from argparse import ArgumentParser
from pathlib import Path

from ultralytics import YOLO


def parse_args():
    parser = ArgumentParser(description="Train YOLOv8 on this dataset.")
    parser.add_argument("--model", default="yolov8n.pt", help="Model or checkpoint path.")
    parser.add_argument("--epochs", type=int, default=100)
    parser.add_argument("--imgsz", type=int, default=640)
    parser.add_argument("--batch", type=int, default=8, help="Use -1 for automatic batch size.")
    parser.add_argument("--device", default="0", help="CUDA device such as 0, or cpu.")
    parser.add_argument("--workers", type=int, default=4)
    parser.add_argument("--patience", type=int, default=30)
    parser.add_argument("--name", default="yolov8n_acne")
    parser.add_argument("--resume", action="store_true", help="Resume from --model checkpoint.")
    return parser.parse_args()


def main():
    args = parse_args()
    root = Path(__file__).resolve().parent
    data = root / "data.yaml"

    if not data.is_file():
        raise FileNotFoundError(f"Dataset config not found: {data}")

    model = YOLO(args.model)
    model.train(
        data=str(data),
        epochs=args.epochs,
        imgsz=args.imgsz,
        batch=args.batch,
        device=args.device,
        workers=args.workers,
        patience=args.patience,
        project=str(root / "runs"),
        name=args.name,
        pretrained=True,
        cache=False,
        amp=True,
        plots=True,
        resume=args.resume,
    )


if __name__ == "__main__":
    main()