问题
I'm working on a project in which I need to analyze an image using Google's Vision API and post the response to a Dynamodb table.
I have successfully implemented the Vision API, but not able to convert its response into Python Dictionary.
Here's what I have tried:
if form.is_valid():
obj = form
obj.imageFile = form.cleaned_data['imageFile']
obj.textFile = form.cleaned_data['textFile']
obj.save()
print(obj.imageFile)
# Process the image using Google's vision API
image_path = os.path.join(settings.MEDIA_ROOT, 'images/', obj.imageFile.name)
print(image_path)
image = vision_image_manager(image_path)
text_path = os.path.join(settings.MEDIA_ROOT, 'texts/', obj.textFile.name)
text = nlp_text_manager(text_path)
# print(image)
# print(text)
results = {
'imageResponse': image,
'textResult': text
}
print(results.values())
print(type(results))
post_to_dynamo_db(image, text)
Here's the Vision api implementation:
def vision_image_manager(image_file):
# Instantiates a client
client = vision.ImageAnnotatorClient()
file_name = str(image_file)
with open(file_name, 'rb') as img_file:
content = img_file.read()
image = types.Image(content=content)
response = client.label_detection(image=image)
labels = response.label_annotations
print('Labels:')
for label in labels:
print(label.description)
return labels
And Here's the post_to_dynamo_db
Function:
def post_to_dynamo_db(image, text):
session = boto3.Session(
aws_access_key_id=settings.AWS_SERVER_PUBLIC_KEY,
aws_secret_access_key=settings.AWS_SERVER_SECRET_KEY
)
client = session.resource('dynamodb')
table = client.Table('basetbl')
result_dict = {
'image': image,
'text': text
}
json_dict = dict_to_item(result_dict)
# item = dict_to_item(result_dict)
table.put_item(
Item={
'id': int(generate_pid()),
'response_obj': json_dict
}
)
Now, It doesn't return any error but the response_obj
is not posted in Database table because it's not the correct form of the object, the problem here is the <class 'google.protobuf.pyext._message.RepeatedCompositeContainer'>
type of response returns from Google's API.
回答1:
The best way to get a proper python friendly response from Vision API is to use this API via the Google's Discovery
service.
Here's how this will work for you:
def vision_image_manager(image_file):
# Instantiates a client
service = discovery.build('vision', 'v1', credentials=credentials)
# text.png is the image file.
file_name = str(image_file)
with open(file_name, 'rb') as image:
image_content = base64.b64encode(image.read())
service_request = service.images().annotate(body={
'requests': [{
'image': {
'content': image_content.decode('UTF-8')
},
'features': [{
'type': 'LABEL_DETECTION',
}]
}]
})
response = service_request.execute()
print(response['responses'])
res_dict = dict(response)
return res_dict
来源:https://stackoverflow.com/questions/50160997/googles-vision-api-protobuf-response-object-to-python-dictionary