Hi @Juani , welcome to the forum!
You can load images in Remo from the server in two ways at the moment:
1- using the Python library from within the server itself. E.g. see this: https://remo.ai/docs/sdk/dataset/#add_data
2- adding a path to the local directories / files from the UI:
- From within a dataset, click “Add data”
- Then select the “Use local data” tab
- Then enter the path(s) in the input box
With either option, Remo will link to your data in your server.
Thanks a lot for the suggestions!
Re documentation - great point.
We didn’t expand on it is because we are not explicitly supporting running Remo on cloud servers yet. We actually just enabled ngrok to support the Colab use case. But as you found out, it works
Since you are using it, we will expand on the explanation on running on a server using ngrok and the config file in the next release - will keep you posted.
We will also be releasing a paid version with official support at some point - allowing for users authentication (so you can control who access your data) and faster loading (no need to tunnel with ngrok) + some other features.
Re data augmentation:
we actually thought about it, we decided to not do it for now because usually augmentation is done in memory and not saved to disk. Whereas Remo is meant more to deal with the core data (it links to the actual files).
Why would you want augmentation in Remo? to avoid writing the code, or to be able to visualize the data itself?
And would you be ok if Remo saved the augmented data to storage?
We were planning on enabling the creation of some datasets for self-supervised pretext tasks instead, as those are usually done on storage from what I have seen.