from vigilcv.core.drift import DriftEngine

engine = DriftEngine()
engine.fit(reference_directory="dataset/train/")
engine.save("baseline.pkl")

report = engine.detect(query_directory="dataset/new_batch/")

if report.is_drifted:
    print(f"DRIFT DETECTED: {report.wasserstein_distance:.4f} W1")

# Inspect a single image
vigilcv inspect photo.jpg --blur-threshold 150

# Audit a massive directory in parallel
vigilcv audit dataset/train/ --workers 16 --report quality_report.html

# Detect distribution drift against baseline
vigilcv drift dataset/new/ --baseline baselines/prod_v1.pkl --threshold 0.20