"""
水印处理门面：preset 解析、检测、去水印、对比度增强。
"""
from __future__ import annotations

from typing import Any, Dict, List, Optional, Tuple, Union

import numpy as np
from loguru import logger
from PIL import Image

from ocr_utils.watermark.algorithms import detect_watermark
from ocr_utils.watermark.presets import Scope, merge_watermark_config
from ocr_utils.watermark.removal import remove_watermark_from_image_rgb


class WatermarkProcessor:
    """页级 / 单元格级水印去除编排。"""

    def __init__(
        self,
        config: Dict[str, Any],
        *,
        scope: Scope = "page",
    ):
        self.scope = scope
        self.config = merge_watermark_config(scope, config)

    @classmethod
    def from_user_config(
        cls,
        user_cfg: Optional[Dict[str, Any]],
        *,
        scope: Scope = "page",
    ) -> "WatermarkProcessor":
        return cls(user_cfg or {}, scope=scope)

    @property
    def enabled(self) -> bool:
        return bool(self.config.get("enabled", False))

    @property
    def method(self) -> str:
        return str(self.config.get("method") or "masked_adaptive")

    @property
    def threshold(self) -> int:
        return int(self.config.get("threshold", 155))

    @property
    def morph_close_kernel(self) -> int:
        return int(self.config.get("morph_close_kernel", 0))

    def contrast_config(self) -> Optional[Dict[str, Any]]:
        ce = self.config.get("contrast_enhancement")
        if not isinstance(ce, dict):
            return None
        if not ce.get("enabled", False):
            return None
        return dict(ce)

    def should_apply(self, image: Union[np.ndarray, Image.Image]) -> bool:
        if not self.enabled:
            return False
        if not bool(self.config.get("detect_before_remove", True)):
            return True

        detect_cfg = self.config.get("detect")
        if not isinstance(detect_cfg, dict):
            detect_cfg = {}

        angle_range = detect_cfg.get("diagonal_angle_range", (30, 60))
        if isinstance(angle_range, list):
            angle_range = tuple(angle_range)

        return detect_watermark(
            image,
            midtone_low=int(detect_cfg.get("midtone_low", 100)),
            midtone_high=int(detect_cfg.get("midtone_high", 220)),
            ratio_threshold=float(detect_cfg.get("ratio_threshold", 0.025)),
            check_diagonal=bool(detect_cfg.get("check_diagonal", True)),
            diagonal_angle_range=angle_range,
        )

    def process(
        self,
        image: Union[np.ndarray, Image.Image],
        *,
        apply_removal: Optional[bool] = None,
        apply_contrast: Optional[bool] = None,
        contrast_override: Optional[Dict[str, Any]] = None,
        removal_debug: Optional[Dict[str, Any]] = None,
        force: bool = False,
    ) -> Tuple[np.ndarray, List[str]]:
        """
        去水印 + 可选对比度增强。

        Returns:
            (BGR ndarray, preprocess_stages)
        """
        stages: List[str] = []
        if isinstance(image, Image.Image):
            img = np.array(image.convert("RGB"))
            img = img[:, :, ::-1].copy()  # RGB -> BGR
        else:
            img = np.array(image)
            if img.ndim == 2:
                img = np.stack([img, img, img], axis=-1)

        do_remove = apply_removal if apply_removal is not None else self.enabled
        if do_remove and not force and not self.should_apply(img):
            do_remove = False

        if contrast_override is not None:
            contrast_cfg = dict(contrast_override)
            if apply_contrast is not False and not contrast_cfg.get("enabled", True):
                contrast_cfg["enabled"] = True
        else:
            contrast_cfg = self.contrast_config()
        if apply_contrast is False:
            contrast_cfg = None
        elif apply_contrast is True and contrast_cfg is None:
            ce = self.config.get("contrast_enhancement") or {}
            if isinstance(ce, dict) and ce.get("method"):
                contrast_cfg = dict(ce)
                contrast_cfg["enabled"] = True

        if not do_remove and not contrast_cfg:
            return img, stages

        try:
            if do_remove:
                stages.append("wm")
            if contrast_cfg:
                stages.append("contrast")

            cleaned = remove_watermark_from_image_rgb(
                img,
                threshold=self.threshold,
                morph_close_kernel=self.morph_close_kernel,
                return_pil=False,
                contrast_enhancement=contrast_cfg,
                apply_watermark_removal=do_remove,
                watermark_removal_cfg=self.config,
                removal_debug=removal_debug,
            )
            return np.asarray(cleaned), stages
        except Exception as e:
            logger.warning(f"WatermarkProcessor.process failed (scope={self.scope}): {e}")
            return img, stages

    def get_full_config(self) -> Dict[str, Any]:
        return dict(self.config)