用于 Python 的 Amaz SDK on Textract 示例 (Boto3)

以下代码示例向您展示了如何在 Amazon Textract 中 AWS SDK for Python (Boto3) 使用来执行操作和实现常见场景。

操作是大型程序的代码摘录，必须在上下文中运行。您可以通过操作了解如何调用单个服务函数，还可以通过函数相关场景的上下文查看操作。

场景是向您展示如何通过在一个服务中调用多个函数或与其他 AWS 服务结合来完成特定任务的代码示例。

每个示例都包含一个指向完整源代码的链接，您可以在其中找到有关如何在上下文中设置和运行代码的说明。

主题

操作
场景

操作

以下代码示例演示如何使用 AnalyzeDocument。

SDK适用于 Python (Boto3)

注意

还有更多相关信息 GitHub。查找完整示例，学习如何在 AWS 代码示例存储库中进行设置和运行。


class TextractWrapper:
    """Encapsulates Textract functions."""

    def __init__(self, textract_client, s3_resource, sqs_resource):
        """
        :param textract_client: A Boto3 Textract client.
        :param s3_resource: A Boto3 Amazon S3 resource.
        :param sqs_resource: A Boto3 Amazon SQS resource.
        """
        self.textract_client = textract_client
        self.s3_resource = s3_resource
        self.sqs_resource = sqs_resource


    def analyze_file(
        self, feature_types, *, document_file_name=None, document_bytes=None
    ):
        """
        Detects text and additional elements, such as forms or tables, in a local image
        file or from in-memory byte data.
        The image must be in PNG or JPG format.

        :param feature_types: The types of additional document features to detect.
        :param document_file_name: The name of a document image file.
        :param document_bytes: In-memory byte data of a document image.
        :return: The response from Amazon Textract, including a list of blocks
                 that describe elements detected in the image.
        """
        if document_file_name is not None:
            with open(document_file_name, "rb") as document_file:
                document_bytes = document_file.read()
        try:
            response = self.textract_client.analyze_document(
                Document={"Bytes": document_bytes}, FeatureTypes=feature_types
            )
            logger.info("Detected %s blocks.", len(response["Blocks"]))
        except ClientError:
            logger.exception("Couldn't detect text.")
            raise
        else:
            return response

有关API详细信息，请参阅AnalyzeDocument中的 AWS SDKPython (Boto3) API 参考。

以下代码示例演示如何使用 DetectDocumentText。

SDK适用于 Python (Boto3)

注意

还有更多相关信息 GitHub。查找完整示例，学习如何在 AWS 代码示例存储库中进行设置和运行。


class TextractWrapper:
    """Encapsulates Textract functions."""

    def __init__(self, textract_client, s3_resource, sqs_resource):
        """
        :param textract_client: A Boto3 Textract client.
        :param s3_resource: A Boto3 Amazon S3 resource.
        :param sqs_resource: A Boto3 Amazon SQS resource.
        """
        self.textract_client = textract_client
        self.s3_resource = s3_resource
        self.sqs_resource = sqs_resource


    def detect_file_text(self, *, document_file_name=None, document_bytes=None):
        """
        Detects text elements in a local image file or from in-memory byte data.
        The image must be in PNG or JPG format.

        :param document_file_name: The name of a document image file.
        :param document_bytes: In-memory byte data of a document image.
        :return: The response from Amazon Textract, including a list of blocks
                 that describe elements detected in the image.
        """
        if document_file_name is not None:
            with open(document_file_name, "rb") as document_file:
                document_bytes = document_file.read()
        try:
            response = self.textract_client.detect_document_text(
                Document={"Bytes": document_bytes}
            )
            logger.info("Detected %s blocks.", len(response["Blocks"]))
        except ClientError:
            logger.exception("Couldn't detect text.")
            raise
        else:
            return response

有关API详细信息，请参阅DetectDocumentText中的 AWS SDKPython (Boto3) API 参考。

以下代码示例演示如何使用 GetDocumentAnalysis。

SDK适用于 Python (Boto3)

注意

还有更多相关信息 GitHub。查找完整示例，学习如何在 AWS 代码示例存储库中进行设置和运行。


class TextractWrapper:
    """Encapsulates Textract functions."""

    def __init__(self, textract_client, s3_resource, sqs_resource):
        """
        :param textract_client: A Boto3 Textract client.
        :param s3_resource: A Boto3 Amazon S3 resource.
        :param sqs_resource: A Boto3 Amazon SQS resource.
        """
        self.textract_client = textract_client
        self.s3_resource = s3_resource
        self.sqs_resource = sqs_resource


    def get_analysis_job(self, job_id):
        """
        Gets data for a previously started detection job that includes additional
        elements.

        :param job_id: The ID of the job to retrieve.
        :return: The job data, including a list of blocks that describe elements
                 detected in the image.
        """
        try:
            response = self.textract_client.get_document_analysis(JobId=job_id)
            job_status = response["JobStatus"]
            logger.info("Job %s status is %s.", job_id, job_status)
        except ClientError:
            logger.exception("Couldn't get data for job %s.", job_id)
            raise
        else:
            return response

有关API详细信息，请参阅GetDocumentAnalysis中的 AWS SDKPython (Boto3) API 参考。

以下代码示例演示如何使用 StartDocumentAnalysis。

SDK适用于 Python (Boto3)

注意

还有更多相关信息 GitHub。查找完整示例，学习如何在 AWS 代码示例存储库中进行设置和运行。

启动异步任务以分析文档。


class TextractWrapper:
    """Encapsulates Textract functions."""

    def __init__(self, textract_client, s3_resource, sqs_resource):
        """
        :param textract_client: A Boto3 Textract client.
        :param s3_resource: A Boto3 Amazon S3 resource.
        :param sqs_resource: A Boto3 Amazon SQS resource.
        """
        self.textract_client = textract_client
        self.s3_resource = s3_resource
        self.sqs_resource = sqs_resource


    def start_analysis_job(
        self,
        bucket_name,
        document_file_name,
        feature_types,
        sns_topic_arn,
        sns_role_arn,
    ):
        """
        Starts an asynchronous job to detect text and additional elements, such as
        forms or tables, in an image stored in an Amazon S3 bucket. Textract publishes
        a notification to the specified Amazon SNS topic when the job completes.
        The image must be in PNG, JPG, or PDF format.

        :param bucket_name: The name of the Amazon S3 bucket that contains the image.
        :param document_file_name: The name of the document image stored in Amazon S3.
        :param feature_types: The types of additional document features to detect.
        :param sns_topic_arn: The Amazon Resource Name (ARN) of an Amazon SNS topic
                              where job completion notification is published.
        :param sns_role_arn: The ARN of an AWS Identity and Access Management (IAM)
                             role that can be assumed by Textract and grants permission
                             to publish to the Amazon SNS topic.
        :return: The ID of the job.
        """
        try:
            response = self.textract_client.start_document_analysis(
                DocumentLocation={
                    "S3Object": {"Bucket": bucket_name, "Name": document_file_name}
                },
                NotificationChannel={
                    "SNSTopicArn": sns_topic_arn,
                    "RoleArn": sns_role_arn,
                },
                FeatureTypes=feature_types,
            )
            job_id = response["JobId"]
            logger.info(
                "Started text analysis job %s on %s.", job_id, document_file_name
            )
        except ClientError:
            logger.exception("Couldn't analyze text in %s.", document_file_name)
            raise
        else:
            return job_id

有关API详细信息，请参阅StartDocumentAnalysis中的 AWS SDKPython (Boto3) API 参考。

以下代码示例演示如何使用 StartDocumentTextDetection。

SDK适用于 Python (Boto3)

注意

还有更多相关信息 GitHub。查找完整示例，学习如何在 AWS 代码示例存储库中进行设置和运行。

启动异步任务以检测文档中的文本。


class TextractWrapper:
    """Encapsulates Textract functions."""

    def __init__(self, textract_client, s3_resource, sqs_resource):
        """
        :param textract_client: A Boto3 Textract client.
        :param s3_resource: A Boto3 Amazon S3 resource.
        :param sqs_resource: A Boto3 Amazon SQS resource.
        """
        self.textract_client = textract_client
        self.s3_resource = s3_resource
        self.sqs_resource = sqs_resource


    def start_detection_job(
        self, bucket_name, document_file_name, sns_topic_arn, sns_role_arn
    ):
        """
        Starts an asynchronous job to detect text elements in an image stored in an
        Amazon S3 bucket. Textract publishes a notification to the specified Amazon SNS
        topic when the job completes.
        The image must be in PNG, JPG, or PDF format.

        :param bucket_name: The name of the Amazon S3 bucket that contains the image.
        :param document_file_name: The name of the document image stored in Amazon S3.
        :param sns_topic_arn: The Amazon Resource Name (ARN) of an Amazon SNS topic
                              where the job completion notification is published.
        :param sns_role_arn: The ARN of an AWS Identity and Access Management (IAM)
                             role that can be assumed by Textract and grants permission
                             to publish to the Amazon SNS topic.
        :return: The ID of the job.
        """
        try:
            response = self.textract_client.start_document_text_detection(
                DocumentLocation={
                    "S3Object": {"Bucket": bucket_name, "Name": document_file_name}
                },
                NotificationChannel={
                    "SNSTopicArn": sns_topic_arn,
                    "RoleArn": sns_role_arn,
                },
            )
            job_id = response["JobId"]
            logger.info(
                "Started text detection job %s on %s.", job_id, document_file_name
            )
        except ClientError:
            logger.exception("Couldn't detect text in %s.", document_file_name)
            raise
        else:
            return job_id

有关API详细信息，请参阅StartDocumentTextDetection中的 AWS SDKPython (Boto3) API 参考。

场景

以下代码示例展示了如何通过交互式应用程序浏览 Amazon Textract 的输出。

SDK适用于 Python (Boto3)

演示如何 AWS SDK for Python (Boto3) 与 Amazon Textract 配合使用来检测文档图像中的文本、表单和表格元素。输入图像和 Amazon Textract 输出在 Tkinter 应用程序中显示，该应用程序可让您探索检测到的元素。

将文档图像提交到 Amazon Textract 并探索检测到的元素的输出。
将图像直接提交到 Amazon Textract，或通过 Amazon Simple Storage Service（Amazon S3）桶提交图像。
使用异步APIs启动任务，该任务在任务完成时向亚马逊简单通知服务 (AmazonSNS) 主题发布通知。
轮询亚马逊简单队列服务 (AmazonSQS) 队列以获取任务完成消息并显示结果。

有关如何设置和运行的完整源代码和说明，请参阅上的完整示例GitHub。

本示例中使用的服务

Amazon S3
Amazon SNS
Amazon SQS
Amazon Textract

以下代码示例显示了如何使用 Amazon Comprehend 检测 Amazon Textract 从存储在 Amazon S3 内的图像中提取的文本中的实体。

SDK适用于 Python (Boto3)

演示如何使用 Jupyter 笔记本 AWS SDK for Python (Boto3) 中的来检测从图像中提取的文本中的实体。此示例使用 Amazon Textract 从存储在 Amazon Simple Storage Service (Amazon S3) 内的图像中提取文本，并使用 Amazon Comprehend 检测提取文本中的实体。

此示例是 Jupyter 笔记本，必须在可以托管笔记本电脑的环境中运行。有关如何使用 Amazon 运行示例的说明 SageMaker，请参阅 TextractAndComprehendNotebook.ipyn b 中的说明。

有关如何设置和运行的完整源代码和说明，请参阅上的完整示例GitHub。

本示例中使用的服务

Amazon Comprehend
Amazon S3
Amazon Textract

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