使用boto3 for python实现AWS textract时。
代码:
import boto3
# Document
documentName = "/home/niranjan/IdeaProjects/amazon-forecast-samples/notebooks/basic/Tutorial/cert.pdf"
# Read document content
with open(documentName, 'rb') as document:
imageBytes = bytearray(document.read())
print(type(imageBytes))
# Amazon Textract client
textract = boto3.client('textract', region_name='us-west-2')
# Call Amazon Textract
response = textract.detect_document_text(Document={'Bytes': imageBytes})
以下是AWS的凭据和配置文件
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
我遇到此异常:
---------------------------------------------------------------------------
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
我对AWS textract还是陌生的,任何帮助将不胜感激。
答案 0 :(得分:1)
由于Textract的DetectDocumentText
API不支持“ pdf”类型的文档,因此将您遇到的UnsupportedDocumentFormat Exception
发送给pdf。尝试改为发送图像文件。
如果您仍然想发送pdf文件,则必须使用Textract的异步API。例如。 StartDocumentAnalysis
API用于开始分析,而GetDocumentAnalysis
用于获取分析的文档。
检测输入文档中的文本。 Amazon Textract可以检测文本行以及组成文本行的单词。输入文档必须是JPEG或PNG格式的图像。 DetectDocumentText返回在Block对象数组中检测到的文本。
https://docs.aws.amazon.com/textract/latest/dg/API_DetectDocumentText.html
答案 1 :(得分:0)
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')
尝试使用此代码,并从AWS将此link进行解释