Hi all,
I'd like to create a static web server to store almost 1 TB of images.
It is an opensource dataset that I'd like to use to train a Deep Learning model.
I have free usage of GPUs and Internet conexion in another plattform, but they
don't provide me 1 TB storage.
I've also 600$ credits in Google Cloud, I was wondering if there was an easy
way to create something to feed with images the server in the other plattform.
The datasource is available as an AWS bucket. I tried to connect the GPU
machine directly to the ASW bucket via awscli, but it is too much slow. Like
if the bucket were thought for a complete sync but not for coninuous random
access to the files.
I've though two possible approaches:
- Execute a python script in GAE to download the dataset and to create
a GAE web server:
https://cloud.google.com/appengine/docs/standard/python/getting-started/hosting-a-static-website
- Execute a python script in GAE to download the dataset and to create
a Google Cloud CDN.
Do you think any of this approaches are valid to feed the model during the
training?
I'm a newbie in GAE and any help, starting point or idea will be very wellcomed.
Thanks in advance
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