from 0 to 1.

623

"y": 3.14, # Y coordinate.

624

"x": 3.14, # X coordinate.

625

},

626

],

627

"vertices": [ # The bounding polygon vertices.

628

{ # A vertex represents a 2D point in the image.

629

# NOTE: the vertex coordinates are in the same scale as the original image.

630

"y": 42, # Y coordinate.

631

"x": 42, # X coordinate.

},

],

},

"description": "A String", # Entity textual description, expressed in its `locale` language.

636

"topicality": 3.14, # The relevancy of the ICA (Image Content Annotation) label to the

637

# image. For example, the relevancy of "tower" is likely higher to an image

638

# containing the detected "Eiffel Tower" than to an image containing a

639

# detected distant towering building, even though the confidence that

640

# there is a tower in each image may be the same. Range [0, 1].

641

},

642

],

643

"localizedObjectAnnotations": [ # If present, localized object detection has completed successfully.

644

# This will be sorted descending by confidence score.

645

{ # Set of detected objects with bounding boxes.

646

"languageCode": "A String", # The BCP-47 language code, such as "en-US" or "sr-Latn". For more

647

# information, see

648

# http://www.unicode.org/reports/tr35/#Unicode_locale_identifier.

649

"mid": "A String", # Object ID that should align with EntityAnnotation mid.

650

"name": "A String", # Object name, expressed in its `language_code` language.

651

"boundingPoly": { # A bounding polygon for the detected image annotation. # Image region to which this object belongs. This must be populated.

652

"normalizedVertices": [ # The bounding polygon normalized vertices.

653

{ # A vertex represents a 2D point in the image.

654

# NOTE: the normalized vertex coordinates are relative to the original image

655

# and range from 0 to 1.

656

"y": 3.14, # Y coordinate.

657

"x": 3.14, # X coordinate.

658

},

659

],

660

"vertices": [ # The bounding polygon vertices.

661

{ # A vertex represents a 2D point in the image.

662

# NOTE: the vertex coordinates are in the same scale as the original image.

663

"y": 42, # Y coordinate.

664

"x": 42, # X coordinate.

},

],

},

"score": 3.14, # Score of the result. Range [0, 1].

669

},

670

],

671

"productSearchResults": { # Results for a product search request. # If present, product search has completed successfully.

672

"indexTime": "A String", # Timestamp of the index which provided these results. Products added to the

673

# product set and products removed from the product set after this time are

674

# not reflected in the current results.

675

"productGroupedResults": [ # List of results grouped by products detected in the query image. Each entry

676

# corresponds to one bounding polygon in the query image, and contains the

677

# matching products specific to that region. There may be duplicate product

678

# matches in the union of all the per-product results.

679

{ # Information about the products similar to a single product in a query

680

# image.

681

"objectAnnotations": [ # List of generic predictions for the object in the bounding box.

682

{ # Prediction for what the object in the bounding box is.

683

"score": 3.14, # Score of the result. Range [0, 1].

684

"languageCode": "A String", # The BCP-47 language code, such as "en-US" or "sr-Latn". For more

685

# information, see

686

# http://www.unicode.org/reports/tr35/#Unicode_locale_identifier.

687

"mid": "A String", # Object ID that should align with EntityAnnotation mid.

688

"name": "A String", # Object name, expressed in its `language_code` language.

689

},

690

],

691

"boundingPoly": { # A bounding polygon for the detected image annotation. # The bounding polygon around the product detected in the query image.

692

"normalizedVertices": [ # The bounding polygon normalized vertices.

693

{ # A vertex represents a 2D point in the image.

694

# NOTE: the normalized vertex coordinates are relative to the original image

695

# and range from 0 to 1.

696

"y": 3.14, # Y coordinate.

697

"x": 3.14, # X coordinate.

698

},

699

],

700

"vertices": [ # The bounding polygon vertices.

701

{ # A vertex represents a 2D point in the image.

702

# NOTE: the vertex coordinates are in the same scale as the original image.

703

"y": 42, # Y coordinate.

704

"x": 42, # X coordinate.

},

],

},

"results": [ # List of results, one for each product match.

709

{ # Information about a product.

710

"image": "A String", # The resource name of the image from the product that is the closest match

711

# to the query.

712

"product": { # A Product contains ReferenceImages. # The Product.

713

"name": "A String", # The resource name of the product.

714

#

715

# Format is:

716

# `projects/PROJECT_ID/locations/LOC_ID/products/PRODUCT_ID`.

717

#

718

# This field is ignored when creating a product.

719

"displayName": "A String", # The user-provided name for this Product. Must not be empty. Must be at most

720

# 4096 characters long.

721

"description": "A String", # User-provided metadata to be stored with this product. Must be at most 4096

722

# characters long.

723

"productCategory": "A String", # Immutable. The category for the product identified by the reference image. This should

724

# be either "homegoods-v2", "apparel-v2", or "toys-v2". The legacy categories

725

# "homegoods", "apparel", and "toys" are still supported, but these should

726

# not be used for new products.

727

"productLabels": [ # Key-value pairs that can be attached to a product. At query time,

728

# constraints can be specified based on the product_labels.

729

#

730

# Note that integer values can be provided as strings, e.g. "1199". Only

731

# strings with integer values can match a range-based restriction which is

732

# to be supported soon.

733

#

734

# Multiple values can be assigned to the same key. One product may have up to

735

# 500 product_labels.

736

#

737

# Notice that the total number of distinct product_labels over all products

738

# in one ProductSet cannot exceed 1M, otherwise the product search pipeline

739

# will refuse to work for that ProductSet.

740

{ # A product label represented as a key-value pair.

741

"value": "A String", # The value of the label attached to the product. Cannot be empty and

742

# cannot exceed 128 bytes.

743

"key": "A String", # The key of the label attached to the product. Cannot be empty and cannot

# exceed 128 bytes.

},

],

},

"score": 3.14, # A confidence level on the match, ranging from 0 (no confidence) to

749

# 1 (full confidence).

},

],

},

],

"results": [ # List of results, one for each product match.

755

{ # Information about a product.

756

"image": "A String", # The resource name of the image from the product that is the closest match

757

# to the query.

758

"product": { # A Product contains ReferenceImages. # The Product.

759

"name": "A String", # The resource name of the product.

760

#

761

# Format is:

762

# `projects/PROJECT_ID/locations/LOC_ID/products/PRODUCT_ID`.

763

#

764

# This field is ignored when creating a product.

765

"displayName": "A String", # The user-provided name for this Product. Must not be empty. Must be at most

766

# 4096 characters long.

767

"description": "A String", # User-provided metadata to be stored with this product. Must be at most 4096

768

# characters long.

769

"productCategory": "A String", # Immutable. The category for the product identified by the reference image. This should

770

# be either "homegoods-v2", "apparel-v2", or "toys-v2". The legacy categories

771

# "homegoods", "apparel", and "toys" are still supported, but these should

772

# not be used for new products.

773

"productLabels": [ # Key-value pairs that can be attached to a product. At query time,

774

# constraints can be specified based on the product_labels.

775

#

776

# Note that integer values can be provided as strings, e.g. "1199". Only

777

# strings with integer values can match a range-based restriction which is

778

# to be supported soon.

779

#

780

# Multiple values can be assigned to the same key. One product may have up to

781

# 500 product_labels.

782

#

783

# Notice that the total number of distinct product_labels over all products

784

# in one ProductSet cannot exceed 1M, otherwise the product search pipeline

785

# will refuse to work for that ProductSet.

786

{ # A product label represented as a key-value pair.

787

"value": "A String", # The value of the label attached to the product. Cannot be empty and

788

# cannot exceed 128 bytes.

789

"key": "A String", # The key of the label attached to the product. Cannot be empty and cannot

# exceed 128 bytes.

},

],

},

"score": 3.14, # A confidence level on the match, ranging from 0 (no confidence) to

795

# 1 (full confidence).

},

],

},

"error": { # The `Status` type defines a logical error model that is suitable for # If set, represents the error message for the operation.

800

# Note that filled-in image annotations are guaranteed to be

801

# correct, even when `error` is set.

802

# different programming environments, including REST APIs and RPC APIs. It is

803

# used by [gRPC](https://github.com/grpc). Each `Status` message contains

804

# three pieces of data: error code, error message, and error details.

805

#

806

# You can find out more about this error model and how to work with it in the

807

# [API Design Guide](https://cloud.google.com/apis/design/errors).

808

"code": 42, # The status code, which should be an enum value of google.rpc.Code.

809

"message": "A String", # A developer-facing error message, which should be in English. Any

810

# user-facing error message should be localized and sent in the

811

# google.rpc.Status.details field, or localized by the client.

812

"details": [ # A list of messages that carry the error details. There is a common set of

813

# message types for APIs to use.

814

{

815

"a_key": "", # Properties of the object. Contains field @type with type URL.

},

],

},

"fullTextAnnotation": { # TextAnnotation contains a structured representation of OCR extracted text. # If present, text (OCR) detection or document (OCR) text detection has

820

# completed successfully.

821

# This annotation provides the structural hierarchy for the OCR detected

822

# text.

823

# The hierarchy of an OCR extracted text structure is like this:

824

# TextAnnotation -> Page -> Block -> Paragraph -> Word -> Symbol

825

# Each structural component, starting from Page, may further have their own

826

# properties. Properties describe detected languages, breaks etc.. Please refer

827

# to the TextAnnotation.TextProperty message definition below for more

828

# detail.

829

"pages": [ # List of pages detected by OCR.

830

{ # Detected page from OCR.

831

"width": 42, # Page width. For PDFs the unit is points. For images (including

832

# TIFFs) the unit is pixels.

833

"blocks": [ # List of blocks of text, images etc on this page.

834

{ # Logical element on the page.

835

"property": { # Additional information detected on the structural component. # Additional information detected for the block.

836

"detectedLanguages": [ # A list of detected languages together with confidence.

837

{ # Detected language for a structural component.

838

"languageCode": "A String", # The BCP-47 language code, such as "en-US" or "sr-Latn". For more

839

# information, see

840

# http://www.unicode.org/reports/tr35/#Unicode_locale_identifier.

841

"confidence": 3.14, # Confidence of detected language. Range [0, 1].

842

},

843

],

844

"detectedBreak": { # Detected start or end of a structural component. # Detected start or end of a text segment.

845

"type": "A String", # Detected break type.

846

"isPrefix": True or False, # True if break prepends the element.

847

},

848

},

849

"blockType": "A String", # Detected block type (text, image etc) for this block.

850

"boundingBox": { # A bounding polygon for the detected image annotation. # The bounding box for the block.

851

# The vertices are in the order of top-left, top-right, bottom-right,

852

# bottom-left. When a rotation of the bounding box is detected the rotation

853

# is represented as around the top-left corner as defined when the text is

854

# read in the 'natural' orientation.

855

# For example:

856

#

857

# * 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).

870

"normalizedVertices": [ # The bounding polygon normalized vertices.

871

{ # A vertex represents a 2D point in the image.

872

# NOTE: the normalized vertex coordinates are relative to the original image

873

# and range from 0 to 1.

874

"y": 3.14, # Y coordinate.

875

"x": 3.14, # X coordinate.

876

},

877

],

878

"vertices": [ # The bounding polygon vertices.

879

{ # A vertex represents a 2D point in the image.

880

# NOTE: the vertex coordinates are in the same scale as the original image.

881

"y": 42, # Y coordinate.

882

"x": 42, # X coordinate.

},

],

},

"confidence": 3.14, # Confidence of the OCR results on the block. Range [0, 1].

887

"paragraphs": [ # List of paragraphs in this block (if this blocks is of type text).

888

{ # Structural unit of text representing a number of words in certain order.

889

"property": { # Additional information detected on the structural component. # Additional information detected for the paragraph.

890

"detectedLanguages": [ # A list of detected languages together with confidence.

891

{ # Detected language for a structural component.

892

"languageCode": "A String", # The BCP-47 language code, such as "en-US" or "sr-Latn". For more

893

# information, see

894

# http://www.unicode.org/reports/tr35/#Unicode_locale_identifier.

895

"confidence": 3.14, # Confidence of detected language. Range [0, 1].

896

},

897

],

898

"detectedBreak": { # Detected start or end of a structural component. # Detected start or end of a text segment.

899

"type": "A String", # Detected break type.

900

"isPrefix": True or False, # True if break prepends the element.

901

},

902

},

903

"boundingBox": { # A bounding polygon for the detected image annotation. # The bounding box for the paragraph.

904

# The vertices are in the order of top-left, top-right, bottom-right,

905

# bottom-left. When a rotation of the bounding box is detected the rotation

906

# is represented as around the top-left corner as defined when the text is

907

# read in the 'natural' orientation.

908

# For example:

909

# * 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).

918

"normalizedVertices": [ # The bounding polygon normalized vertices.

919

{ # A vertex represents a 2D point in the image.

920

# NOTE: the normalized vertex coordinates are relative to the original image

921

# and range from 0 to 1.

922

"y": 3.14, # Y coordinate.

923

"x": 3.14, # X coordinate.

924

},

925

],

926

"vertices": [ # The bounding polygon vertices.

927

{ # A vertex represents a 2D point in the image.

928

# NOTE: the vertex coordinates are in the same scale as the original image.

929

"y": 42, # Y coordinate.

930

"x": 42, # X coordinate.

},

],

},

"confidence": 3.14, # Confidence of the OCR results for the paragraph. Range [0, 1].

935

"words": [ # List of all words in this paragraph.

936

{ # A word representation.

937

"property": { # Additional information detected on the structural component. # Additional information detected for the word.

938

"detectedLanguages": [ # A list of detected languages together with confidence.

939

{ # Detected language for a structural component.

940

"languageCode": "A String", # The BCP-47 language code, such as "en-US" or "sr-Latn". For more

941

# information, see

942

# http://www.unicode.org/reports/tr35/#Unicode_locale_identifier.

943

"confidence": 3.14, # Confidence of detected language. Range [0, 1].

944

},

945

],

946

"detectedBreak": { # Detected start or end of a structural component. # Detected start or end of a text segment.

947

"type": "A String", # Detected break type.

948

"isPrefix": True or False, # True if break prepends the element.

949

},

950

},

951

"boundingBox": { # A bounding polygon for the detected image annotation. # The bounding box for the word.

952

# The vertices are in the order of top-left, top-right, bottom-right,

953

# bottom-left. When a rotation of the bounding box is detected the rotation

954

# is represented as around the top-left corner as defined when the text is

955

# read in the 'natural' orientation.

956

# For example:

957

# * 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).

966

"normalizedVertices": [ # The bounding polygon normalized vertices.

967

{ # A vertex represents a 2D point in the image.

968

# NOTE: the normalized vertex coordinates are relative to the original image

969

# and range from 0 to 1.

970

"y": 3.14, # Y coordinate.

971

"x": 3.14, # X coordinate.

972

},

973

],

974

"vertices": [ # The bounding polygon vertices.

975

{ # A vertex represents a 2D point in the image.

976

# NOTE: the vertex coordinates are in the same scale as the original image.

977

"y": 42, # Y coordinate.

978

"x": 42, # X coordinate.

},

],

},

"confidence": 3.14, # Confidence of the OCR results for the word. Range [0, 1].

983

"symbols": [ # List of symbols in the word.

984

# The order of the symbols follows the natural reading order.

985

{ # A single symbol representation.

986

"boundingBox": { # A bounding polygon for the detected image annotation. # The bounding box for the symbol.

987

# The vertices are in the order of top-left, top-right, bottom-right,

988

# bottom-left. When a rotation of the bounding box is detected the rotation

989

# is represented as around the top-left corner as defined when the text is

990

# read in the 'natural' orientation.

991

# For example:

992

# * 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).

1001

"normalizedVertices": [ # The bounding polygon normalized vertices.

1002

{ # A vertex represents a 2D point in the image.

1003

# NOTE: the normalized vertex coordinates are relative to the original image

1004

# and range from 0 to 1.

1005

"y": 3.14, # Y coordinate.

1006

"x": 3.14, # X coordinate.

1007

},

1008

],

1009

"vertices": [ # The bounding polygon vertices.

1010

{ # A vertex represents a 2D point in the image.

1011

# NOTE: the vertex coordinates are in the same scale as the original image.

1012

"y": 42, # Y coordinate.

1013

"x": 42, # X coordinate.

},

],

},

"confidence": 3.14, # Confidence of the OCR results for the symbol. Range [0, 1].

1018

"text": "A String", # The actual UTF-8 representation of the symbol.

1019

"property": { # Additional information detected on the structural component. # Additional information detected for the symbol.

1020

"detectedLanguages": [ # A list of detected languages together with confidence.

1021

{ # Detected language for a structural component.

1022

"languageCode": "A String", # The BCP-47 language code, such as "en-US" or "sr-Latn". For more

1023

# information, see

1024

# http://www.unicode.org/reports/tr35/#Unicode_locale_identifier.

1025

"confidence": 3.14, # Confidence of detected language. Range [0, 1].

1026

},

1027

],

1028

"detectedBreak": { # Detected start or end of a structural component. # Detected start or end of a text segment.

1029

"type": "A String", # Detected break type.

1030

"isPrefix": True or False, # True if break prepends the element.

},

},

},

],

},

],

},

],

},

],

"property": { # Additional information detected on the structural component. # Additional information detected on the page.

1042

"detectedLanguages": [ # A list of detected languages together with confidence.

1043

{ # Detected language for a structural component.

1044

"languageCode": "A String", # The BCP-47 language code, such as "en-US" or "sr-Latn". For more

1045

# information, see

1046

# http://www.unicode.org/reports/tr35/#Unicode_locale_identifier.

1047

"confidence": 3.14, # Confidence of detected language. Range [0, 1].

1048

},

1049

],

1050

"detectedBreak": { # Detected start or end of a structural component. # Detected start or end of a text segment.

1051

"type": "A String", # Detected break type.

1052

"isPrefix": True or False, # True if break prepends the element.

1053

},

1054

},

1055

"confidence": 3.14, # Confidence of the OCR results on the page. Range [0, 1].

1056

"height": 42, # Page height. For PDFs the unit is points. For images (including

1057

# TIFFs) the unit is pixels.

1058

},

1059

],

1060

"text": "A String", # UTF-8 text detected on the pages.

1061

},

1062

"textAnnotations": [ # If present, text (OCR) detection has completed successfully.

1063

{ # Set of detected entity features.

1064

"properties": [ # Some entities may have optional user-supplied `Property` (name/value)

1065

# fields, such a score or string that qualifies the entity.

1066

{ # A `Property` consists of a user-supplied name/value pair.

1067

"uint64Value": "A String", # Value of numeric properties.

1068

"name": "A String", # Name of the property.

1069

"value": "A String", # Value of the property.

1070

},

1071

],

1072

"score": 3.14, # Overall score of the result. Range [0, 1].

1073

"locations": [ # The location information for the detected entity. Multiple

1074

# `LocationInfo` elements can be present because one location may

1075

# indicate the location of the scene in the image, and another location

1076

# may indicate the location of the place where the image was taken.

1077

# Location information is usually present for landmarks.

1078

{ # Detected entity location information.

1079

"latLng": { # An object representing a latitude/longitude pair. This is expressed as a pair # lat/long location coordinates.

1080

# of doubles representing degrees latitude and degrees longitude. Unless

1081

# specified otherwise, this must conform to the

1082

# <a href="http://www.unoosa.org/pdf/icg/2012/template/WGS_84.pdf">WGS84

1083

# standard</a>. Values must be within normalized ranges.

1084

"latitude": 3.14, # The latitude in degrees. It must be in the range [-90.0, +90.0].

1085

"longitude": 3.14, # The longitude in degrees. It must be in the range [-180.0, +180.0].

},

},

],

"mid": "A String", # Opaque entity ID. Some IDs may be available in

1090

# [Google Knowledge Graph Search

1091

# API](https://developers.google.com/knowledge-graph/).

1092

"confidence": 3.14, # **Deprecated. Use `score` instead.**

1093

# The accuracy of the entity detection in an image.

1094

# For example, for an image in which the "Eiffel Tower" entity is detected,

1095

# this field represents the confidence that there is a tower in the query

1096

# image. Range [0, 1].

1097

"locale": "A String", # The language code for the locale in which the entity textual

1098

# `description` is expressed.

1099

"boundingPoly": { # A bounding polygon for the detected image annotation. # Image region to which this entity belongs. Not produced

1100

# for `LABEL_DETECTION` features.

1101

"normalizedVertices": [ # The bounding polygon normalized vertices.

1102

{ # A vertex represents a 2D point in the image.

1103

# NOTE: the normalized vertex coordinates are relative to the original image

1104

# and range from 0 to 1.

1105

"y": 3.14, # Y coordinate.

1106

"x": 3.14, # X coordinate.

1107

},

1108

],

1109

"vertices": [ # The bounding polygon vertices.

1110

{ # A vertex represents a 2D point in the image.

1111

# NOTE: the vertex coordinates are in the same scale as the original image.

1112

"y": 42, # Y coordinate.

1113

"x": 42, # X coordinate.

},

],

},

"description": "A String", # Entity textual description, expressed in its `locale` language.

1118

"topicality": 3.14, # The relevancy of the ICA (Image Content Annotation) label to the

1119

# image. For example, the relevancy of "tower" is likely higher to an image

1120

# containing the detected "Eiffel Tower" than to an image containing a

1121

# detected distant towering building, even though the confidence that

1122

# there is a tower in each image may be the same. Range [0, 1].

1123

},

1124

],

1125

"imagePropertiesAnnotation": { # Stores image properties, such as dominant colors. # If present, image properties were extracted successfully.

1126

"dominantColors": { # Set of dominant colors and their corresponding scores. # If present, dominant colors completed successfully.

1127

"colors": [ # RGB color values with their score and pixel fraction.

1128

{ # Color information consists of RGB channels, score, and the fraction of

1129

# the image that the color occupies in the image.

1130

"pixelFraction": 3.14, # The fraction of pixels the color occupies in the image.

1131

# Value in range [0, 1].

1132

"color": { # Represents a color in the RGBA color space. This representation is designed # RGB components of the color.

1133

# for simplicity of conversion to/from color representations in various

1134

# languages over compactness; for example, the fields of this representation

1135

# can be trivially provided to the constructor of "java.awt.Color" in Java; it

1136

# can also be trivially provided to UIColor's "+colorWithRed:green:blue:alpha"

1137

# method in iOS; and, with just a little work, it can be easily formatted into

1138

# a CSS "rgba()" string in JavaScript, as well.

1139

#

1140

# Note: this proto does not carry information about the absolute color space

1141

# that should be used to interpret the RGB value (e.g. sRGB, Adobe RGB,

1142

# DCI-P3, BT.2020, etc.). By default, applications SHOULD assume the sRGB color

# space.

#

# Example (Java):

#

# import com.google.type.Color;

1148

#

1149

# // ...

1150

# public static java.awt.Color fromProto(Color protocolor) {

1151

# float alpha = protocolor.hasAlpha()

1152

# ? protocolor.getAlpha().getValue()

1153

# : 1.0;

1154

#

1155

# return new java.awt.Color(

1156

# protocolor.getRed(),

1157

# protocolor.getGreen(),

1158

# protocolor.getBlue(),

# alpha);

# }

#

# public static Color toProto(java.awt.Color color) {

1163

# float red = (float) color.getRed();

1164

# float green = (float) color.getGreen();

1165

# float blue = (float) color.getBlue();

1166

# float denominator = 255.0;

1167

# Color.Builder resultBuilder =

1168

# Color

1169

# .newBuilder()

1170

# .setRed(red / denominator)

1171

# .setGreen(green / denominator)

1172

# .setBlue(blue / denominator);

1173

# int alpha = color.getAlpha();

1174

# if (alpha != 255) {

# result.setAlpha(

# FloatValue

# .newBuilder()

# .setValue(((float) alpha) / denominator)

1179

# .build());

1180

# }

1181

# return resultBuilder.build();

# }

# // ...

#

# Example (iOS / Obj-C):

1186

#

1187

# // ...

1188

# static UIColor* fromProto(Color* protocolor) {

1189

# float red = [protocolor red];

1190

# float green = [protocolor green];

1191

# float blue = [protocolor blue];

1192

# FloatValue* alpha_wrapper = [protocolor alpha];

1193

# float alpha = 1.0;

1194

# if (alpha_wrapper != nil) {

1195

# alpha = [alpha_wrapper value];

1196

# }

1197

# return [UIColor colorWithRed:red green:green blue:blue alpha:alpha];

1198

# }

1199

#

1200

# static Color* toProto(UIColor* color) {

1201

# CGFloat red, green, blue, alpha;

1202

# if (![color getRed:&red green:&green blue:&blue alpha:&alpha]) {

1203

# return nil;

1204

# }

1205

# Color* result = [[Color alloc] init];

1206

# [result setRed:red];

1207

# [result setGreen:green];

1208

# [result setBlue:blue];

1209

# if (alpha <= 0.9999) {

1210

# [result setAlpha:floatWrapperWithValue(alpha)];

1211

# }

1212

# [result autorelease];

# return result;

# }

# // ...

#

# Example (JavaScript):

#

# // ...

#

# var protoToCssColor = function(rgb_color) {

1222

# var redFrac = rgb_color.red || 0.0;

1223

# var greenFrac = rgb_color.green || 0.0;

1224

# var blueFrac = rgb_color.blue || 0.0;

1225

# var red = Math.floor(redFrac * 255);

1226

# var green = Math.floor(greenFrac * 255);

1227

# var blue = Math.floor(blueFrac * 255);

1228

#

1229

# if (!('alpha' in rgb_color)) {

1230

# return rgbToCssColor_(red, green, blue);

1231

# }

1232

#

1233

# var alphaFrac = rgb_color.alpha.value || 0.0;

1234

# var rgbParams = [red, green, blue].join(',');

1235

# return ['rgba(', rgbParams, ',', alphaFrac, ')'].join('');

1236

# };

1237

#

1238

# var rgbToCssColor_ = function(red, green, blue) {

1239

# var rgbNumber = new Number((red << 16) | (green << 8) | blue);

1240

# var hexString = rgbNumber.toString(16);

1241

# var missingZeros = 6 - hexString.length;

1242

# var resultBuilder = ['#'];

1243

# for (var i = 0; i < missingZeros; i++) {

1244

# resultBuilder.push('0');

1245

# }

1246

# resultBuilder.push(hexString);

1247

# return resultBuilder.join('');

# };

#

# // ...

"red": 3.14, # The amount of red in the color as a value in the interval [0, 1].

1252

"green": 3.14, # The amount of green in the color as a value in the interval [0, 1].

1253

"blue": 3.14, # The amount of blue in the color as a value in the interval [0, 1].

1254

"alpha": 3.14, # The fraction of this color that should be applied to the pixel. That is,

1255

# the final pixel color is defined by the equation:

1256

#

1257

# pixel color = alpha * (this color) + (1.0 - alpha) * (background color)

1258

#

1259

# This means that a value of 1.0 corresponds to a solid color, whereas

1260

# a value of 0.0 corresponds to a completely transparent color. This

1261

# uses a wrapper message rather than a simple float scalar so that it is

1262

# possible to distinguish between a default value and the value being unset.

1263

# If omitted, this color object is to be rendered as a solid color

1264

# (as if the alpha value had been explicitly given with a value of 1.0).

1265

},

1266

"score": 3.14, # Image-specific score for this color. Value in range [0, 1].

},

],

},

},

},

],

}</pre>

</div>

<code class="details" id="asyncBatchAnnotate">asyncBatchAnnotate(parent, body=None, x__xgafv=None)</code>

1278

<pre>Run asynchronous image detection and annotation for a list of images.

1279

1280

Progress and results can be retrieved through the

1281

`google.longrunning.Operations` interface.

1282

`Operation.metadata` contains `OperationMetadata` (metadata).

1283

`Operation.response` contains `AsyncBatchAnnotateImagesResponse` (results).

1284

1285

This service will write image annotation outputs to json files in customer

1286

GCS bucket, each json file containing BatchAnnotateImagesResponse proto.

1287

1288

Args:

1289

parent: string, Optional. Target project and location to make a call.

1290

1291

Format: `projects/{project-id}/locations/{location-id}`.

1292

1293

If no parent is specified, a region will be chosen automatically.

1294

1295

Supported location-ids:

1296

`us`: USA country only,

1297

`asia`: East asia areas, like Japan, Taiwan,

1298

`eu`: The European Union.

1299

1300

Example: `projects/project-A/locations/eu`. (required)

1301

body: object, The request body.

1302

The object takes the form of:

1303

1304

{ # Request for async image annotation for a list of images.

1305

"parent": "A String", # Optional. Target project and location to make a call.

1306

#

1307

# Format: `projects/{project-id}/locations/{location-id}`.

1308

#

1309

# If no parent is specified, a region will be chosen automatically.

1310

#

1311

# Supported location-ids:

1312

# `us`: USA country only,

1313

# `asia`: East asia areas, like Japan, Taiwan,

1314

# `eu`: The European Union.

1315

#

1316

# Example: `projects/project-A/locations/eu`.

1317

"outputConfig": { # The desired output location and metadata. # Required. The desired output location and metadata (e.g. format).

1318

"gcsDestination": { # The Google Cloud Storage location where the output will be written to. # The Google Cloud Storage location to write the output(s) to.

1319

"uri": "A String", # Google Cloud Storage URI prefix where the results will be stored. Results

1320

# will be in JSON format and preceded by its corresponding input URI prefix.

1321

# This field can either represent a gcs file prefix or gcs directory. In

1322

# either case, the uri should be unique because in order to get all of the

1323

# 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

1329

# will be created in gs://bucket-name/here/ and the names of the

1330

# output files will begin with "filenameprefix".

1331

#

1332

# * Directory Prefix: gs://bucket-name/some/location/ The output files

1333

# will be created in gs://bucket-name/some/location/ and the names of the

1334

# output files could be anything because there was no filename prefix

1335

# specified.

1336

#

1337

# If multiple outputs, each response is still AnnotateFileResponse, each of

1338

# which contains some subset of the full list of AnnotateImageResponse.

1339

# Multiple outputs can happen if, for example, the output JSON is too large

1340

# and overflows into multiple sharded files.

1341

},

1342

"batchSize": 42, # The max number of response protos to put into each output JSON file on

1343

# Google Cloud Storage.

1344

# The valid range is [1, 100]. If not specified, the default value is 20.

1345

#

1346

# For example, for one pdf file with 100 pages, 100 response protos will

1347

# be generated. If `batch_size` = 20, then 5 json files each

1348

# containing 20 response protos will be written under the prefix

1349

# `gcs_destination`.`uri`.

1350

#

1351

# Currently, batch_size only applies to GcsDestination, with potential future

1352

# support for other output configurations.

1353

},

1354

"requests": [ # Required. Individual image annotation requests for this batch.

1355

{ # Request for performing Google Cloud Vision API tasks over a user-provided

1356

# image, with user-requested features, and with context information.

1357

"image": { # Client image to perform Google Cloud Vision API tasks over. # The image to be processed.

1358

"content": "A String", # Image content, represented as a stream of bytes.

1359

# Note: As with all `bytes` fields, protobuffers use a pure binary

1360

# representation, whereas JSON representations use base64.

1361

"source": { # External image source (Google Cloud Storage or web URL image location). # Google Cloud Storage image location, or publicly-accessible image

1362

# URL. If both `content` and `source` are provided for an image, `content`

1363

# takes precedence and is used to perform the image annotation request.

1364

"imageUri": "A String", # The URI of the source image. Can be either:

1365

#

1366

# 1. A Google Cloud Storage URI of the form

1367

# `gs://bucket_name/object_name`. Object versioning is not supported. See

1368

# [Google Cloud Storage Request

1369

# URIs](https://cloud.google.com/storage/docs/reference-uris) for more

1370

# info.

1371

#

1372

# 2. A publicly-accessible image HTTP/HTTPS URL. When fetching images from

1373

# HTTP/HTTPS URLs, Google cannot guarantee that the request will be

1374

# completed. Your request may fail if the specified host denies the

1375

# request (e.g. due to request throttling or DOS prevention), or if Google

1376

# throttles requests to the site for abuse prevention. You should not

1377

# depend on externally-hosted images for production applications.

1378

#

1379

# When both `gcs_image_uri` and `image_uri` are specified, `image_uri` takes

1380

# precedence.

1381

"gcsImageUri": "A String", # **Use `image_uri` instead.**

1382

#

1383

# The Google Cloud Storage URI of the form

1384

# `gs://bucket_name/object_name`. Object versioning is not supported. See

1385

# [Google Cloud Storage Request

1386

# URIs](https://cloud.google.com/storage/docs/reference-uris) for more info.

1387

},

1388

},

1389

"features": [ # Requested features.

1390

{ # The type of Google Cloud Vision API detection to perform, and the maximum

1391

# number of results to return for that type. Multiple `Feature` objects can

1392

# be specified in the `features` list.

1393

"type": "A String", # The feature type.

1394

"maxResults": 42, # Maximum number of results of this type. Does not apply to

1395

# `TEXT_DETECTION`, `DOCUMENT_TEXT_DETECTION`, or `CROP_HINTS`.

1396

"model": "A String", # Model to use for the feature.

1397

# Supported values: "builtin/stable" (the default if unset) and

# "builtin/latest".

},

],

"imageContext": { # Image context and/or feature-specific parameters. # Additional context that may accompany the image.

1402

"languageHints": [ # List of languages to use for TEXT_DETECTION. In most cases, an empty value

1403

# yields the best results since it enables automatic language detection. For

1404

# languages based on the Latin alphabet, setting `language_hints` is not

1405

# needed. In rare cases, when the language of the text in the image is known,

1406

# setting a hint will help get better results (although it will be a

1407

# significant hindrance if the hint is wrong). Text detection returns an

1408

# error if one or more of the specified languages is not one of the

1409

# [supported languages](https://cloud.google.com/vision/docs/languages).

1410

"A String",

1411

],

1412

"webDetectionParams": { # Parameters for web detection request. # Parameters for web detection.

1413

"includeGeoResults": True or False, # Whether to include results derived from the geo information in the image.

1414

},

1415

"latLongRect": { # Rectangle determined by min and max `LatLng` pairs. # Not used.

1416

"minLatLng": { # An object representing a latitude/longitude pair. This is expressed as a pair # Min lat/long pair.

1417

# of doubles representing degrees latitude and degrees longitude. Unless

1418

# specified otherwise, this must conform to the

1419

# <a href="http://www.unoosa.org/pdf/icg/2012/template/WGS_84.pdf">WGS84

1420

# standard</a>. Values must be within normalized ranges.

1421

"latitude": 3.14, # The latitude in degrees. It must be in the range [-90.0, +90.0].

1422

"longitude": 3.14, # The longitude in degrees. It must be in the range [-180.0, +180.0].

1423

},

1424

"maxLatLng": { # An object representing a latitude/longitude pair. This is expressed as a pair # Max lat/long pair.

1425

# of doubles representing degrees latitude and degrees longitude. Unless

1426

# specified otherwise, this must conform to the

1427

# <a href="http://www.unoosa.org/pdf/icg/2012/template/WGS_84.pdf">WGS84

1428

# standard</a>. Values must be within normalized ranges.

1429

"latitude": 3.14, # The latitude in degrees. It must be in the range [-90.0, +90.0].

1430

"longitude": 3.14, # The longitude in degrees. It must be in the range [-180.0, +180.0].

1431

},

1432

},

1433

"cropHintsParams": { # Parameters for crop hints annotation request. # Parameters for crop hints annotation request.

1434

"aspectRatios": [ # Aspect ratios in floats, representing the ratio of the width to the height

1435

# of the image. For example, if the desired aspect ratio is 4/3, the

1436

# corresponding float value should be 1.33333. If not specified, the

1437

# best possible crop is returned. The number of provided aspect ratios is

1438

# limited to a maximum of 16; any aspect ratios provided after the 16th are

# ignored.

3.14,

],

},

"productSearchParams": { # Parameters for a product search request. # Parameters for product search.

1444

"productSet": "A String", # The resource name of a ProductSet to be searched for similar images.

1445

#

1446

# Format is:

1447

# `projects/PROJECT_ID/locations/LOC_ID/productSets/PRODUCT_SET_ID`.

1448

"boundingPoly": { # A bounding polygon for the detected image annotation. # The bounding polygon around the area of interest in the image.

1449

# If it is not specified, system discretion will be applied.

1450

"normalizedVertices": [ # The bounding polygon normalized vertices.

1451

{ # A vertex represents a 2D point in the image.

1452

# NOTE: the normalized vertex coordinates are relative to the original image

1453

# and range from 0 to 1.

1454

"y": 3.14, # Y coordinate.

1455

"x": 3.14, # X coordinate.

1456

},

1457

],

1458

"vertices": [ # The bounding polygon vertices.

1459

{ # A vertex represents a 2D point in the image.

1460

# NOTE: the vertex coordinates are in the same scale as the original image.

1461

"y": 42, # Y coordinate.

1462

"x": 42, # X coordinate.

},

],

},

"productCategories": [ # The list of product categories to search in. Currently, we only consider

1467

# the first category, and either "homegoods-v2", "apparel-v2", "toys-v2",

1468

# "packagedgoods-v1", or "general-v1" should be specified. The legacy

1469

# categories "homegoods", "apparel", and "toys" are still supported but will

1470

# be deprecated. For new products, please use "homegoods-v2", "apparel-v2",

1471

# or "toys-v2" for better product search accuracy. It is recommended to

1472

# migrate existing products to these categories as well.

1473

"A String",

1474

],

1475

"filter": "A String", # The filtering expression. This can be used to restrict search results based

1476

# on Product labels. We currently support an AND of OR of key-value

1477

# expressions, where each expression within an OR must have the same key. An

1478

# '=' should be used to connect the key and value.

1479

#

1480

# For example, "(color = red OR color = blue) AND brand = Google" is

1481

# acceptable, but "(color = red OR brand = Google)" is not acceptable.

1482

# "color: red" is not acceptable because it uses a ':' instead of an '='.

},

},

},

],

}

x__xgafv: string, V1 error format.

Allowed values

1 - v1 error format

2 - v2 error format

Returns:

An object of the form:

1496

1497

{ # This resource represents a long-running operation that is the result of a

1498

# network API call.

1499

"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.

1500

# different programming environments, including REST APIs and RPC APIs. It is

1501

# used by [gRPC](https://github.com/grpc). Each `Status` message contains

1502

# three pieces of data: error code, error message, and error details.

1503

#

1504

# You can find out more about this error model and how to work with it in the

1505

# [API Design Guide](https://cloud.google.com/apis/design/errors).

1506

"code": 42, # The status code, which should be an enum value of google.rpc.Code.

1507

"message": "A String", # A developer-facing error message, which should be in English. Any

1508

# user-facing error message should be localized and sent in the

1509

# google.rpc.Status.details field, or localized by the client.

1510

"details": [ # A list of messages that carry the error details. There is a common set of

1511

# message types for APIs to use.

1512

{

1513

"a_key": "", # Properties of the object. Contains field @type with type URL.

},

],

},

"metadata": { # Service-specific metadata associated with the operation. It typically

1518

# contains progress information and common metadata such as create time.

1519

# Some services might not provide such metadata. Any method that returns a

1520

# long-running operation should document the metadata type, if any.

1521

"a_key": "", # Properties of the object. Contains field @type with type URL.

1522

},

1523

"done": True or False, # If the value is `false`, it means the operation is still in progress.

1524

# If `true`, the operation is completed, and either `error` or `response` is

1525

# available.

1526

"response": { # The normal response of the operation in case of success. If the original

1527

# method returns no data on success, such as `Delete`, the response is

1528

# `google.protobuf.Empty`. If the original method is standard

1529

# `Get`/`Create`/`Update`, the response should be the resource. For other

1530

# methods, the response should have the type `XxxResponse`, where `Xxx`

1531

# is the original method name. For example, if the original method name

1532

# is `TakeSnapshot()`, the inferred response type is

1533

# `TakeSnapshotResponse`.

1534

"a_key": "", # Properties of the object. Contains field @type with type URL.

1535

},

1536

"name": "A String", # The server-assigned name, which is only unique within the same service that

1537

# originally returns it. If you use the default HTTP mapping, the

1538

# `name` should be a resource name ending with `operations/{unique_id}`.

}</pre>

</div>

</body></html>