Amazon web services AWS文本摘要-不支持文档例外

在使用boto3 for python实现aws textract时

代码：

下面是aws的凭证和配置文件

niranjan@niranjan:~$ cat ~/.aws/credentials
[default]
aws_access_key_id=my_access_key_id
aws_secret_access_key=my_secret_access_key

niranjan@niranjan:~$ cat ~/.aws/config 
[default]
region=eu-west-1

我得到一个例外：

---------------------------------------------------------------------------
UnsupportedDocumentException              Traceback (most recent call last)
<ipython-input-11-f52c10e3f3db> in <module>
     14 
     15 # Call Amazon Textract
---> 16 response = textract.detect_document_text(Document={'Bytes': imageBytes})
     17 
     18 #print(response)

~/venv/lib/python3.7/site-packages/botocore/client.py in _api_call(self, *args, **kwargs)
    314                     "%s() only accepts keyword arguments." % py_operation_name)
    315             # The "self" in this scope is referring to the BaseClient.
--> 316             return self._make_api_call(operation_name, kwargs)
    317 
    318         _api_call.__name__ = str(py_operation_name)

~/venv/lib/python3.7/site-packages/botocore/client.py in _make_api_call(self, operation_name, api_params)
    624             error_code = parsed_response.get("Error", {}).get("Code")
    625             error_class = self.exceptions.from_code(error_code)
--> 626             raise error_class(parsed_response, operation_name)
    627         else:
    628             return parsed_response

UnsupportedDocumentException: An error occurred (UnsupportedDocumentException) when calling the DetectDocumentText operation: Request has unsupported document format

---------------------------------------------------------------------------
UnsupportedDocumentException回溯（最后一次最近调用）
在里面
14
15#打电话给Amazon Textract
--->16 response=textract.detect\u document\u text（document={'Bytes'：imageBytes}）
17
18#打印（回复）
调用中的~/venv/lib/python3.7/site-packages/botocore/client.py（self，*args，**kwargs）
314“%s（）只接受关键字参数。“%py\u操作\u名称）
315#此范围中的“自我”指的是基本客户机。
-->316返回self.\u make\u api\u调用（操作名称，kwargs）
317
318\u api\u调用。\u名称\u=str（py\u操作\u名称）
~/venv/lib/python3.7/site-packages/botocore/client.py in\u make\u api\u调用（self、operation\u name、api\u参数）
624 error_code=解析的_响应.get（“error”，{}）.get（“code”）
625错误\u类=self.exceptions.from\u代码（错误\u代码）
-->626引发错误\u类（解析的\u响应、操作\u名称）
627其他：
628返回解析的_响应
UnsupportedDocumentException:调用DetectDocumentText操作时发生错误（UnsupportedDocumentException）：请求的文档格式不受支持

---

我对AWS textract有点陌生，任何帮助都将不胜感激。

因为textract的API不支持“pdf”类型的文档，发送遇到的pdf

不支持文档格式异常

。尝试改为发送图像文件

如果您仍然想要发送pdf文件，那么您必须使用Textract的异步API。例如，

StartDocumentAnalysis

API开始分析，以及

GetDocumentAnalysis

获取分析过的文档

检测输入文档中的文本。Amazon Textract可以检测文本行和组成文本行的单词。输入文档必须是JPEG或PNG格式的图像。DetectDocumentText返回块对象数组中检测到的文本

请尝试此代码，并参考AWS的说明

---------------------------------------------------------------------------
UnsupportedDocumentException              Traceback (most recent call last)
<ipython-input-11-f52c10e3f3db> in <module>
     14 
     15 # Call Amazon Textract
---> 16 response = textract.detect_document_text(Document={'Bytes': imageBytes})
     17 
     18 #print(response)

~/venv/lib/python3.7/site-packages/botocore/client.py in _api_call(self, *args, **kwargs)
    314                     "%s() only accepts keyword arguments." % py_operation_name)
    315             # The "self" in this scope is referring to the BaseClient.
--> 316             return self._make_api_call(operation_name, kwargs)
    317 
    318         _api_call.__name__ = str(py_operation_name)

~/venv/lib/python3.7/site-packages/botocore/client.py in _make_api_call(self, operation_name, api_params)
    624             error_code = parsed_response.get("Error", {}).get("Code")
    625             error_class = self.exceptions.from_code(error_code)
--> 626             raise error_class(parsed_response, operation_name)
    627         else:
    628             return parsed_response

UnsupportedDocumentException: An error occurred (UnsupportedDocumentException) when calling the DetectDocumentText operation: Request has unsupported document format

import boto3
import time

def startJob(s3BucketName, objectName):
    response = None
    client = boto3.client('textract')
    response = client.start_document_text_detection(
    DocumentLocation={
        'S3Object': {
            'Bucket': s3BucketName,
            'Name': objectName
        }
    })

    return response["JobId"]

def isJobComplete(jobId):
    # For production use cases, use SNS based notification 
    # Details at: https://docs.aws.amazon.com/textract/latest/dg/api-async.html
    time.sleep(5)
    client = boto3.client('textract')
    response = client.get_document_text_detection(JobId=jobId)
    status = response["JobStatus"]
    print("Job status: {}".format(status))

    while(status == "IN_PROGRESS"):
        time.sleep(5)
        response = client.get_document_text_detection(JobId=jobId)
        status = response["JobStatus"]
        print("Job status: {}".format(status))

    return status

def getJobResults(jobId):

    pages = []

    client = boto3.client('textract')
    response = client.get_document_text_detection(JobId=jobId)
    
    pages.append(response)
    print("Resultset page recieved: {}".format(len(pages)))
    nextToken = None
    if('NextToken' in response):
        nextToken = response['NextToken']

    while(nextToken):

        response = client.get_document_text_detection(JobId=jobId, NextToken=nextToken)

        pages.append(response)
        print("Resultset page recieved: {}".format(len(pages)))
        nextToken = None
        if('NextToken' in response):
            nextToken = response['NextToken']

    return pages

# Document
s3BucketName = "ki-textract-demo-docs"
documentName = "Amazon-Textract-Pdf.pdf"

jobId = startJob(s3BucketName, documentName)
print("Started job with id: {}".format(jobId))
if(isJobComplete(jobId)):
    response = getJobResults(jobId)

#print(response)

# Print detected text
for resultPage in response:
    for item in resultPage["Blocks"]:
        if item["BlockType"] == "LINE":
            print ('\033[94m' +  item["Text"] + '\033[0m')