Service availability notice: Streaming Video and Bulk Image Analysis is no longer available to new customers. For more information, see Rekognition feature availability changes.
This change does not impact the availability of other Amazon Rekognition features.
Gets a list of stream processors that you have created with CreateStreamProcessor.
Parameters:
-
next_token
(Optional[PaginationToken], default:
None
)
–
If the previous response was incomplete (because there are more stream processors to retrieve), Amazon Rekognition Video returns a pagination token in the response. You can use this pagination token to retrieve the next set of stream processors.
-
max_results
(Optional[MaxResults], default:
None
)
–
Maximum number of stream processors you want Amazon Rekognition Video to return in the response. The default is 1000.
Raises:
Source code in docs_src/capo_rekognition/_services/rekognition.py
| def list_stream_processors(
self,
*,
config_overrides: Optional[RekognitionClientConfig] = None,
next_token: Optional[
"capo_rekognition.types.pagination_token.PaginationToken"
] = None,
max_results: Optional["capo_rekognition.types.max_results.MaxResults"] = None,
) -> "capo_rekognition.types.list_stream_processors_response.ListStreamProcessorsResponse":
"""<important> <p>Service availability notice: Streaming Video and Bulk Image Analysis is no longer available to new customers. For more information, see <a href="https://docs.aws.amazon.com/rekognition/latest/dg/rekognition-availability-changes.html">Rekognition feature availability changes</a>.</p> <p> <b>This change does not impact the availability of other Amazon Rekognition features.</b> </p> </important> <p>Gets a list of stream processors that you have created with <a>CreateStreamProcessor</a>. </p>
Args:
next_token: <p>If the previous response was incomplete (because there are more stream processors to retrieve), Amazon Rekognition Video returns a pagination token in the response. You can use this pagination token to retrieve the next set of stream processors. </p>
max_results: <p>Maximum number of stream processors you want Amazon Rekognition Video to return in the response. The default is 1000. </p>
Raises:
capo_rekognition.errors.access_denied_exception.AccessDeniedException: <p>You are not authorized to perform the action.</p>
capo_rekognition.errors.internal_server_error.InternalServerError: <p>Amazon Rekognition experienced a service issue. Try your call again.</p>
capo_rekognition.errors.invalid_pagination_token_exception.InvalidPaginationTokenException: <p>Pagination token in the request is not valid.</p>
capo_rekognition.errors.invalid_parameter_exception.InvalidParameterException: <p>Input parameter violated a constraint. Validate your parameter before calling the API operation again.</p>
capo_rekognition.errors.provisioned_throughput_exceeded_exception.ProvisionedThroughputExceededException: <p>The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.</p>
capo_rekognition.errors.throttling_exception.ThrottlingException: <p>Amazon Rekognition is temporarily unable to process the request. Try your call again.</p>
capo_rekognition.errors.UnknownServiceError: The service returned an error code this client does not model.
"""
def _handler(
req: "OperationRequest[capo_rekognition.types.list_stream_processors_request.ListStreamProcessorsRequest]",
) -> OperationResponse[
"capo_rekognition.types.list_stream_processors_response.ListStreamProcessorsResponse"
]:
import capo_rekognition._operations.rekognition_service.list_stream_processors
output, http_response = (
capo_rekognition._operations.rekognition_service.list_stream_processors.list_stream_processors(
req.options, req.input
)
)
return OperationResponse(output=output, response=http_response)
interceptors_, options_ = self.operation_options(
config_overrides, OperationLogging("ListStreamProcessors")
)
input_: capo_rekognition.types.list_stream_processors_request.ListStreamProcessorsRequest = {}
if next_token is not None:
input_["next_token"] = next_token
if max_results is not None:
input_["max_results"] = max_results
response = execute_pipeline(
OperationRequest(input=input_, options=options_),
handler=_handler,
interceptors=list(interceptors_),
)
response.response.close()
return response.output
|