Training a Model on a Dataset

Training in anomalib always goes through anomalib.engine.Engine, which wraps a Lightning Trainer.

Python API — standard benchmark dataset (MVTecAD)

from anomalib.data import MVTecAD
from anomalib.models import Patchcore
from anomalib.engine import Engine

datamodule = MVTecAD(root="./datasets/MVTecAD", category="bottle", train_batch_size=32)
model = Patchcore()
engine = Engine()                      # any Lightning Trainer kwarg can go here
engine.fit(model=model, datamodule=datamodule)
results = engine.test(model=model, datamodule=datamodule)