Reference documentation and code samples for the Cloud AutoML V1 API class Google::Cloud::AutoML::V1::PredictionService::Client.
Client for the PredictionService service.
AutoML Prediction API.
On any input that is documented to expect a string parameter in snake_case or dash-case, either of those cases is accepted.
Inherits
- Object
Methods
.configure
def self.configure() { |config| ... } -> Client::Configuration
Configure the PredictionService Client class.
See Configuration for a description of the configuration fields.
- (config) — Configure the Client client.
- config (Client::Configuration)
# Modify the configuration for all PredictionService clients ::Google::Cloud::AutoML::V1::PredictionService::Client.configure do |config| config.timeout = 10.0 end
#batch_predict
def batch_predict(request, options = nil) -> ::Gapic::Operation
def batch_predict(name: nil, input_config: nil, output_config: nil, params: nil) -> ::Gapic::Operation
Perform a batch prediction. Unlike the online Predict, batch prediction result won't be immediately available in the response. Instead, a long running operation object is returned. User can poll the operation result via GetOperation method. Once the operation is done, BatchPredictResult is returned in the response field. Available for following ML scenarios:
- AutoML Vision Classification
- AutoML Vision Object Detection
- AutoML Video Intelligence Classification
- AutoML Video Intelligence Object Tracking * AutoML Natural Language Classification
- AutoML Natural Language Entity Extraction
- AutoML Natural Language Sentiment Analysis
- AutoML Tables
def batch_predict(request, options = nil) -> ::Gapic::Operation
batch_predict
via a request object, either of type
BatchPredictRequest or an equivalent Hash.
- request (::Google::Cloud::AutoML::V1::BatchPredictRequest, ::Hash) — A request object representing the call parameters. Required. To specify no parameters, or to keep all the default parameter values, pass an empty Hash.
- options (::Gapic::CallOptions, ::Hash) — Overrides the default settings for this call, e.g, timeout, retries, etc. Optional.
def batch_predict(name: nil, input_config: nil, output_config: nil, params: nil) -> ::Gapic::Operation
batch_predict
via keyword arguments. Note that at
least one keyword argument is required. To specify no parameters, or to keep all
the default parameter values, pass an empty Hash as a request object (see above).
- name (::String) — Required. Name of the model requested to serve the batch prediction.
- input_config (::Google::Cloud::AutoML::V1::BatchPredictInputConfig, ::Hash) — Required. The input configuration for batch prediction.
- output_config (::Google::Cloud::AutoML::V1::BatchPredictOutputConfig, ::Hash) — Required. The Configuration specifying where output predictions should be written.
-
params (::Hash{::String => ::String}) — Additional domain-specific parameters for the predictions, any string must
be up to 25000 characters long.
AutoML Natural Language Classification
score_threshold
: (float) A value from 0.0 to 1.0. When the model makes predictions for a text snippet, it will only produce results that have at least this confidence score. The default is 0.5.AutoML Vision Classification
score_threshold
: (float) A value from 0.0 to 1.0. When the model makes predictions for an image, it will only produce results that have at least this confidence score. The default is 0.5.AutoML Vision Object Detection
score_threshold
: (float) When Model detects objects on the image, it will only produce bounding boxes which have at least this confidence score. Value in 0 to 1 range, default is 0.5.max_bounding_box_count
: (int64) The maximum number of bounding boxes returned per image. The default is 100, the number of bounding boxes returned might be limited by the server. AutoML Video Intelligence Classificationscore_threshold
: (float) A value from 0.0 to 1.0. When the model makes predictions for a video, it will only produce results that have at least this confidence score. The default is 0.5.segment_classification
: (boolean) Set to true to request segment-level classification. AutoML Video Intelligence returns labels and their confidence scores for the entire segment of the video that user specified in the request configuration. The default is true.shot_classification
: (boolean) Set to true to request shot-level classification. AutoML Video Intelligence determines the boundaries for each camera shot in the entire segment of the video that user specified in the request configuration. AutoML Video Intelligence then returns labels and their confidence scores for each detected shot, along with the start and end time of the shot. The default is false.WARNING: Model evaluation is not done for this classification type, the quality of it depends on training data, but there are no metrics provided to describe that quality.
1s_interval_classification
: (boolean) Set to true to request classification for a video at one-second intervals. AutoML Video Intelligence returns labels and their confidence scores for each second of the entire segment of the video that user specified in the request configuration. The default is false.WARNING: Model evaluation is not done for this classification type, the quality of it depends on training data, but there are no metrics provided to describe that quality.
AutoML Video Intelligence Object Tracking
score_threshold
: (float) When Model detects objects on video frames, it will only produce bounding boxes which have at least this confidence score. Value in 0 to 1 range, default is 0.5.max_bounding_box_count
: (int64) The maximum number of bounding boxes returned per image. The default is 100, the number of bounding boxes returned might be limited by the server.min_bounding_box_size
: (float) Only bounding boxes with shortest edge at least that long as a relative value of video frame size are returned. Value in 0 to 1 range. Default is 0.
- (response, operation) — Access the result along with the RPC operation
- response (::Gapic::Operation)
- operation (::GRPC::ActiveCall::Operation)
- (::Gapic::Operation)
- (::Google::Cloud::Error) — if the RPC is aborted.
Basic example
require "google/cloud/automl/v1" # Create a client object. The client can be reused for multiple calls. client = Google::Cloud::AutoML::V1::PredictionService::Client.new # Create a request. To set request fields, pass in keyword arguments. request = Google::Cloud::AutoML::V1::BatchPredictRequest.new # Call the batch_predict method. result = client.batch_predict request # The returned object is of type Gapic::Operation. You can use it to # check the status of an operation, cancel it, or wait for results. # Here is how to wait for a response. result.wait_until_done! timeout: 60 if result.response? p result.response else puts "No response received." end
#configure
def configure() { |config| ... } -> Client::Configuration
Configure the PredictionService Client instance.
The configuration is set to the derived mode, meaning that values can be changed, but structural changes (adding new fields, etc.) are not allowed. Structural changes should be made on Client.configure.
See Configuration for a description of the configuration fields.
- (config) — Configure the Client client.
- config (Client::Configuration)
#initialize
def initialize() { |config| ... } -> Client
Create a new PredictionService client object.
- (config) — Configure the PredictionService client.
- config (Client::Configuration)
- (Client) — a new instance of Client
# Create a client using the default configuration client = ::Google::Cloud::AutoML::V1::PredictionService::Client.new # Create a client using a custom configuration client = ::Google::Cloud::AutoML::V1::PredictionService::Client.new do |config| config.timeout = 10.0 end
#operations_client
def operations_client() -> ::Google::Cloud::AutoML::V1::PredictionService::Operations
Get the associated client for long-running operations.
#predict
def predict(request, options = nil) -> ::Google::Cloud::AutoML::V1::PredictResponse
def predict(name: nil, payload: nil, params: nil) -> ::Google::Cloud::AutoML::V1::PredictResponse
Perform an online prediction. The prediction result is directly returned in the response. Available for following ML scenarios, and their expected request payloads:
AutoML Vision Classification
- An image in .JPEG, .GIF or .PNG format, image_bytes up to 30MB.
AutoML Vision Object Detection
- An image in .JPEG, .GIF or .PNG format, image_bytes up to 30MB.
AutoML Natural Language Classification
- A TextSnippet up to 60,000 characters, UTF-8 encoded or a document in .PDF, .TIF or .TIFF format with size upto 2MB.
AutoML Natural Language Entity Extraction
- A TextSnippet up to 10,000 characters, UTF-8 NFC encoded or a document in .PDF, .TIF or .TIFF format with size upto 20MB.
AutoML Natural Language Sentiment Analysis
- A TextSnippet up to 60,000 characters, UTF-8 encoded or a document in .PDF, .TIF or .TIFF format with size upto 2MB.
AutoML Translation
- A TextSnippet up to 25,000 characters, UTF-8 encoded.
AutoML Tables
- A row with column values matching
the columns of the model, up to 5MB. Not available for FORECASTING
prediction_type
.
def predict(request, options = nil) -> ::Google::Cloud::AutoML::V1::PredictResponse
predict
via a request object, either of type
Google::Cloud::AutoML::V1::PredictRequest or an equivalent Hash.
- request (::Google::Cloud::AutoML::V1::PredictRequest, ::Hash) — A request object representing the call parameters. Required. To specify no parameters, or to keep all the default parameter values, pass an empty Hash.
- options (::Gapic::CallOptions, ::Hash) — Overrides the default settings for this call, e.g, timeout, retries, etc. Optional.
def predict(name: nil, payload: nil, params: nil) -> ::Google::Cloud::AutoML::V1::PredictResponse
predict
via keyword arguments. Note that at
least one keyword argument is required. To specify no parameters, or to keep all
the default parameter values, pass an empty Hash as a request object (see above).
- name (::String) — Required. Name of the model requested to serve the prediction.
- payload (::Google::Cloud::AutoML::V1::ExamplePayload, ::Hash) — Required. Payload to perform a prediction on. The payload must match the problem type that the model was trained to solve.
-
params (::Hash{::String => ::String}) — Additional domain-specific parameters, any string must be up to 25000
characters long.
AutoML Vision Classification
score_threshold
: (float) A value from 0.0 to 1.0. When the model makes predictions for an image, it will only produce results that have at least this confidence score. The default is 0.5.AutoML Vision Object Detection
score_threshold
: (float) When Model detects objects on the image, it will only produce bounding boxes which have at least this confidence score. Value in 0 to 1 range, default is 0.5.max_bounding_box_count
: (int64) The maximum number of bounding boxes returned. The default is 100. The number of returned bounding boxes might be limited by the server.AutoML Tables
feature_importance
: (boolean) Whether [feature_importance][google.cloud.automl.v1.TablesModelColumnInfo.feature_importance] is populated in the returned list of [TablesAnnotation][google.cloud.automl.v1.TablesAnnotation] objects. The default is false.
- (response, operation) — Access the result along with the RPC operation
- response (::Google::Cloud::AutoML::V1::PredictResponse)
- operation (::GRPC::ActiveCall::Operation)
- (::Google::Cloud::Error) — if the RPC is aborted.
Basic example
require "google/cloud/automl/v1" # Create a client object. The client can be reused for multiple calls. client = Google::Cloud::AutoML::V1::PredictionService::Client.new # Create a request. To set request fields, pass in keyword arguments. request = Google::Cloud::AutoML::V1::PredictRequest.new # Call the predict method. result = client.predict request # The returned object is of type Google::Cloud::AutoML::V1::PredictResponse. p result
#universe_domain
def universe_domain() -> String
The effective universe domain
- (String)