Upload python object to Google Cloud Storage without saving it to file
Question:
I am clipping images in Python 2.7 on Windows 10 and would like to send them to Google’s Cloud Vision API. For images saved locally, I can send them using the google.cloud python module like this:
blob.upload_from_filename(filename=path)
Documented here
I would rather not save each crop to file, just to send the numpy arrays directly. I could change the numpy arrays to str objects and use
blob.upload_from_string()
but then Cloud Vision API would not be able to read them in my bucket. Is there any way to pipe from python to cloud storage bucket without wasting time/space saving them as an intermediate temporary object?
Answers:
Unfortunately there is not. I am sorry!
you can convert your numpy array to json and then
filename = "file_name_required on cloud"
json_object = [] # your array
and then do
blob = BUCKET.blob(filename)
blob.upload_from_string(data=json.dumps(json_object),content_type='application/json')
I am clipping images in Python 2.7 on Windows 10 and would like to send them to Google’s Cloud Vision API. For images saved locally, I can send them using the google.cloud python module like this:
blob.upload_from_filename(filename=path)
Documented here
I would rather not save each crop to file, just to send the numpy arrays directly. I could change the numpy arrays to str objects and use
blob.upload_from_string()
but then Cloud Vision API would not be able to read them in my bucket. Is there any way to pipe from python to cloud storage bucket without wasting time/space saving them as an intermediate temporary object?
Unfortunately there is not. I am sorry!
you can convert your numpy array to json and then
filename = "file_name_required on cloud"
json_object = [] # your array
and then do
blob = BUCKET.blob(filename)
blob.upload_from_string(data=json.dumps(json_object),content_type='application/json')