import os

from watermark_verify.inference import rcnn
from watermark_verify import logger
from watermark_verify.tools import secret_label_func, qrcode_tool, general_tool, parse_qrcode_label_file


def label_verification(model_filename: str) -> bool:
    """
    模型标签提取验证
    :param model_filename: 模型权重文件，onnx格式
    :return: 模型标签验证结果
    """
    if not os.path.exists(model_filename):
        logger.error(f"model_filename={model_filename}指定模型权重文件不存在")
        raise FileNotFoundError("指定模型权重文件不存在")
    file_extension = general_tool.get_file_extension(model_filename)
    if file_extension != "onnx":
        logger.error(f"模型权重文件格式不合法")
        raise RuntimeError(f"模型权重文件格式不合法")
    root_dir = os.path.dirname(model_filename)
    logger.info(f"开始检测模型水印, model_filename: {model_filename}, root_dir: {root_dir}")
    # step 1 获取触发集目录，公钥信息
    trigger_dir = os.path.join(root_dir, 'trigger')
    public_key_txt = os.path.join(root_dir, 'keys', 'public.key')
    if not os.path.exists(trigger_dir):
        logger.error(f"trigger_dir={trigger_dir}, 触发集目录不存在")
        raise FileNotFoundError("触发集目录不存在")
    if not os.path.exists(public_key_txt):
        logger.error(f"public_key_txt={public_key_txt}, 签名公钥文件不存在")
        raise FileNotFoundError("签名公钥文件不存在")
    with open(public_key_txt, 'r') as file:
        public_key = file.read()
    logger.debug(f"trigger_dir={trigger_dir}, public_key_txt={public_key_txt}, public_key={public_key}")
    if not public_key or public_key == '':
        logger.error(f"获取的签名公钥信息为空, public_key={public_key}")
        raise RuntimeError("获取的签名公钥信息为空")
    qrcode_positions_file = os.path.join(trigger_dir, 'qrcode_positions.txt')
    if not os.path.exists(qrcode_positions_file):
        raise FileNotFoundError("二维码标签文件不存在")

    # step 2 获取权重文件，使用触发集进行模型推理, 将推理结果与触发集预先二维码保存位置进行比对，在误差范围内则进行下一步，否则返回False
    watermark_detect_result = False
    cls_image_mapping = parse_qrcode_label_file.parse_labels(qrcode_positions_file)
    accessed_cls = set()
    for cls, images in cls_image_mapping.items():
        for image in images:
            image_path = os.path.join(trigger_dir, image)
            try:
                detect_result = rcnn.predict_and_detect(image_path, model_filename, qrcode_positions_file, (600, 600))
            except Exception as e:
                continue
            if detect_result:
                accessed_cls.add(cls)
                break
    if accessed_cls == set(cls_image_mapping.keys()):  # 所有的分类都检测出模型水印，模型水印检测结果为True
        watermark_detect_result = True

    if not watermark_detect_result:  # 如果没有从模型中检测出黑盒水印，直接返回验证失败
        return False

    # step 3 从触发集图片中提取密码标签，进行验签
    secret_label = extract_crypto_label_from_trigger(trigger_dir)
    label_check_result = secret_label_func.verify_secret_label(secret_label=secret_label, public_key=public_key)
    return label_check_result


def extract_crypto_label_from_trigger(trigger_dir: str):
    """
    从触发集中提取密码标签
    :param trigger_dir: 触发集目录
    :return: 密码标签
    """
    # Initialize variables to store the paths
    image_folder_path = None
    qrcode_positions_file_path = None
    label = ''

    # Walk through the extracted folder to find the specific folder and file
    for root, dirs, files in os.walk(trigger_dir):
        if 'images' in dirs:
            image_folder_path = os.path.join(root, 'images')
        if 'qrcode_positions.txt' in files:
            qrcode_positions_file_path = os.path.join(root, 'qrcode_positions.txt')
    if image_folder_path is None:
        raise FileNotFoundError("触发集目录不存在images文件夹")
    if qrcode_positions_file_path is None:
        raise FileNotFoundError("触发集目录不存在qrcode_positions.txt")

    sub_image_dir_names = os.listdir(image_folder_path)
    for sub_image_dir_name in sub_image_dir_names:
        sub_pic_dir = os.path.join(image_folder_path, sub_image_dir_name)
        images = os.listdir(sub_pic_dir)
        for image in images:
            img_path = os.path.join(sub_pic_dir, image)
            watermark_box = parse_qrcode_label_file.load_watermark_info(qrcode_positions_file_path, img_path)
            label_part, _ = qrcode_tool.detect_and_decode_qr_code(img_path, watermark_box)
            if label_part is not None:
                label = label + label_part
                break
    return label