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jakowenko avatar jakowenko commented on May 16, 2024 1

Rescanning when the API hits is what I was leaning towards for now too. That should be easy to fix and get in.

My only logic in keeping the training files is that it makes it easy to retrain in the future or if the user ends up using a new detector, all those images are still available on the disk for the user to easily queue back up.

from double-take.

jakowenko avatar jakowenko commented on May 16, 2024

You're right, this is a known issue and was something I overlooked when I worked on the feature. I wonder if it makes sense to implement some sort of file watcher like chokidar or to just rescan the folder when the /train route is hit. Do you have any opinions?

from double-take.

erikarenhill avatar erikarenhill commented on May 16, 2024

I was thinking a rescan of the folder on the API hit is enough as it shouldnt be hit so often to cause problems, at least that's a starter?

My initial thought from another point of view was actually that the train/add endpoint could actually delete the files after they have been trained, that way no database/file scan is needed at all. Does that make sense? Or do you want to keep the training database to easily train another service (e.g. running compreface but also want to add deepstack and easily put the same dataset into deepstack)

from double-take.

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