The goal of anomaly detection is to recognize examples of an object that may fall out of a desired distribution of acceptable objects. For example, in manufacturing, we may want to automaticaly detect when some defect occurs.
This experiment uses a PaDiM model trained on wood. Training was done using the anomalib library.
pip install -r requirements.txt
python3 main.py