#!/usr/bin/env python3
"""
utils package (lightweight __init__)
- Export only light helpers/consts at import time
- Provide LAZY wrappers for heavy CV functions so legacy imports still work:
    from utils import segment_person_hq  -> OK (resolved at call time)
"""

from __future__ import annotations

import os
import logging
from typing import Dict, Any, Tuple, Optional

# import numpy as np  # light; OK at import time

logger = logging.getLogger(__name__)

# ---------------------------------------------------------------------
# Background presets & builders (lightweight)
# ---------------------------------------------------------------------

PROFESSIONAL_BACKGROUNDS: Dict[str, Dict[str, Any]] = {
    "office":   {"color": (240, 248, 255), "gradient": True},
    "studio":   {"color": (32, 32, 32),    "gradient": False},
    "nature":   {"color": (34, 139, 34),   "gradient": True},
    "abstract": {"color": (75, 0, 130),    "gradient": True},
    "white":    {"color": (255, 255, 255), "gradient": False},
    "black":    {"color": (0, 0, 0),       "gradient": False},
    # add more if you like
}

def _solid_bg(color: Tuple[int,int,int], width: int, height: int) -> np.ndarray:
    return np.full((height, width, 3), tuple(int(x) for x in color), dtype=np.uint8)

def _vertical_gradient(top: Tuple[int,int,int], bottom: Tuple[int,int,int], width: int, height: int) -> np.ndarray:
    bg = np.zeros((height, width, 3), dtype=np.uint8)
    for y in range(height):
        t = y / max(1, height - 1)
        r = int(top[0] * (1 - t) + bottom[0] * t)
        g = int(top[1] * (1 - t) + bottom[1] * t)
        b = int(top[2] * (1 - t) + bottom[2] * t)
        bg[y, :] = (r, g, b)
    return bg

def create_professional_background(key_or_cfg: Any, width: int, height: int) -> np.ndarray:
    """
    Accepts either:
      - string key in PROFESSIONAL_BACKGROUNDS
      - a config dict with {"color": (r,g,b), "gradient": bool}
    Returns RGB uint8 background (H, W, 3).
    """
    if isinstance(key_or_cfg, str):
        cfg = PROFESSIONAL_BACKGROUNDS.get(key_or_cfg, PROFESSIONAL_BACKGROUNDS["office"])
    elif isinstance(key_or_cfg, dict):
        cfg = key_or_cfg
    else:
        cfg = PROFESSIONAL_BACKGROUNDS["office"]

    color = tuple(int(x) for x in cfg.get("color", (255, 255, 255)))
    use_grad = bool(cfg.get("gradient", False))

    if not use_grad:
        return _solid_bg(color, width, height)

    # simple vertical gradient dark->color
    dark = (int(color[0]*0.7), int(color[1]*0.7), int(color[2]*0.7))
    return _vertical_gradient(dark, color, width, height)

def create_gradient_background(spec: Dict[str, Any], width: int, height: int) -> np.ndarray:
    """
    spec: {"type": "linear"|"radial", "start": (r,g,b)|"#RRGGBB", "end": (r,g,b)|"#RRGGBB", "angle_deg": float}
    Returns RGB uint8 background (H, W, 3). (Radial treated as linear fallback unless extended.)
    """
    import re
    import cv2  # import locally to keep top-level light

    def _to_rgb(c):
        if isinstance(c, (list, tuple)) and len(c) == 3:
            return tuple(int(x) for x in c)
        if isinstance(c, str) and re.match(r"^#[0-9a-fA-F]{6}$", c):
            return tuple(int(c[i:i+2], 16) for i in (1,3,5))
        return (255, 255, 255)

    start = _to_rgb(spec.get("start", (32, 32, 32)))
    end   = _to_rgb(spec.get("end", (200, 200, 200)))
    angle = float(spec.get("angle_deg", 0.0))

    bg = _vertical_gradient(start, end, width, height)

    # rotate by angle
    center = (width / 2, height / 2)
    rot = cv2.getRotationMatrix2D(center, angle, 1.0)
    bg = cv2.warpAffine(bg, rot, (width, height), flags=cv2.INTER_LINEAR, borderMode=cv2.BORDER_REFLECT_101)
    return bg

# ---------------------------------------------------------------------
# Video validation (lightweight)
# ---------------------------------------------------------------------
def validate_video_file(video_path: str) -> bool:
    """
    Fast sanity check: file exists, cv2 can open, first frame is readable.
    Returns True/False (lightweight for UI).
    """
    try:
        if not video_path or not os.path.exists(video_path):
            return False
        import cv2  # local import
        cap = cv2.VideoCapture(video_path)
        if not cap.isOpened():
            return False
        ok, frame = cap.read()
        cap.release()
        return bool(ok and frame is not None)
    except Exception as e:
        logger.warning("validate_video_file error: %s", e)
        return False

def validate_video_file_detail(video_path: str) -> Tuple[bool, str]:
    if not video_path:
        return False, "No path provided"
    if not os.path.exists(video_path):
        return False, "File does not exist"
    try:
        import cv2
        cap = cv2.VideoCapture(video_path)
        if not cap.isOpened():
            return False, "cv2 could not open file"
        ok, frame = cap.read()
        cap.release()
        if not ok or frame is None:
            return False, "Could not read first frame"
        return True, "OK"
    except Exception as e:
        return False, f"cv2 error: {e}"

# ---------------------------------------------------------------------
# LAZY WRAPPERS (avoid importing utils.cv_processing at module import time)
# ---------------------------------------------------------------------
def segment_person_hq(*args, **kwargs):
    from .cv_processing import segment_person_hq as _f
    return _f(*args, **kwargs)

def refine_mask_hq(*args, **kwargs):
    from .cv_processing import refine_mask_hq as _f
    return _f(*args, **kwargs)

def replace_background_hq(*args, **kwargs):
    from .cv_processing import replace_background_hq as _f
    return _f(*args, **kwargs)

__all__ = [
    # backgrounds
    "PROFESSIONAL_BACKGROUNDS",
    "create_professional_background",
    "create_gradient_background",
    # validation
    "validate_video_file",
    "validate_video_file_detail",
    # lazy CV exports (back-compat)
    "segment_person_hq",
    "refine_mask_hq",
    "replace_background_hq",
]