96 lines
3.5 KiB
Python
96 lines
3.5 KiB
Python
from typing import Dict, List, Optional, Tuple
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from ..types import Matrix, Point
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def perspective_calculate(
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imgwidth: int,
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imgheight: int,
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texwidth: int,
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texheight: int,
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transform: Matrix,
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camera: Point,
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focal_length: float,
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) -> Tuple[Optional[Matrix], int, int, int, int]:
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# Arbitrarily choose three points on the texture to create a pair of vectors
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# so that we can interpolate backwards. This isn't as simple as inverting the
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# view matrix like in affine compositing because dividing by Z makes the
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# perspective transform non-linear. So instead we interpolate 1/Z, u/Z and
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# v/Z since those ARE linear, and work backwards from there.
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xy: List[Point] = []
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uvz: Dict[Point, Point] = {}
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for (texx, texy) in [
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(0, 0),
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(texwidth, 0),
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(0, texheight),
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# Include this just to get a good upper bounds for where the texture
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# will be drawn.
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(texwidth, texheight),
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]:
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imgloc = transform.multiply_point(Point(texx, texy))
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distance = imgloc.z - camera.z
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imgx = ((imgloc.x - camera.x) * (focal_length / distance)) + camera.x
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imgy = ((imgloc.y - camera.y) * (focal_length / distance)) + camera.y
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xy_point = Point(imgx, imgy)
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xy.append(xy_point)
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uvz[xy_point] = Point(
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texx / distance,
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texy / distance,
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1 / distance,
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)
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# Calculate the maximum range of update this texture can possibly reside in.
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minx = max(int(min(p.x for p in xy)), 0)
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maxx = min(int(max(p.x for p in xy)) + 1, imgwidth)
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miny = max(int(min(p.y for p in xy)), 0)
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maxy = min(int(max(p.y for p in xy)) + 1, imgheight)
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if maxx <= minx or maxy <= miny:
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# This image is entirely off the screen!
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return (None, minx, miny, maxx, maxy)
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# Now that we have three points, construct a matrix that allows us to calculate
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# what amount of each u/z, v/z and 1/z vector we need to interpolate values. The
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# below matrix gives us an affine transform that will convert a point that's in
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# the range 0, 0 to 1, 1 to a point inside the parallellogram that is made by
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# projecting the two vectors we got from calculating the three texture points above.
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xy_matrix = Matrix.affine(
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a=xy[1].x - xy[0].x,
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b=xy[1].y - xy[0].y,
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c=xy[2].x - xy[0].x,
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d=xy[2].y - xy[0].y,
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tx=xy[0].x,
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ty=xy[0].y,
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)
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# We invert that above, which gives us a matrix that can take screen space (imgx,
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# imgy) and gives us instead those ratios, which allows us to then interpolate the
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# u/z, v/z and 1/z values.
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try:
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xy_matrix = xy_matrix.inverse()
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except ZeroDivisionError:
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# This can't be inverted, so this shouldn't be displayed.
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return (None, minx, miny, maxx, maxy)
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# We construct a second matrix, which interpolates coordinates in the range of
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# 0, 0 to 1, 1 and gives us back the u/z, v/z and 1/z values.
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uvz_matrix = Matrix(
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a11=uvz[xy[1]].x - uvz[xy[0]].x,
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a12=uvz[xy[1]].y - uvz[xy[0]].y,
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a13=uvz[xy[1]].z - uvz[xy[0]].z,
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a21=uvz[xy[2]].x - uvz[xy[0]].x,
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a22=uvz[xy[2]].y - uvz[xy[0]].y,
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a23=uvz[xy[2]].z - uvz[xy[0]].z,
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a31=0.0,
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a32=0.0,
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a33=0.0,
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a41=uvz[xy[0]].x,
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a42=uvz[xy[0]].y,
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a43=uvz[xy[0]].z,
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)
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# Finally, we can combine the two matrixes to do the interpolation all at once.
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inverse_matrix = xy_matrix.multiply(uvz_matrix)
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return (inverse_matrix, minx, miny, maxx, maxy)
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