I have 1000s of images sitting in a container on my blob storage. I want to process these images one by one in Python and spit out the new images out into a new container (the process is basically detecting and redacting objects). Downloading the images locally is not an option because they take up way too much space.
So far, I have been able to connect to the blob and have created a new container to store the processed images in, but I have no idea how to run the code to process the pictures and save them to the new container. Can anyone help with this?
Code so far is:
from azure.storage.file import FileService
from azure.storage.blob import BlockBlobService
# call blob service for the storage acct
block_blob_service = BlockBlobService(account_name = 'mycontainer', account_key = 'HJMEchn')
# create new container to store processed images
container_name = 'new_images'
block_blob_service.create_container(container_name)
Do I need to use get_blob_to_stream or get_blob_to_path from here: https://azure-storage.readthedocs.io/ref/azure.storage.blob.baseblobservice.html so I don't have to download the images?
Any help would be much appreciated!