Class ImageAnnotatorClient (3.8.1)

Service that performs Google Cloud Vision API detection tasks over client images, such as face, landmark, logo, label, and text detection. The ImageAnnotator service returns detected entities from the images.

Return the API endpoint used by the client instance.

Returns the transport used by the client instance.

Return the universe domain used by the client instance.

Instantiates the image annotator client.

Releases underlying transport's resources.

Run asynchronous image detection and annotation for a list of generic files, such as PDF files, which may contain multiple pages and multiple images per page. Progress and results can be retrieved through the google.longrunning.Operations interface. Operation.metadata contains OperationMetadata (metadata). Operation.response contains AsyncBatchAnnotateFilesResponse (results).

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import vision_v1p4beta1

def sample_async_batch_annotate_files():
    # Create a client
    client = vision_v1p4beta1.ImageAnnotatorClient()

    # Initialize request argument(s)
    request = vision_v1p4beta1.AsyncBatchAnnotateFilesRequest(
    )

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

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

    response = operation.result()

    # Handle the response
    print(response)

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

Progress and results can be retrieved through the google.longrunning.Operations interface. Operation.metadata contains OperationMetadata (metadata). Operation.response contains AsyncBatchAnnotateImagesResponse (results).

This service will write image annotation outputs to json files in customer GCS bucket, each json file containing BatchAnnotateImagesResponse proto.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import vision_v1p4beta1

def sample_async_batch_annotate_images():
    # Create a client
    client = vision_v1p4beta1.ImageAnnotatorClient()

    # Initialize request argument(s)
    request = vision_v1p4beta1.AsyncBatchAnnotateImagesRequest(
    )

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

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

    response = operation.result()

    # Handle the response
    print(response)

Service that performs image detection and annotation for a batch of files. Now only "application/pdf", "image/tiff" and "image/gif" are supported.

This service will extract at most 5 (customers can specify which 5 in AnnotateFileRequest.pages) frames (gif) or pages (pdf or tiff) from each file provided and perform detection and annotation for each image extracted.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import vision_v1p4beta1

def sample_batch_annotate_files():
    # Create a client
    client = vision_v1p4beta1.ImageAnnotatorClient()

    # Initialize request argument(s)
    request = vision_v1p4beta1.BatchAnnotateFilesRequest(
    )

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

    # Handle the response
    print(response)

Run image detection and annotation for a batch of images.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import vision_v1p4beta1

def sample_batch_annotate_images():
    # Create a client
    client = vision_v1p4beta1.ImageAnnotatorClient()

    # Initialize request argument(s)
    request = vision_v1p4beta1.BatchAnnotateImagesRequest(
    )

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

    # Handle the response
    print(response)

Returns a fully-qualified billing_account string.

Returns a fully-qualified folder string.

Returns a fully-qualified location string.

Returns a fully-qualified organization string.

Returns a fully-qualified project string.

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

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

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

Deprecated. 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 variable 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.

Parse a billing_account path into its component segments.

Parse a folder path into its component segments.

Parse a location path into its component segments.

Parse a organization path into its component segments.

Parse a project path into its component segments.

Parses a product path into its component segments.

Parses a product_set path into its component segments.

Returns a fully-qualified product string.

Returns a fully-qualified product_set string.