"""图片处理流水线

处理流程：双页拆分 → 裁白边 → 缩放 → 灰度 → 对比度增强
各步骤均可通过 config 开关控制。
"""

from pathlib import Path

from PIL import Image, ImageEnhance, ImageOps

from kobo_manga.config import DeviceConfig, ProcessingConfig


class ImageProcessor:
    """图片处理器，将漫画原图优化为适合 e-ink 设备阅读的格式。"""

    def __init__(self, processing: ProcessingConfig, device: DeviceConfig):
        self.processing = processing
        self.device = device

    def process_image(self, img: Image.Image) -> list[Image.Image]:
        """执行完整处理流水线。

        返回列表是因为双页拆分可能产生 2 张图片。
        """
        images = [img]

        if self.processing.split_double_page:
            images = self._split_double_pages(images)

        result = []
        for im in images:
            if self.processing.crop_whitespace:
                im = self._crop_whitespace(im)
            if self.processing.resize:
                im = self._resize(im)
            if self.processing.grayscale and not self.device.color:
                im = self._grayscale(im)
            if self.processing.enhance_contrast:
                im = self._enhance_contrast(im)
            result.append(im)

        return result

    def process_chapter(
        self, image_paths: list[Path], output_dir: Path
    ) -> list[Path]:
        """处理整个章节的图片，返回输出文件路径列表。

        逐张处理以控制内存占用。
        """
        output_dir.mkdir(parents=True, exist_ok=True)
        output_paths = []
        page_num = 1

        for path in image_paths:
            img = Image.open(path)
            processed = self.process_image(img)
            img.close()

            for p_img in processed:
                out_path = output_dir / f"page_{page_num:03d}.jpg"
                # 灰度图保存为 L 模式 JPEG
                if p_img.mode == "L":
                    p_img.save(out_path, "JPEG", quality=85)
                else:
                    p_img.save(out_path, "JPEG", quality=85)
                p_img.close()
                output_paths.append(out_path)
                page_num += 1

        return output_paths

    # ── 流水线各步骤 ──────────────────────────────────────

    def _split_double_pages(
        self, images: list[Image.Image]
    ) -> list[Image.Image]:
        """检测并拆分双页。宽高比 > 1.2 视为双页。

        日漫从右往左读，所以右半页在前。
        """
        result = []
        for img in images:
            w, h = img.size
            if w > h * 1.2:
                mid = w // 2
                right = img.crop((mid, 0, w, h))
                left = img.crop((0, 0, mid, h))
                result.extend([right, left])
            else:
                result.append(img)
        return result

    def _crop_whitespace(self, img: Image.Image) -> Image.Image:
        """裁剪图片周围的白色/浅色边框。"""
        # 转灰度检测边界
        if img.mode == "RGBA":
            gray = img.convert("RGB").convert("L")
        else:
            gray = img.convert("L")

        # 反转后白边变黑(0)，getbbox() 找非零区域
        inverted = ImageOps.invert(gray)
        bbox = inverted.getbbox()

        if bbox is None:
            # 全白页，不裁剪
            return img

        # 安全检查：裁剪后面积不应小于原图 50%
        orig_area = img.size[0] * img.size[1]
        crop_w = bbox[2] - bbox[0]
        crop_h = bbox[3] - bbox[1]
        if crop_w * crop_h < orig_area * 0.5:
            return img

        # 加 2px margin
        margin = 2
        x0 = max(0, bbox[0] - margin)
        y0 = max(0, bbox[1] - margin)
        x1 = min(img.size[0], bbox[2] + margin)
        y1 = min(img.size[1], bbox[3] + margin)

        return img.crop((x0, y0, x1, y1))

    def _resize(self, img: Image.Image) -> Image.Image:
        """缩放到设备分辨率内，保持宽高比，只缩小不放大。"""
        w, h = img.size
        target_w = self.device.width
        target_h = self.device.height

        # 已经小于等于目标尺寸，不处理
        if w <= target_w and h <= target_h:
            return img

        scale = min(target_w / w, target_h / h)
        new_w = int(w * scale)
        new_h = int(h * scale)

        return img.resize((new_w, new_h), Image.Resampling.LANCZOS)

    def _grayscale(self, img: Image.Image) -> Image.Image:
        """转灰度。"""
        return img.convert("L")

    def _enhance_contrast(self, img: Image.Image) -> Image.Image:
        """增强对比度。"""
        enhancer = ImageEnhance.Contrast(img)
        return enhancer.enhance(self.processing.contrast_factor)