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https://git.mirrors.martin98.com/https://github.com/Ultimaker/Cura
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143 lines
6.5 KiB
Python
143 lines
6.5 KiB
Python
# Copyright (c) 2019 Ultimaker B.V.
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# Cura is released under the terms of the LGPLv3 or higher.
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import numpy
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import copy
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from typing import Optional, Tuple, TYPE_CHECKING
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from UM.Math.Polygon import Polygon
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if TYPE_CHECKING:
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from UM.Scene.SceneNode import SceneNode
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## Polygon representation as an array for use with Arrange
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class ShapeArray:
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def __init__(self, arr: numpy.array, offset_x: float, offset_y: float, scale: float = 1) -> None:
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self.arr = arr
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self.offset_x = offset_x
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self.offset_y = offset_y
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self.scale = scale
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## Instantiate from a bunch of vertices
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# \param vertices
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# \param scale scale the coordinates
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@classmethod
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def fromPolygon(cls, vertices: numpy.array, scale: float = 1) -> "ShapeArray":
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# scale
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vertices = vertices * scale
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# flip y, x -> x, y
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flip_vertices = numpy.zeros((vertices.shape))
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flip_vertices[:, 0] = vertices[:, 1]
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flip_vertices[:, 1] = vertices[:, 0]
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flip_vertices = flip_vertices[::-1]
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# offset, we want that all coordinates have positive values
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offset_y = int(numpy.amin(flip_vertices[:, 0]))
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offset_x = int(numpy.amin(flip_vertices[:, 1]))
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flip_vertices[:, 0] = numpy.add(flip_vertices[:, 0], -offset_y)
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flip_vertices[:, 1] = numpy.add(flip_vertices[:, 1], -offset_x)
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shape = numpy.array([int(numpy.amax(flip_vertices[:, 0])), int(numpy.amax(flip_vertices[:, 1]))])
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shape[numpy.where(shape == 0)] = 1
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arr = cls.arrayFromPolygon(shape, flip_vertices)
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if not numpy.ndarray.any(arr):
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# set at least 1 pixel
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arr[0][0] = 1
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return cls(arr, offset_x, offset_y)
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## Instantiate an offset and hull ShapeArray from a scene node.
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# \param node source node where the convex hull must be present
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# \param min_offset offset for the offset ShapeArray
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# \param scale scale the coordinates
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@classmethod
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def fromNode(cls, node: "SceneNode", min_offset: float, scale: float = 0.5, include_children: bool = False) -> Tuple[Optional["ShapeArray"], Optional["ShapeArray"]]:
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transform = node._transformation
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transform_x = transform._data[0][3]
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transform_y = transform._data[2][3]
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hull_verts = node.callDecoration("getConvexHull")
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# If a model is too small then it will not contain any points
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if hull_verts is None or not hull_verts.getPoints().any():
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return None, None
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# For one_at_a_time printing you need the convex hull head.
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hull_head_verts = node.callDecoration("getConvexHullHead") or hull_verts
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if hull_head_verts is None:
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hull_head_verts = Polygon()
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# If the child-nodes are included, adjust convex hulls as well:
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if include_children:
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children = node.getAllChildren()
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if not children is None:
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for child in children:
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# 'Inefficient' combination of convex hulls through known code rather than mess it up:
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child_hull = child.callDecoration("getConvexHull")
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if not child_hull is None:
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hull_verts = hull_verts.unionConvexHulls(child_hull)
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child_hull_head = child.callDecoration("getConvexHullHead") or child_hull
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if not child_hull_head is None:
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hull_head_verts = hull_head_verts.unionConvexHulls(child_hull_head)
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offset_verts = hull_head_verts.getMinkowskiHull(Polygon.approximatedCircle(min_offset))
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offset_points = copy.deepcopy(offset_verts._points) # x, y
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offset_points[:, 0] = numpy.add(offset_points[:, 0], -transform_x)
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offset_points[:, 1] = numpy.add(offset_points[:, 1], -transform_y)
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offset_shape_arr = ShapeArray.fromPolygon(offset_points, scale = scale)
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hull_points = copy.deepcopy(hull_verts._points)
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hull_points[:, 0] = numpy.add(hull_points[:, 0], -transform_x)
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hull_points[:, 1] = numpy.add(hull_points[:, 1], -transform_y)
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hull_shape_arr = ShapeArray.fromPolygon(hull_points, scale = scale) # x, y
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return offset_shape_arr, hull_shape_arr
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## Create np.array with dimensions defined by shape
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# Fills polygon defined by vertices with ones, all other values zero
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# Only works correctly for convex hull vertices
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# Originally from: http://stackoverflow.com/questions/37117878/generating-a-filled-polygon-inside-a-numpy-array
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# \param shape numpy format shape, [x-size, y-size]
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# \param vertices
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@classmethod
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def arrayFromPolygon(cls, shape: Tuple[int, int], vertices: numpy.array) -> numpy.array:
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base_array = numpy.zeros(shape, dtype = numpy.int32) # Initialize your array of zeros
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fill = numpy.ones(base_array.shape) * True # Initialize boolean array defining shape fill
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# Create check array for each edge segment, combine into fill array
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for k in range(vertices.shape[0]):
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check_array = cls._check(vertices[k - 1], vertices[k], base_array)
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if check_array is not None:
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fill = numpy.all([fill, check_array], axis=0)
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# Set all values inside polygon to one
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base_array[fill] = 1
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return base_array
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## Return indices that mark one side of the line, used by arrayFromPolygon
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# Uses the line defined by p1 and p2 to check array of
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# input indices against interpolated value
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# Returns boolean array, with True inside and False outside of shape
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# Originally from: http://stackoverflow.com/questions/37117878/generating-a-filled-polygon-inside-a-numpy-array
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# \param p1 2-tuple with x, y for point 1
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# \param p2 2-tuple with x, y for point 2
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# \param base_array boolean array to project the line on
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@classmethod
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def _check(cls, p1: numpy.array, p2: numpy.array, base_array: numpy.array) -> Optional[numpy.array]:
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if p1[0] == p2[0] and p1[1] == p2[1]:
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return None
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idxs = numpy.indices(base_array.shape) # Create 3D array of indices
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p1 = p1.astype(float)
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p2 = p2.astype(float)
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if p2[0] == p1[0]:
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sign = numpy.sign(p2[1] - p1[1])
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return idxs[1] * sign
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if p2[1] == p1[1]:
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sign = numpy.sign(p2[0] - p1[0])
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return idxs[1] * sign
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# Calculate max column idx for each row idx based on interpolated line between two points
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max_col_idx = (idxs[0] - p1[0]) / (p2[0] - p1[0]) * (p2[1] - p1[1]) + p1[1]
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sign = numpy.sign(p2[0] - p1[0])
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return idxs[1] * sign <= max_col_idx * sign |