matei jordache
d4c5cf4670
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76 lines
2.2 KiB
Python
76 lines
2.2 KiB
Python
"""Level Rotate — level by physically rotating the data plane."""
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from __future__ import annotations
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import numpy as np
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from scipy.ndimage import map_coordinates
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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="Level Rotate")
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class LevelRotate:
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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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}
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}
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OUTPUTS = (
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('DATA_FIELD', 'leveled'),
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)
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FUNCTION = "process"
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DESCRIPTION = (
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"Level by physically rotating the data plane. Fits a best-fit plane, "
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"converts its slopes to tilt angles, then rotates the surface by "
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"those angles using interpolation rather than algebraic subtraction."
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)
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KEYWORDS = ("rotate", "tilt", "level", "plane")
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def process(self, field: DataField) -> tuple:
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data = np.asarray(field.data, dtype=np.float64)
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yres, xres = data.shape
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# Fit plane: z = a + bx*x + by*y (x,y in pixel coords)
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yy, xx = np.mgrid[:yres, :xres].astype(np.float64)
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A = np.column_stack([np.ones(yres * xres), xx.ravel(), yy.ravel()])
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coeffs, _, _, _ = np.linalg.lstsq(A, data.ravel(), rcond=None)
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_, bx, by = coeffs
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# Convert pixel slopes to tilt angles
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alpha_x = np.arctan(bx)
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alpha_y = np.arctan(by)
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# Build rotation: for each output pixel, find where it came from
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cx = (xres - 1) / 2.0
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cy = (yres - 1) / 2.0
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cos_x = np.cos(alpha_x)
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cos_y = np.cos(alpha_y)
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# Source coordinates after removing tilt
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src_x = xx.copy()
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src_y = yy.copy()
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src_z = data.copy()
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# Rotate about x-axis (corrects y-tilt)
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dy = yy - cy
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src_y_rot = cy + dy * cos_y
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src_z = src_z - dy * np.sin(alpha_y)
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# Rotate about y-axis (corrects x-tilt)
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dx = xx - cx
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src_x_rot = cx + dx * cos_x
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src_z = src_z - dx * np.sin(alpha_x)
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# Resample with the adjusted z values
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result = map_coordinates(src_z, [src_y_rot, src_x_rot], order=1,
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mode='nearest')
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return (field.replace(data=result),)
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