from light_training.preprocessing.preprocessors.preprocessor_mri import MultiModalityPreprocessor 
import argparse

data_filename = ["t2w.nii.gz",
                 "t2f.nii.gz",
                 "t1n.nii.gz",
                 "t1c.nii.gz"]
seg_filename = "seg.nii.gz"

def _parse_spacing(s: str):
    parts = [p.strip() for p in s.split(",") if p.strip()]
    if len(parts) != 3:
        raise ValueError(f"output_spacing should be like '1,1,1', got: {s}")
    return [float(parts[0]), float(parts[1]), float(parts[2])]


def main():
    parser = argparse.ArgumentParser(description="BraTS2023 preprocessing (resample/normalization/cropping).")
    parser.add_argument(
        "--base_dir",
        type=str,
        default="./data/raw_data/BraTS2023/",
        help="Base directory that contains the BraTS2023 image_dir folder.",
    )
    parser.add_argument(
        "--image_dir",
        type=str,
        default="ASNR-MICCAI-BraTS2023-GLI-Challenge-TrainingData",
        help="Folder name under base_dir.",
    )
    parser.add_argument(
        "--output_dir",
        type=str,
        default="./data/fullres/train/",
        help="Output directory for preprocessed npz/npy/pkl files.",
    )
    parser.add_argument(
        "--output_spacing",
        type=str,
        default="1,1,1",
        help="Target spacing, e.g. '1,1,1'.",
    )
    parser.add_argument(
        "--num_processes",
        type=int,
        default=8,
        help="Number of worker processes for preprocessing.",
    )
    parser.add_argument(
        "--only_plan",
        action="store_true",
        help="Only run planning (statistics) and exit.",
    )
    parser.add_argument(
        "--skip_plan",
        action="store_true",
        help="Skip planning step.",
    )
    args = parser.parse_args()

    preprocessor = MultiModalityPreprocessor(
        base_dir=args.base_dir,
        image_dir=args.image_dir,
        data_filenames=data_filename,
        seg_filename=seg_filename,
    )

    if not args.skip_plan:
        preprocessor.run_plan()
        if args.only_plan:
            return

    out_spacing = _parse_spacing(args.output_spacing)
    preprocessor.run(
        output_spacing=out_spacing,
        output_dir=args.output_dir,
        all_labels=[1, 2, 3],
        num_processes=args.num_processes,
    )


if __name__ == "__main__":
    main()