1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
|
# Copyright (c) 2016 Weitian LI <liweitianux@live.com>
# MIT license
"""
Generic drawers (a.k.a. painters) that draw some commonly used shapes.
Credits
-------
The ``_ellipse_in_shape`` and ``ellipse()`` functions are originally taken
from project [scikit-image]_, which are licensed under the *Modified BSD*
license.
.. [scikit-image] skimage.draw.draw
http://scikit-image.org/docs/dev/api/skimage.draw.html
https://github.com/scikit-image/scikit-image/blob/master/skimage/draw/draw.py
"""
import numpy as np
import numba as nb
@nb.jit([nb.types.UniTuple(nb.int64[:], 2)(nb.types.UniTuple(nb.int64, 2),
nb.types.UniTuple(nb.int64, 2),
nb.types.UniTuple(nb.int64, 2)),
nb.types.UniTuple(nb.int64[:], 2)(nb.int64[:], nb.int64[:],
nb.int64[:])],
nopython=True)
def _ellipse_in_shape(shape, center, radii):
"""Generate coordinates of points within the ellipse bounded by shape."""
# XXX: ``numba`` currently does not support ``numpy.meshgrid``
nrow, ncol = shape
r_lim = np.zeros((nrow, ncol))
for i in range(nrow):
r_lim[i, :] = np.arange(float(ncol))
c_lim = np.zeros((nrow, ncol))
for i in range(ncol):
c_lim[:, i] = np.arange(float(nrow))
#
r_o, c_o = center
r_r, c_r = radii
distances = (((r_lim-r_o) / r_r) * ((r_lim-r_o) / r_r) +
xi, yi = np.nonzero(distances < 1.0)
return (xi, yi)
((c_lim-c_o) / c_r) * ((c_lim-c_o) / c_r))
@nb.jit(nb.types.UniTuple(nb.int64[:], 2)(nb.int64, nb.int64,
nb.int64, nb.int64,
nb.types.UniTuple(nb.int64, 2)),
nopython=True)
def ellipse(r, c, r_radius, c_radius, shape):
"""Generate coordinates of pixels within the ellipse.
XXX/NOTE
--------
* Cannot figure out why ``nb.optional(nb.types.UniTuple(nb.int64, 2))``
does NOT work. Therefore, make ``shape`` as mandatory parameter
instead of optional.
* Cannot figure out multi-dispatch that allows both int and float types
for ``r``, ``c``, ``r_radius`` and ``c_radius``. Thus only support
the int type for the moment.
Parameters
----------
r, c : int
Center coordinate of the ellipse.
r_radius, c_radius : int
Minor and major semi-axes. ``(r/r_radius)**2 + (c/c_radius)**2 = 1``.
shape : tuple
Image shape which is used to determine the maximum extent of output
pixel coordinates. This is useful for ellipses that exceed the image
size. If None, the full extent of the ellipse is used.
Returns
-------
rr, cc : integer `~numpy.ndarray`
Pixel coordinates of the ellipse.
May be used to directly index into an array, e.g.
``img[rr, cc] = 1``.
Examples
--------
>>> from fg21sim.utils.draw import ellipse
>>> img = np.zeros((10, 10), dtype=np.uint8)
>>> rr, cc = ellipse(5, 5, 3, 4)
>>> img[rr, cc] = 1
>>> img
array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 1, 1, 0],
[0, 0, 1, 1, 1, 1, 1, 1, 1, 0],
[0, 0, 1, 1, 1, 1, 1, 1, 1, 0],
[0, 0, 0, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], dtype=uint8)
"""
center = np.array([r, c])
radii = np.array([r_radius, c_radius])
# The upper_left and lower_right corners of the
# smallest rectangle containing the ellipse.
upper_left = np.ceil(center - radii).astype(np.int64)
lower_right = np.floor(center + radii).astype(np.int64)
# Constrain upper_left and lower_right by shape boundary.
upper_left = np.maximum(upper_left, np.array([0, 0]))
lower_right = np.minimum(lower_right, np.array(shape)-1)
shifted_center = center - upper_left
bounding_shape = lower_right - upper_left + 1
rr, cc = _ellipse_in_shape(bounding_shape, shifted_center, radii)
rr += upper_left[0]
cc += upper_left[1]
return (rr, cc)
|
