42 lines
1.4 KiB
Python
42 lines
1.4 KiB
Python
"""Classic inpainting restorer (cv2) — the always-available baseline.
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HONEST LIMITATION: cv2 inpainting fills the masked region by propagating
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surrounding pixels. It removes the mosaic/bar but does NOT reconstruct the hidden
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detail — it smooths/guesses. For real reconstruction a generative model
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(DeepMosaics / LADA) is needed; this is the no-weights, no-GPU fallback so the
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"Расцензурить кадр" flow works end-to-end today.
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"""
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from __future__ import annotations
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import cv2
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import numpy as np
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from ..detection.types import Detection
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from .base import CancelCheck, Restorer
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from .mask import detections_to_mask
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class InpaintRestorer(Restorer):
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def __init__(self, radius: int = 3, dilate: int = 2, method: str = "telea") -> None:
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self.radius = radius
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self.dilate = dilate
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self.method = method
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@property
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def name(self) -> str:
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return f"InpaintRestorer({self.method})"
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def restore(
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self,
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image: np.ndarray,
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detections: list[Detection],
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should_cancel: CancelCheck | None = None,
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) -> np.ndarray:
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# Single cv2.inpaint call — effectively instant, so cancellation is moot.
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if not detections:
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return image.copy()
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mask = detections_to_mask(image.shape, detections, dilate=self.dilate)
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flags = cv2.INPAINT_TELEA if self.method == "telea" else cv2.INPAINT_NS
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return cv2.inpaint(image, mask, self.radius, flags)
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