====== Common Machine Learning API ======



===== V5 Services =====

New services should be deployed to tower01 if possible since this is the only machine with GPU Support.


==== Model ====

We use a new model: https://github.com/facebookresearch/deit/


==== Training Data ====

All datasets will be stored at ''%%sg01:/var/www/picalike.corpex-kunden.de/sg01/htdocs/ml_data%%'' The folder structure is as follows ''%%$root/$service_name/$date%%''

The content of the folder MUST contain:\\
A file with one URL per line for each class\\
A sqlite with the image data (3,224,224) as a backup.\\



===== Models =====



==== sheego: Size Table Detector ====

sg01:/var/www/picalike.corpex-kunden.de/sg01/htdocs/ml_data/size_table


==== detector: Person ====

sg01:/var/www/picalike.corpex-kunden.de/sg01/htdocs/ml_data/person


==== detector: Freigestellt ====

sg01:/var/www/picalike.corpex-kunden.de/sg01/htdocs/ml_data/freigestellt


===== tower01 =====

A task is to update the OS of the machine to allow Docker + cuda + Pytorch. But since this is a bigger task, new v5 services will run in CPU-only mode for now.


==== ML API ====

A service should provide an endpoint (POST). The input is a list of URLs.\\
In case of a 2-class service, the result should be a dictionary with URL→{True,False}.