Using the API access lib, create a class that abstracts over a cache of the API. This class would take a path to a directory as an argument, and check the cache in that directory. Using the DB access lib, it will ensure that cache is complete. The cache should have the following layout:
db.csv: A CSV file with a table esk layout, linking pattern IDs and metadata
assets/{pattern id}: A directory of directories, where each subdirectory is named after a pattern ID. Inside of these directories are all images of that id. These images should be named patternid-center.jpg and so on for each image.
This will be used in the training process, to both train the model and generate an embeddings store.
Using the API access lib, create a class that abstracts over a cache of the API. This class would take a path to a directory as an argument, and check the cache in that directory. Using the DB access lib, it will ensure that cache is complete. The cache should have the following layout:
patternid-center.jpg
and so on for each image.This will be used in the training process, to both train the model and generate an embeddings store.