41 lines
1.1 KiB
Python
41 lines
1.1 KiB
Python
from logging import getLogger
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from typing import Optional
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import cv2
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from PIL import Image
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from ..params import ImageParams, SizeChart, StageParams
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from ..server import ServerContext
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from ..worker import ProgressCallback, WorkerContext
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from .base import BaseStage
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from .result import StageResult
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logger = getLogger(__name__)
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class BlendDenoiseFastNLMeansStage(BaseStage):
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max_tile = SizeChart.max
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def run(
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self,
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_worker: WorkerContext,
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_server: ServerContext,
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_stage: StageParams,
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_params: ImageParams,
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sources: StageResult,
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*,
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strength: int = 3,
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stage_source: Optional[Image.Image] = None,
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callback: Optional[ProgressCallback] = None,
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**kwargs,
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) -> StageResult:
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logger.info("denoising source images")
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results = []
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for source in sources.as_arrays():
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data = cv2.cvtColor(source, cv2.COLOR_RGB2BGR)
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data = cv2.fastNlMeansDenoisingColored(data, None, strength, strength)
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results.append(cv2.cvtColor(data, cv2.COLOR_BGR2RGB))
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return StageResult.from_arrays(results, metadata=sources.metadata)
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