"""水印 去水印入口（由 ocr_utils.watermark_utils 迁入）。"""
from __future__ import annotations

import json
import re
from pathlib import Path
from typing import Any, Dict, Optional, Tuple, Union

import cv2
import numpy as np
from loguru import logger
from PIL import Image

from ocr_utils.watermark.algorithms import (
    _image_to_gray_and_bgr,
    remove_watermark_masked_adaptive,
)
from ocr_utils.watermark.contrast import apply_contrast_enhancement_config

def remove_watermark_from_image(
    image: Union[np.ndarray, Image.Image],
    threshold: int = 160,
    morph_close_kernel: int = 2,
    return_pil: Optional[bool] = None,
    watermark_removal_cfg: Optional[Dict[str, Any]] = None,
    removal_debug: Optional[Dict[str, Any]] = None,
) -> Union[np.ndarray, Image.Image]:
    """
    去除图像中的浅色斜向文字水印，返回灰度图。

    method（watermark_removal_cfg）:
        threshold（默认）: gray > threshold → 255
        masked / masked_adaptive: 掩膜 + 掩膜内动态阈值

    Args:
        image: 输入图像（PIL.Image 或 np.ndarray BGR/RGB/灰度）。
        threshold: 全局阈值或掩膜失败时的回退阈值。
        morph_close_kernel: 形态学闭运算核大小，0 跳过。
        watermark_removal_cfg: 完整配置（含 method / mask / adaptive）。
        removal_debug: 若传入 dict，写入掩膜与 T_wm 等调试字段。

    Returns:
        去除水印后的灰度图：PIL.Image(mode='L') 或 np.ndarray(HxW, uint8)。
    """
    input_is_pil = isinstance(image, Image.Image)
    cfg = watermark_removal_cfg or {}
    method = str(cfg.get("method") or "threshold").lower().strip()

    gray, bgr = _image_to_gray_and_bgr(image)

    if method in ("masked", "masked_adaptive"):
        cleaned, dbg = remove_watermark_masked_adaptive(
            gray,
            bgr=bgr,
            mask_cfg=cfg.get("mask") if isinstance(cfg.get("mask"), dict) else None,
            adaptive_cfg=cfg.get("adaptive")
            if isinstance(cfg.get("adaptive"), dict)
            else None,
            threshold_fallback=threshold,
            morph_close_kernel=morph_close_kernel,
        )
        if removal_debug is not None:
            removal_debug.clear()
            removal_debug.update(dbg)
    else:
        cleaned = gray.copy()
        cleaned[gray > threshold] = 255
        if morph_close_kernel > 0:
            kernel = np.ones((morph_close_kernel, morph_close_kernel), np.uint8)
            cleaned = cv2.morphologyEx(cleaned, cv2.MORPH_CLOSE, kernel)
        if removal_debug is not None:
            removal_debug.clear()
            removal_debug.update({"mode": "threshold", "threshold": threshold})

    should_return_pil = input_is_pil if return_pil is None else return_pil
    return Image.fromarray(cleaned, mode='L') if should_return_pil else cleaned


def remove_watermark_from_image_rgb(
    image: Union[np.ndarray, Image.Image],
    threshold: int = 160,
    morph_close_kernel: int = 2,
    return_pil: Optional[bool] = None,
    contrast_enhancement: Optional[Dict[str, Any]] = None,
    apply_watermark_removal: bool = True,
    watermark_removal_cfg: Optional[Dict[str, Any]] = None,
    removal_debug: Optional[Dict[str, Any]] = None,
) -> Union[np.ndarray, Image.Image]:
    """
    去除水印并返回 RGB 三通道图像。

    与 remove_watermark_from_image 逻辑相同，但输出为 RGB（三通道），
    方便直接传入布局检测、OCR 等需要彩色输入的下游模型。

    Args:
        contrast_enhancement: 对比度增强配置（含 enabled / method 等），见 apply_contrast_enhancement_config
        apply_watermark_removal: False 时跳过阈值抹白，仅做对比度增强（若启用）

    Args/Returns: 同 remove_watermark_from_image，但输出为 RGB/BGR 三通道。
    """
    input_is_pil = isinstance(image, Image.Image)

    if apply_watermark_removal:
        gray_result = remove_watermark_from_image(
            image,
            threshold,
            morph_close_kernel,
            return_pil=False,
            watermark_removal_cfg=watermark_removal_cfg,
            removal_debug=removal_debug,
        )
    else:
        if isinstance(image, Image.Image):
            np_img = np.array(image.convert("RGB"))
            np_img = cv2.cvtColor(np_img, cv2.COLOR_RGB2BGR)
        else:
            np_img = image.copy()
        gray_result = (
            cv2.cvtColor(np_img, cv2.COLOR_BGR2GRAY)
            if np_img.ndim == 3
            else np_img
        )

    gray_result = apply_contrast_enhancement_config(gray_result, contrast_enhancement)
    rgb_np = cv2.cvtColor(gray_result, cv2.COLOR_GRAY2BGR)

    should_return_pil = input_is_pil if return_pil is None else return_pil
    if should_return_pil:
        return Image.fromarray(cv2.cvtColor(rgb_np, cv2.COLOR_BGR2RGB))
    return rgb_np


def render_watermark_mask_overlay(
    image: np.ndarray,
    wm_mask: np.ndarray,
    *,
    color: Tuple[int, int, int] = (0, 0, 255),
    alpha: float = 0.45,
) -> np.ndarray:
    """在原图上叠加红色半透明水印掩膜，供调试图保存。"""
    if image.ndim == 2:
        base = cv2.cvtColor(image, cv2.COLOR_GRAY2BGR)
    elif image.shape[2] == 3:
        base = image.copy()
        if image.max() <= 1:
            base = (image * 255).astype(np.uint8)
    else:
        base = cv2.cvtColor(image, cv2.COLOR_BGRA2BGR)

    overlay = base.copy()
    overlay[wm_mask] = color
    return cv2.addWeighted(base, 1.0 - alpha, overlay, alpha, 0)