import argparse

from src.model_loader import load_food_classifier
from src.nutrition import load_calorie_db
from src.predict import predict_top_k
from src.preprocessing import load_rgb_image


def main() -> None:
    parser = argparse.ArgumentParser(description="Predict Indian food class for one image.")
    parser.add_argument("image", help="Path to an input image")
    parser.add_argument("--top-k", type=int, default=3, help="Number of predictions to show")
    args = parser.parse_args()

    processor, model = load_food_classifier()
    calorie_db = load_calorie_db()
    image = load_rgb_image(args.image)

    for item in predict_top_k(image, processor, model, calorie_db, top_k=args.top_k):
        print(item)


if __name__ == "__main__":
    main()