66 lines
2.3 KiB
Python
66 lines
2.3 KiB
Python
from __future__ import annotations
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import numpy as np
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from backend.node_registry import register_node
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from backend.data_types import DataField
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@register_node(display_name="Local Contrast")
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class LocalContrast:
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@classmethod
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def INPUT_TYPES(cls):
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return {
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"required": {
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"field": ("DATA_FIELD",),
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"kernel_size": ("INT", {"default": 10, "min": 2, "max": 100}),
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"weight": ("FLOAT", {"default": 0.5, "min": 0.0, "max": 1.0, "step": 0.05}),
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}
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}
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OUTPUTS = (
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('DATA_FIELD', 'result'),
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)
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FUNCTION = "process"
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DESCRIPTION = (
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"Expand the local dynamic range at each pixel. "
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"Reveals fine surface features that are hidden by global contrast range. "
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)
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KEYWORDS = ("clahe", "enhance", "adaptive", "dynamic range")
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def process(self, field: DataField, kernel_size: int, weight: float) -> tuple:
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from scipy.ndimage import minimum_filter, maximum_filter
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data = np.asarray(field.data, dtype=np.float64)
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kernel_size = max(2, int(kernel_size))
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weight = float(np.clip(weight, 0.0, 1.0))
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local_min = minimum_filter(data, size=kernel_size, mode="reflect")
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local_max = maximum_filter(data, size=kernel_size, mode="reflect")
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global_min = float(data.min())
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global_max = float(data.max())
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local_range = local_max - local_min
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eps = np.finfo(np.float64).eps * max(abs(global_max), abs(global_min), 1.0)
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# Remap each pixel from its local range to the global range.
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# Where local_range is near zero, the pixel is already flat: leave it
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# unchanged (enhancement factor = 1).
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safe_range = np.where(local_range > eps, local_range, 1.0)
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global_span = global_max - global_min
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if global_span <= eps:
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# Uniform field - nothing to enhance.
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return (field.replace(data=data.copy()),)
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enhancement_factor = global_span / safe_range
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# Locally enhanced value: remap v from [local_min, local_max] → [global_min, global_max]
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v_enhanced = global_min + enhancement_factor * (data - local_min)
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# Blend between original and enhanced.
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result = (1.0 - weight) * data + weight * v_enhanced
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return (field.replace(data=result),)
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