"""Classic inpainting restorer (cv2) — the always-available baseline.

HONEST LIMITATION: cv2 inpainting fills the masked region by propagating
surrounding pixels. It removes the mosaic/bar but does NOT reconstruct the hidden
detail — it smooths/guesses. For real reconstruction a generative model
(DeepMosaics / LADA) is needed; this is the no-weights, no-GPU fallback so the
"Расцензурить кадр" flow works end-to-end today.
"""

from __future__ import annotations

import cv2
import numpy as np

from ..detection.types import Detection
from .base import CancelCheck, Restorer
from .mask import detections_to_mask


class InpaintRestorer(Restorer):
    def __init__(self, radius: int = 3, dilate: int = 2, method: str = "telea") -> None:
        self.radius = radius
        self.dilate = dilate
        self.method = method

    @property
    def name(self) -> str:
        return f"InpaintRestorer({self.method})"

    def restore(
        self,
        image: np.ndarray,
        detections: list[Detection],
        should_cancel: CancelCheck | None = None,
    ) -> np.ndarray:
        # Single cv2.inpaint call — effectively instant, so cancellation is moot.
        if not detections:
            return image.copy()
        mask = detections_to_mask(image.shape, detections, dilate=self.dilate)
        flags = cv2.INPAINT_TELEA if self.method == "telea" else cv2.INPAINT_NS
        return cv2.inpaint(image, mask, self.radius, flags)