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create_collection 

create_collection(
    collection_id: CollectionId,
    *,
    config_overrides: Optional[RekognitionClientConfig] = None,
    tags: Optional[TagMap] = None,
) -> CreateCollectionResponse

Creates a collection in an AWS Region. You can add faces to the collection using the IndexFaces operation.

For example, you might create collections, one for each of your application users. A user can then index faces using the IndexFaces operation and persist results in a specific collection. Then, a user can search the collection for faces in the user-specific container.

When you create a collection, it is associated with the latest version of the face model version.

Collection names are case-sensitive.

This operation requires permissions to perform the rekognition:CreateCollection action. If you want to tag your collection, you also require permission to perform the rekognition:TagResource operation.

Parameters:

  • collection_id (CollectionId) –

    ID for the collection that you are creating.

  • tags (Optional[TagMap], default: None ) –

    A set of tags (key-value pairs) that you want to attach to the collection.

Raises:

Examples:

To create a collection This operation creates a Rekognition collection for storing image data.

>>> client.create_collection(collection_id='myphotos')
Source code in docs_src/capo_rekognition/_services/rekognition.py 
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def create_collection(
    self,
    collection_id: "capo_rekognition.types.collection_id.CollectionId",
    *,
    config_overrides: Optional[RekognitionClientConfig] = None,
    tags: Optional["capo_rekognition.types.tag_map.TagMap"] = None,
) -> "capo_rekognition.types.create_collection_response.CreateCollectionResponse":
    """<p>Creates a collection in an AWS Region. You can add faces to the collection using the <a>IndexFaces</a> operation. </p> <p>For example, you might create collections, one for each of your application users. A user can then index faces using the <code>IndexFaces</code> operation and persist results in a specific collection. Then, a user can search the collection for faces in the user-specific container. </p> <p>When you create a collection, it is associated with the latest version of the face model version.</p> <note> <p>Collection names are case-sensitive.</p> </note> <p>This operation requires permissions to perform the <code>rekognition:CreateCollection</code> action. If you want to tag your collection, you also require permission to perform the <code>rekognition:TagResource</code> operation.</p>

    Args:
        collection_id: <p>ID for the collection that you are creating.</p>
        tags: <p> A set of tags (key-value pairs) that you want to attach to the collection. </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_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.resource_already_exists_exception.ResourceAlreadyExistsException: <p>A resource with the specified ID already exists.</p>
        capo_rekognition.errors.service_quota_exceeded_exception.ServiceQuotaExceededException: <p></p> <p>The size of the collection exceeds the allowed limit. For more information, see Guidelines and quotas in Amazon Rekognition in the Amazon Rekognition Developer Guide. </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.

    Examples:
        To create a collection
        This operation creates a Rekognition collection for storing image data.

        >>> client.create_collection(collection_id='myphotos')
    """

    def _handler(
        req: "OperationRequest[capo_rekognition.types.create_collection_request.CreateCollectionRequest]",
    ) -> OperationResponse[
        "capo_rekognition.types.create_collection_response.CreateCollectionResponse"
    ]:
        import capo_rekognition._operations.rekognition_service.create_collection

        output, http_response = (
            capo_rekognition._operations.rekognition_service.create_collection.create_collection(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("CreateCollection")
    )
    input_: capo_rekognition.types.create_collection_request.CreateCollectionRequest = {
        "collection_id": collection_id
    }
    if tags is not None:
        input_["tags"] = tags

    response = execute_pipeline(
        OperationRequest(input=input_, options=options_),
        handler=_handler,
        interceptors=list(interceptors_),
    )
    response.response.close()
    return response.output