Class PredictionServiceClient (2.7.3)

PredictionServiceClient(*, credentials: Optional[google.auth.credentials.Credentials] = None, transport: Optional[Union[str, google.cloud.automl_v1beta1.services.prediction_service.transports.base.PredictionServiceTransport]] = None, client_options: Optional[google.api_core.client_options.ClientOptions] = None, client_info: google.api_core.gapic_v1.client_info.ClientInfo = <google.api_core.gapic_v1.client_info.ClientInfo object>)

AutoML Prediction API.

On any input that is documented to expect a string parameter in snake_case or kebab-case, either of those cases is accepted.

Properties

transport

Returns the transport used by the client instance.

Returns

Type	Description
`PredictionServiceTransport`	The transport used by the client instance.

Methods

PredictionServiceClient

PredictionServiceClient(*, credentials: Optional[google.auth.credentials.Credentials] = None, transport: Optional[Union[str, google.cloud.automl_v1beta1.services.prediction_service.transports.base.PredictionServiceTransport]] = None, client_options: Optional[google.api_core.client_options.ClientOptions] = None, client_info: google.api_core.gapic_v1.client_info.ClientInfo = <google.api_core.gapic_v1.client_info.ClientInfo object>)

Instantiates the prediction service client.

Parameters

Name	Description
`credentials`	`Optional[google.auth.credentials.Credentials]` The authorization credentials to attach to requests. These credentials identify the application to the service; if none are specified, the client will attempt to ascertain the credentials from the environment.
`transport`	`Union[str, PredictionServiceTransport]` The transport to use. If set to None, a transport is chosen automatically.
`client_options`	`google.api_core.client_options.ClientOptions` Custom options for the client. It won't take effect if a `transport` instance is provided. (1) The `api_endpoint` property can be used to override the default endpoint provided by the client. GOOGLE_API_USE_MTLS_ENDPOINT environment variable can also be used to override the endpoint: "always" (always use the default mTLS endpoint), "never" (always use the default regular endpoint) and "auto" (auto switch to the default mTLS endpoint if client certificate is present, this is the default value). However, the `api_endpoint` property takes precedence if provided. (2) If GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable is "true", then the `client_cert_source` property can be used to provide client certificate for mutual TLS transport. If not provided, the default SSL client certificate will be used if present. If GOOGLE_API_USE_CLIENT_CERTIFICATE is "false" or not set, no client certificate will be used.
`client_info`	`google.api_core.gapic_v1.client_info.ClientInfo` The client info used to send a user-agent string along with API requests. If `None`, then default info will be used. Generally, you only need to set this if you're developing your own client library.

Exceptions

Type	Description
`google.auth.exceptions.MutualTLSChannelError`	If mutual TLS transport creation failed for any reason.

exit

__exit__(type, value, traceback)

Releases underlying transport's resources.

batch_predict

batch_predict(request: Optional[Union[google.cloud.automl_v1beta1.types.prediction_service.BatchPredictRequest, dict]] = None, *, name: Optional[str] = None, input_config: Optional[google.cloud.automl_v1beta1.types.io.BatchPredictInputConfig] = None, output_config: Optional[google.cloud.automl_v1beta1.types.io.BatchPredictOutputConfig] = None, params: Optional[Mapping[str, str]] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Perform a batch prediction. Unlike the online xref_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][google.longrunning.Operations.GetOperation] method. Once the operation is done, xref_BatchPredictResult is returned in the response][google.longrunning.Operation.response] field. Available for following ML problems:

Image Classification
Image Object Detection
Video Classification
Video Object Tracking * Text Extraction
Tables

from google.cloud import automl_v1beta1

def sample_batch_predict():
    # Create a client
    client = automl_v1beta1.PredictionServiceClient()

    # Initialize request argument(s)
    request = automl_v1beta1.BatchPredictRequest(
        name="name_value",
    )

    # Make the request
    operation = client.batch_predict(request=request)

    print("Waiting for operation to complete...")

    response = operation.result()

    # Handle the response
    print(response)

Parameters

Name	Description
`request`	`Union[google.cloud.automl_v1beta1.types.BatchPredictRequest, dict]` The request object. Request message for PredictionService.BatchPredict.
`name`	`str` Required. Name of the model requested to serve the batch prediction. This corresponds to the `name` field on the `request` instance; if `request` is provided, this should not be set.
`input_config`	`google.cloud.automl_v1beta1.types.BatchPredictInputConfig` Required. The input configuration for batch prediction. This corresponds to the `input_config` field on the `request` instance; if `request` is provided, this should not be set.
`output_config`	`google.cloud.automl_v1beta1.types.BatchPredictOutputConfig` Required. The Configuration specifying where output predictions should be written. This corresponds to the `output_config` field on the `request` instance; if `request` is provided, this should not be set.
`params`	`Mapping[str, str]` Required. Additional domain-specific parameters for the predictions, any string must be up to 25000 characters long. - For Text 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. - For Image 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. - For Image 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) No more than this number of bounding boxes will be produced per image. Default is 100, the requested value may be limited by server. - For Video Classification : `score_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. 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. The default is "false". `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. 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. The default is "false". - For Tables: feature_importance - (boolean) Whether feature importance should be populated in the returned TablesAnnotations. The default is false. - For Video 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) No more than this number of bounding boxes will be returned per frame. Default is 100, the requested value may be limited by server. `min_bounding_box_size` - (float) Only bounding boxes with shortest edge at least that long as a relative value of video frame size will be returned. Value in 0 to 1 range. Default is 0. This corresponds to the `params` field on the `request` instance; if `request` is provided, this should not be set.
`retry`	`google.api_core.retry.Retry` Designation of what errors, if any, should be retried.
`timeout`	`float` The timeout for this request.
`metadata`	`Sequence[Tuple[str, str]]` Strings which should be sent along with the request as metadata.

Returns

Type	Description
`google.api_core.operation.Operation`	An object representing a long-running operation. The result type for the operation will be BatchPredictResult Result of the Batch Predict. This message is returned in `response][google.longrunning.Operation.response]` of the operation returned by the PredictionService.BatchPredict.

common_billing_account_path

common_billing_account_path(billing_account: str)

Returns a fully-qualified billing_account string.

common_folder_path

common_folder_path(folder: str)

Returns a fully-qualified folder string.

common_location_path

common_location_path(project: str, location: str)

Returns a fully-qualified location string.

common_organization_path

common_organization_path(organization: str)

Returns a fully-qualified organization string.

common_project_path

common_project_path(project: str)

Returns a fully-qualified project string.

from_service_account_file

from_service_account_file(filename: str, *args, **kwargs)

Creates an instance of this client using the provided credentials file.

Parameter

Name	Description
`filename`	`str` The path to the service account private key json file.

Returns

Type	Description
`PredictionServiceClient`	The constructed client.

from_service_account_info

from_service_account_info(info: dict, *args, **kwargs)

Creates an instance of this client using the provided credentials info.

Parameter

Name	Description
`info`	`dict` The service account private key info.

Returns

Type	Description
`PredictionServiceClient`	The constructed client.

from_service_account_json

from_service_account_json(filename: str, *args, **kwargs)

Creates an instance of this client using the provided credentials file.

Parameter

Name	Description
`filename`	`str` The path to the service account private key json file.

Returns

Type	Description
`PredictionServiceClient`	The constructed client.

get_mtls_endpoint_and_cert_source

get_mtls_endpoint_and_cert_source(
    client_options: Optional[google.api_core.client_options.ClientOptions] = None,
)

Return the API endpoint and client cert source for mutual TLS.

The client cert source is determined in the following order: (1) if GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable is not "true", the client cert source is None. (2) if client_options.client_cert_source is provided, use the provided one; if the default client cert source exists, use the default one; otherwise the client cert source is None.

The API endpoint is determined in the following order: (1) if client_options.api_endpoint if provided, use the provided one. (2) if GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable is "always", use the default mTLS endpoint; if the environment variabel is "never", use the default API endpoint; otherwise if client cert source exists, use the default mTLS endpoint, otherwise use the default API endpoint.

More details can be found at https://google.aip.dev/auth/4114.

Parameter

Name	Description
`client_options`	`google.api_core.client_options.ClientOptions` Custom options for the client. Only the `api_endpoint` and `client_cert_source` properties may be used in this method.

Exceptions

Type	Description
`google.auth.exceptions.MutualTLSChannelError`	If any errors happen.

Returns

Type	Description
`Tuple[str, Callable[[], Tuple[bytes, bytes]]]`	returns the API endpoint and the client cert source to use.

model_path

model_path(project: str, location: str, model: str)

Returns a fully-qualified model string.

parse_common_billing_account_path

parse_common_billing_account_path(path: str)

Parse a billing_account path into its component segments.

parse_common_folder_path

parse_common_folder_path(path: str)

Parse a folder path into its component segments.

parse_common_location_path

parse_common_location_path(path: str)

Parse a location path into its component segments.

parse_common_organization_path

parse_common_organization_path(path: str)

Parse a organization path into its component segments.

parse_common_project_path

parse_common_project_path(path: str)

Parse a project path into its component segments.

parse_model_path

parse_model_path(path: str)

Parses a model path into its component segments.

predict

predict(request: Optional[Union[google.cloud.automl_v1beta1.types.prediction_service.PredictRequest, dict]] = None, *, name: Optional[str] = None, payload: Optional[google.cloud.automl_v1beta1.types.data_items.ExamplePayload] = None, params: Optional[Mapping[str, str]] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Perform an online prediction. The prediction result will be directly returned in the response. Available for following ML problems, and their expected request payloads:

Image Classification - Image in .JPEG, .GIF or .PNG format, image_bytes up to 30MB.
Image Object Detection - Image in .JPEG, .GIF or .PNG format, image_bytes up to 30MB.
Text Classification - TextSnippet, content up to 60,000 characters, UTF-8 encoded.
Text Extraction - TextSnippet, content up to 30,000 characters, UTF-8 NFC encoded.
Translation - TextSnippet, content up to 25,000 characters, UTF-8 encoded.
Tables - Row, with column values matching the columns of the model, up to 5MB. Not available for FORECASTING

xref_prediction_type.

Text Sentiment - TextSnippet, content up 500 characters, UTF-8 encoded.

from google.cloud import automl_v1beta1

def sample_predict():
    # Create a client
    client = automl_v1beta1.PredictionServiceClient()

    # Initialize request argument(s)
    payload = automl_v1beta1.ExamplePayload()
    payload.image.image_bytes = b'image_bytes_blob'

    request = automl_v1beta1.PredictRequest(
        name="name_value",
        payload=payload,
    )

    # Make the request
    response = client.predict(request=request)

    # Handle the response
    print(response)

Parameters

Name	Description
`request`	`Union[google.cloud.automl_v1beta1.types.PredictRequest, dict]` The request object. Request message for PredictionService.Predict.
`name`	`str` Required. Name of the model requested to serve the prediction. This corresponds to the `name` field on the `request` instance; if `request` is provided, this should not be set.
`payload`	`google.cloud.automl_v1beta1.types.ExamplePayload` Required. Payload to perform a prediction on. The payload must match the problem type that the model was trained to solve. This corresponds to the `payload` field on the `request` instance; if `request` is provided, this should not be set.
`params`	`Mapping[str, str]` Additional domain-specific parameters, any string must be up to 25000 characters long. - For Image 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. - For Image 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) No more than this number of bounding boxes will be returned in the response. Default is 100, the requested value may be limited by server. - For Tables: feature_importance - (boolean) Whether feature importance should be populated in the returned TablesAnnotation. The default is false. This corresponds to the `params` field on the `request` instance; if `request` is provided, this should not be set.
`retry`	`google.api_core.retry.Retry` Designation of what errors, if any, should be retried.
`timeout`	`float` The timeout for this request.
`metadata`	`Sequence[Tuple[str, str]]` Strings which should be sent along with the request as metadata.

Returns

Type	Description
`google.cloud.automl_v1beta1.types.PredictResponse`	Response message for PredictionService.Predict.