from __future__ import annotations

import numpy as np

from .deps import require_cv2
from .settings import TrimapSettings


def radius_from_ratio(shape: tuple[int, int], ratio: float, minimum: int) -> int:
    return max(minimum, int(round(max(shape) * ratio)))


def elliptical_kernel(radius: int) -> np.ndarray:
    cv2 = require_cv2()
    size = radius * 2 + 1
    return cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (size, size))


def generate_trimap(
    bg_confidence: np.ndarray, settings: TrimapSettings
) -> tuple[np.ndarray, dict[str, int]]:
    cv2 = require_cv2()
    shape = bg_confidence.shape
    unknown_radius = radius_from_ratio(
        shape, settings.unknown_radius_ratio, settings.min_unknown_radius
    )
    fg_safe_radius = radius_from_ratio(
        shape, settings.fg_safe_radius_ratio, settings.min_fg_safe_radius
    )

    sure_bg = bg_confidence >= settings.sure_bg_threshold
    low_bg = bg_confidence <= settings.sure_fg_threshold

    bg_u8 = sure_bg.astype(np.uint8)
    unknown_band = cv2.dilate(bg_u8, elliptical_kernel(unknown_radius)).astype(bool)
    fg_safe = ~cv2.dilate(bg_u8, elliptical_kernel(fg_safe_radius)).astype(bool)
    sure_fg = low_bg & fg_safe

    trimap = np.full(shape, 128, dtype=np.uint8)
    trimap[sure_bg] = 0
    trimap[sure_fg] = 255

    # Keep a protective unknown band around all sure background, including holes.
    trimap[unknown_band & ~sure_bg & ~sure_fg] = 128

    stats = {
        "sure_bg_pixels": int((trimap == 0).sum()),
        "unknown_pixels": int((trimap == 128).sum()),
        "sure_fg_pixels": int((trimap == 255).sum()),
        "unknown_radius": int(unknown_radius),
        "fg_safe_radius": int(fg_safe_radius),
    }
    return trimap, stats


def fuse_trimap(
    seg_mask: np.ndarray, bg_confidence: np.ndarray, settings: TrimapSettings
) -> tuple[np.ndarray, dict[str, int]]:
    """Build a trimap from a semantic subject mask, refined by the green key.

    Authority split: the segmentation mask decides subject *topology* (it keeps
    colour-contaminated hair as foreground and drops see-through holes), while the
    bright-green chroma key sharpens the screen boundary. ViTMatte then refines
    the unknown band.
    """
    cv2 = require_cv2()
    shape = seg_mask.shape
    fg_safe_radius = radius_from_ratio(
        shape, settings.fg_safe_radius_ratio, settings.min_fg_safe_radius
    )
    band_radius = max(settings.min_fg_safe_radius, fg_safe_radius // 2)

    green_bg = bg_confidence >= settings.sure_bg_threshold       # bright clean screen
    core = (seg_mask >= settings.seg_core_threshold).astype(np.uint8)
    loose = (seg_mask >= settings.seg_loose_threshold).astype(np.uint8)

    # A small protective band around the mask boundary lets ViTMatte anti-alias
    # crisp edges; hair gets extra width from BiRefNet's own soft region. The band
    # is deliberately small so it does not swallow small holes (finger gaps).
    kernel = elliptical_kernel(band_radius)
    band = cv2.dilate(loose, kernel).astype(bool) & ~cv2.erode(loose, kernel).astype(bool)

    # Background follows the mask directly so interior holes stay background, minus
    # the boundary band; foreground is the confident subject, never bright screen.
    sure_fg = core.astype(bool) & ~band & ~green_bg
    sure_bg = ((loose == 0) & ~band) | (green_bg & (loose == 0))

    trimap = np.full(shape, 128, dtype=np.uint8)
    trimap[sure_bg] = 0
    trimap[sure_fg] = 255

    stats = {
        "sure_bg_pixels": int((trimap == 0).sum()),
        "unknown_pixels": int((trimap == 128).sum()),
        "sure_fg_pixels": int((trimap == 255).sum()),
        "band_radius": int(band_radius),
        "fg_safe_radius": int(fg_safe_radius),
        "seg_subject_pixels": int((core > 0).sum()),
    }
    return trimap, stats


def trimap_to_alpha_seed(trimap: np.ndarray, bg_confidence: np.ndarray) -> np.ndarray:
    alpha = np.clip(1.0 - bg_confidence, 0.0, 1.0).astype(np.float32)
    alpha[trimap == 0] = 0.0
    alpha[trimap == 255] = 1.0
    return alpha