#!/usr/bin/env python3
from PIL import Image
import os
import argparse
import sys
from roi_lib import *

def parse_args():
    parser = argparse.ArgumentParser(description='ROI prediction')
    parser.add_argument('--model', type=str, required=True, help='model path')
    parser.add_argument('image', nargs='+', type=str, help='image file')
    return parser.parse_args()

# 主函数
def main():
    args = parse_args()
    model = load_model(args.model)
    ret = 0
    for image_path in args.image:
        image_tensor = preprocess_image(image_path)
        predicted_class, probabilities = predict(model, image_tensor)
        print(f'{image_path} predicted={predicted_class} prob={probabilities}')
        if predicted_class == 1:
            print("verify ok")
        else:
            print("verify ng")
            ret = 1
    return ret

if __name__ == '__main__':
    sys.exit(main())