get_face_search ¶

def get_face_search(
    self,
    job_id: "capo_rekognition.types.job_id.JobId",
    *,
    config_overrides: Optional[RekognitionClientConfig] = None,
    max_results: Optional["capo_rekognition.types.max_results.MaxResults"] = None,
    next_token: Optional[
        "capo_rekognition.types.pagination_token.PaginationToken"
    ] = None,
    sort_by: Optional[
        "capo_rekognition.types.face_search_sort_by.FaceSearchSortBy"
    ] = None,
) -> "capo_rekognition.types.get_face_search_response.GetFaceSearchResponse":
    """<p>Gets the face search results for Amazon Rekognition Video face search started by <a>StartFaceSearch</a>. The search returns faces in a collection that match the faces of persons detected in a video. It also includes the time(s) that faces are matched in the video.</p> <p>Face search in a video is an asynchronous operation. You start face search by calling to <a>StartFaceSearch</a> which returns a job identifier (<code>JobId</code>). When the search operation finishes, Amazon Rekognition Video publishes a completion status to the Amazon Simple Notification Service topic registered in the initial call to <code>StartFaceSearch</code>. To get the search results, first check that the status value published to the Amazon SNS topic is <code>SUCCEEDED</code>. If so, call <code>GetFaceSearch</code> and pass the job identifier (<code>JobId</code>) from the initial call to <code>StartFaceSearch</code>.</p> <p>For more information, see Searching Faces in a Collection in the Amazon Rekognition Developer Guide.</p> <p>The search results are retured in an array, <code>Persons</code>, of <a>PersonMatch</a> objects. Each<code>PersonMatch</code> element contains details about the matching faces in the input collection, person information (facial attributes, bounding boxes, and person identifer) for the matched person, and the time the person was matched in the video.</p> <note> <p> <code>GetFaceSearch</code> only returns the default facial attributes (<code>BoundingBox</code>, <code>Confidence</code>, <code>Landmarks</code>, <code>Pose</code>, and <code>Quality</code>). The other facial attributes listed in the <code>Face</code> object of the following response syntax are not returned. For more information, see FaceDetail in the Amazon Rekognition Developer Guide. </p> </note> <p>By default, the <code>Persons</code> array is sorted by the time, in milliseconds from the start of the video, persons are matched. You can also sort by persons by specifying <code>INDEX</code> for the <code>SORTBY</code> input parameter.</p>

    Args:
        job_id: <p>The job identifer for the search request. You get the job identifier from an initial call to <code>StartFaceSearch</code>.</p>
        max_results: <p>Maximum number of results to return per paginated call. The largest value you can specify is 1000. If you specify a value greater than 1000, a maximum of 1000 results is returned. The default value is 1000.</p>
        next_token: <p>If the previous response was incomplete (because there is more search results to retrieve), Amazon Rekognition Video returns a pagination token in the response. You can use this pagination token to retrieve the next set of search results. </p>
        sort_by: <p>Sort to use for grouping faces in the response. Use <code>TIMESTAMP</code> to group faces by the time that they are recognized. Use <code>INDEX</code> to sort by recognized faces. </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.resource_not_found_exception.ResourceNotFoundException: <p>The resource specified in the request cannot be found.</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.get_face_search_request.GetFaceSearchRequest]",
    ) -> OperationResponse[
        "capo_rekognition.types.get_face_search_response.GetFaceSearchResponse"
    ]:
        import capo_rekognition._operations.rekognition_service.get_face_search

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

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("GetFaceSearch")
    )
    input_: capo_rekognition.types.get_face_search_request.GetFaceSearchRequest = {
        "job_id": job_id
    }
    if max_results is not None:
        input_["max_results"] = max_results
    if next_token is not None:
        input_["next_token"] = next_token
    if sort_by is not None:
        input_["sort_by"] = sort_by

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