detect_text async ¶

async def detect_text(
    self,
    image: "capo_rekognition.types.image.Image",
    *,
    config_overrides: Optional[AsyncRekognitionClientConfig] = None,
    filters: Optional[
        "capo_rekognition.types.detect_text_filters.DetectTextFilters"
    ] = None,
) -> "capo_rekognition.types.detect_text_response.DetectTextResponse":
    """<p>Detects text in the input image and converts it into machine-readable text.</p> <p>Pass the input image as base64-encoded image bytes or as a reference to an image in an Amazon S3 bucket. If you use the AWS CLI to call Amazon Rekognition operations, you must pass it as a reference to an image in an Amazon S3 bucket. For the AWS CLI, passing image bytes is not supported. The image must be either a .png or .jpeg formatted file. </p> <p>The <code>DetectText</code> operation returns text in an array of <a>TextDetection</a> elements, <code>TextDetections</code>. Each <code>TextDetection</code> element provides information about a single word or line of text that was detected in the image. </p> <p>A word is one or more script characters that are not separated by spaces. <code>DetectText</code> can detect up to 100 words in an image.</p> <p>A line is a string of equally spaced words. A line isn't necessarily a complete sentence. For example, a driver's license number is detected as a line. A line ends when there is no aligned text after it. Also, a line ends when there is a large gap between words, relative to the length of the words. This means, depending on the gap between words, Amazon Rekognition may detect multiple lines in text aligned in the same direction. Periods don't represent the end of a line. If a sentence spans multiple lines, the <code>DetectText</code> operation returns multiple lines.</p> <p>To determine whether a <code>TextDetection</code> element is a line of text or a word, use the <code>TextDetection</code> object <code>Type</code> field. </p> <p>To be detected, text must be within +/- 90 degrees orientation of the horizontal axis.</p> <p>For more information, see Detecting text in the Amazon Rekognition Developer Guide.</p>

    Args:
        image: <p>The input image as base64-encoded bytes or an Amazon S3 object. If you use the AWS CLI to call Amazon Rekognition operations, you can't pass image bytes. </p> <p>If you are using an AWS SDK to call Amazon Rekognition, you might not need to base64-encode image bytes passed using the <code>Bytes</code> field. For more information, see Images in the Amazon Rekognition developer guide.</p>
        filters: <p>Optional parameters that let you set the criteria that the text must meet to be included in your response.</p>

    Raises:
        capo_rekognition.errors.access_denied_exception.AccessDeniedException: <p>You are not authorized to perform the action.</p>
        capo_rekognition.errors.image_too_large_exception.ImageTooLargeException: <p>The input image size exceeds the allowed limit. If you are calling DetectProtectiveEquipment, the image size or resolution exceeds the allowed limit. For more information, see Guidelines and quotas in Amazon Rekognition in the Amazon Rekognition Developer Guide. </p>
        capo_rekognition.errors.internal_server_error.InternalServerError: <p>Amazon Rekognition experienced a service issue. Try your call again.</p>
        capo_rekognition.errors.invalid_image_format_exception.InvalidImageFormatException: <p>The provided image format is not supported. </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.invalid_s3_object_exception.InvalidS3ObjectException: <p>Amazon Rekognition is unable to access the S3 object specified in the request.</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.
    """

    async def _handler(
        req: "AsyncOperationRequest[capo_rekognition.types.detect_text_request.DetectTextRequest]",
    ) -> AsyncOperationResponse[
        "capo_rekognition.types.detect_text_response.DetectTextResponse"
    ]:
        import capo_rekognition._operations.rekognition_service.detect_text

        (
            output,
            http_response,
        ) = await capo_rekognition._operations.rekognition_service.detect_text.async_detect_text(
            req.options, req.input
        )
        return AsyncOperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("DetectText")
    )
    input_: capo_rekognition.types.detect_text_request.DetectTextRequest = {
        "image": image
    }
    if filters is not None:
        input_["filters"] = filters

    response = await aexecute_pipeline(
        AsyncOperationRequest(input=input_, options=options_),
        handler=_handler,
        interceptors=list(interceptors_),
    )
    await response.response.aclose()
    return response.output