Class: Google::Cloud::VisionAI::V1::CustomProcessorSourceInfo

Inherits:
Object
  • Object
show all
Extended by:
Protobuf::MessageExts::ClassMethods
Includes:
Protobuf::MessageExts
Defined in:
proto_docs/google/cloud/visionai/v1/platform.rb

Overview

Describes the source info for a custom processor.

Defined Under Namespace

Modules: SourceType Classes: AdditionalInfoEntry, ModelSchema, ProductRecognizerArtifact

Instance Attribute Summary collapse

Instance Attribute Details

#additional_info ⇒ ::Google::Protobuf::Map{::String => ::String} (readonly)

Returns Output only. Additional info related to the imported custom processor. Data is filled in by app platform during the processor creation.

Returns:

  • (::Google::Protobuf::Map{::String => ::String}) —

    Output only. Additional info related to the imported custom processor. Data is filled in by app platform during the processor creation.



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# File 'proto_docs/google/cloud/visionai/v1/platform.rb', line 1489

class CustomProcessorSourceInfo
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods

  # Message describes product recognizer artifact.
  # @!attribute [rw] retail_product_recognition_index
  #   @return [::String]
  #     Required. Resource name of RetailProductRecognitionIndex.
  #     Format is
  #     'projects/*/locations/*/retailCatalogs/*/retailProductRecognitionIndexes/*'
  # @!attribute [rw] vertex_model
  #   @return [::String]
  #     Optional. The resource name of embedding model hosted in Vertex AI
  #     Platform.
  class ProductRecognizerArtifact
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # The schema is defined as an OpenAPI 3.0.2 [Schema
  # Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject).
  # @!attribute [rw] instances_schema
  #   @return [::Google::Cloud::VisionAI::V1::GcsSource]
  #     Cloud Storage location to a YAML file that defines the format of a single
  #     instance used in prediction and explanation requests.
  # @!attribute [rw] parameters_schema
  #   @return [::Google::Cloud::VisionAI::V1::GcsSource]
  #     Cloud Storage location to a YAML file that defines the prediction and
  #     explanation parameters.
  # @!attribute [rw] predictions_schema
  #   @return [::Google::Cloud::VisionAI::V1::GcsSource]
  #     Cloud Storage location to a YAML file that defines the format of a single
  #     prediction or explanation.
  class ModelSchema
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # @!attribute [rw] key
  #   @return [::String]
  # @!attribute [rw] value
  #   @return [::String]
  class AdditionalInfoEntry
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Source type of the imported custom processor.
  module SourceType
    # Source type unspecified.
    SOURCE_TYPE_UNSPECIFIED = 0

    # Custom processors coming from Vertex AutoML product.
    VERTEX_AUTOML = 1

    # Custom processors coming from general custom models from Vertex.
    VERTEX_CUSTOM = 2

    # Source for Product Recognizer.
    PRODUCT_RECOGNIZER = 3
  end
end

#model_schema ⇒ ::Google::Cloud::VisionAI::V1::CustomProcessorSourceInfo::ModelSchema

Returns Model schema files which specifies the signature of the model. For VERTEX_CUSTOM models, instances schema is required. If instances schema is not specified during the processor creation, VisionAI Platform will try to get it from Vertex, if it doesn't exist, the creation will fail.

Returns:

  • (::Google::Cloud::VisionAI::V1::CustomProcessorSourceInfo::ModelSchema) —

    Model schema files which specifies the signature of the model. For VERTEX_CUSTOM models, instances schema is required. If instances schema is not specified during the processor creation, VisionAI Platform will try to get it from Vertex, if it doesn't exist, the creation will fail.



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# File 'proto_docs/google/cloud/visionai/v1/platform.rb', line 1489

class CustomProcessorSourceInfo
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods

  # Message describes product recognizer artifact.
  # @!attribute [rw] retail_product_recognition_index
  #   @return [::String]
  #     Required. Resource name of RetailProductRecognitionIndex.
  #     Format is
  #     'projects/*/locations/*/retailCatalogs/*/retailProductRecognitionIndexes/*'
  # @!attribute [rw] vertex_model
  #   @return [::String]
  #     Optional. The resource name of embedding model hosted in Vertex AI
  #     Platform.
  class ProductRecognizerArtifact
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # The schema is defined as an OpenAPI 3.0.2 [Schema
  # Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject).
  # @!attribute [rw] instances_schema
  #   @return [::Google::Cloud::VisionAI::V1::GcsSource]
  #     Cloud Storage location to a YAML file that defines the format of a single
  #     instance used in prediction and explanation requests.
  # @!attribute [rw] parameters_schema
  #   @return [::Google::Cloud::VisionAI::V1::GcsSource]
  #     Cloud Storage location to a YAML file that defines the prediction and
  #     explanation parameters.
  # @!attribute [rw] predictions_schema
  #   @return [::Google::Cloud::VisionAI::V1::GcsSource]
  #     Cloud Storage location to a YAML file that defines the format of a single
  #     prediction or explanation.
  class ModelSchema
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # @!attribute [rw] key
  #   @return [::String]
  # @!attribute [rw] value
  #   @return [::String]
  class AdditionalInfoEntry
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Source type of the imported custom processor.
  module SourceType
    # Source type unspecified.
    SOURCE_TYPE_UNSPECIFIED = 0

    # Custom processors coming from Vertex AutoML product.
    VERTEX_AUTOML = 1

    # Custom processors coming from general custom models from Vertex.
    VERTEX_CUSTOM = 2

    # Source for Product Recognizer.
    PRODUCT_RECOGNIZER = 3
  end
end

#product_recognizer_artifact ⇒ ::Google::Cloud::VisionAI::V1::CustomProcessorSourceInfo::ProductRecognizerArtifact

Returns Artifact for product recognizer.

Returns:



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# File 'proto_docs/google/cloud/visionai/v1/platform.rb', line 1489

class CustomProcessorSourceInfo
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods

  # Message describes product recognizer artifact.
  # @!attribute [rw] retail_product_recognition_index
  #   @return [::String]
  #     Required. Resource name of RetailProductRecognitionIndex.
  #     Format is
  #     'projects/*/locations/*/retailCatalogs/*/retailProductRecognitionIndexes/*'
  # @!attribute [rw] vertex_model
  #   @return [::String]
  #     Optional. The resource name of embedding model hosted in Vertex AI
  #     Platform.
  class ProductRecognizerArtifact
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # The schema is defined as an OpenAPI 3.0.2 [Schema
  # Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject).
  # @!attribute [rw] instances_schema
  #   @return [::Google::Cloud::VisionAI::V1::GcsSource]
  #     Cloud Storage location to a YAML file that defines the format of a single
  #     instance used in prediction and explanation requests.
  # @!attribute [rw] parameters_schema
  #   @return [::Google::Cloud::VisionAI::V1::GcsSource]
  #     Cloud Storage location to a YAML file that defines the prediction and
  #     explanation parameters.
  # @!attribute [rw] predictions_schema
  #   @return [::Google::Cloud::VisionAI::V1::GcsSource]
  #     Cloud Storage location to a YAML file that defines the format of a single
  #     prediction or explanation.
  class ModelSchema
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # @!attribute [rw] key
  #   @return [::String]
  # @!attribute [rw] value
  #   @return [::String]
  class AdditionalInfoEntry
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Source type of the imported custom processor.
  module SourceType
    # Source type unspecified.
    SOURCE_TYPE_UNSPECIFIED = 0

    # Custom processors coming from Vertex AutoML product.
    VERTEX_AUTOML = 1

    # Custom processors coming from general custom models from Vertex.
    VERTEX_CUSTOM = 2

    # Source for Product Recognizer.
    PRODUCT_RECOGNIZER = 3
  end
end

#source_type ⇒ ::Google::Cloud::VisionAI::V1::CustomProcessorSourceInfo::SourceType

Returns The original product which holds the custom processor's functionality.

Returns:



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# File 'proto_docs/google/cloud/visionai/v1/platform.rb', line 1489

class CustomProcessorSourceInfo
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods

  # Message describes product recognizer artifact.
  # @!attribute [rw] retail_product_recognition_index
  #   @return [::String]
  #     Required. Resource name of RetailProductRecognitionIndex.
  #     Format is
  #     'projects/*/locations/*/retailCatalogs/*/retailProductRecognitionIndexes/*'
  # @!attribute [rw] vertex_model
  #   @return [::String]
  #     Optional. The resource name of embedding model hosted in Vertex AI
  #     Platform.
  class ProductRecognizerArtifact
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # The schema is defined as an OpenAPI 3.0.2 [Schema
  # Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject).
  # @!attribute [rw] instances_schema
  #   @return [::Google::Cloud::VisionAI::V1::GcsSource]
  #     Cloud Storage location to a YAML file that defines the format of a single
  #     instance used in prediction and explanation requests.
  # @!attribute [rw] parameters_schema
  #   @return [::Google::Cloud::VisionAI::V1::GcsSource]
  #     Cloud Storage location to a YAML file that defines the prediction and
  #     explanation parameters.
  # @!attribute [rw] predictions_schema
  #   @return [::Google::Cloud::VisionAI::V1::GcsSource]
  #     Cloud Storage location to a YAML file that defines the format of a single
  #     prediction or explanation.
  class ModelSchema
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # @!attribute [rw] key
  #   @return [::String]
  # @!attribute [rw] value
  #   @return [::String]
  class AdditionalInfoEntry
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Source type of the imported custom processor.
  module SourceType
    # Source type unspecified.
    SOURCE_TYPE_UNSPECIFIED = 0

    # Custom processors coming from Vertex AutoML product.
    VERTEX_AUTOML = 1

    # Custom processors coming from general custom models from Vertex.
    VERTEX_CUSTOM = 2

    # Source for Product Recognizer.
    PRODUCT_RECOGNIZER = 3
  end
end

#vertex_model ⇒ ::String

Returns The resource name original model hosted in the vertex AI platform.

Returns:

  • (::String) —

    The resource name original model hosted in the vertex AI platform.



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# File 'proto_docs/google/cloud/visionai/v1/platform.rb', line 1489

class CustomProcessorSourceInfo
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods

  # Message describes product recognizer artifact.
  # @!attribute [rw] retail_product_recognition_index
  #   @return [::String]
  #     Required. Resource name of RetailProductRecognitionIndex.
  #     Format is
  #     'projects/*/locations/*/retailCatalogs/*/retailProductRecognitionIndexes/*'
  # @!attribute [rw] vertex_model
  #   @return [::String]
  #     Optional. The resource name of embedding model hosted in Vertex AI
  #     Platform.
  class ProductRecognizerArtifact
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # The schema is defined as an OpenAPI 3.0.2 [Schema
  # Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject).
  # @!attribute [rw] instances_schema
  #   @return [::Google::Cloud::VisionAI::V1::GcsSource]
  #     Cloud Storage location to a YAML file that defines the format of a single
  #     instance used in prediction and explanation requests.
  # @!attribute [rw] parameters_schema
  #   @return [::Google::Cloud::VisionAI::V1::GcsSource]
  #     Cloud Storage location to a YAML file that defines the prediction and
  #     explanation parameters.
  # @!attribute [rw] predictions_schema
  #   @return [::Google::Cloud::VisionAI::V1::GcsSource]
  #     Cloud Storage location to a YAML file that defines the format of a single
  #     prediction or explanation.
  class ModelSchema
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # @!attribute [rw] key
  #   @return [::String]
  # @!attribute [rw] value
  #   @return [::String]
  class AdditionalInfoEntry
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Source type of the imported custom processor.
  module SourceType
    # Source type unspecified.
    SOURCE_TYPE_UNSPECIFIED = 0

    # Custom processors coming from Vertex AutoML product.
    VERTEX_AUTOML = 1

    # Custom processors coming from general custom models from Vertex.
    VERTEX_CUSTOM = 2

    # Source for Product Recognizer.
    PRODUCT_RECOGNIZER = 3
  end
end