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# Copyright (c) 2016-2017 Weitian LI <weitian@aaronly.me>
# MIT license
"""
Generic drawers (a.k.a. painters) that draw some commonly used shapes.
Credit
------
* scikit-image - skimage/draw/draw.py
https://github.com/scikit-image/scikit-image/blob/master/skimage/draw/draw.py
"""
import logging
import numpy as np
from scipy import interpolate
logger = logging.getLogger(__name__)
def circle(radius=None, rprofile=None, fill_value=0.0):
"""
Draw a (filled) circle at the center of the output grid.
If ``rprofile`` is supplied, then it is used as the radial values
for the circle.
Parameters
----------
radius : int
The radius of the circle to draw
rprofile : 1D `~numpy.ndarray`, optional
The radial values for the circle, and ``radius`` will be ignored
if specified.
If not provided, then fill the circle with ones.
fill_value : float, optional
Value to be filled to the empty pixels, default 0.0
Returns
-------
img : 2D `~numpy.ndarray`
Image of size ``(2*radius+1, 2*radius+1)`` with the circle drawn
at the center.
NOTE
----
Using a rotational formulation to create the 2D window/image from the
1D window/profile gives more circular contours, than using the
"outer product."
Credit
------
[1] MATLAB - creating 2D convolution filters
https://cn.mathworks.com/matlabcentral/newsreader/view_thread/23588
"""
if rprofile is not None:
if radius is not None:
logger.warning("circle(): Ignored parameter radius.")
rprofile = np.asarray(rprofile)
radius = len(rprofile) - 1
xsize = 2 * radius + 1
x = np.arange(xsize) - radius
xg, yg = np.meshgrid(x, x)
r = np.sqrt(xg**2 + yg**2)
ridx = (r <= radius)
img = np.zeros(shape=(xsize, xsize))
img.fill(fill_value)
if rprofile is None:
img[ridx] = 1.0
else:
finterp = interpolate.interp1d(x=np.arange(len(rprofile)),
y=rprofile, kind="linear")
img[ridx] = finterp(r[ridx])
return img
def _ellipse_in_shape(shape, center, radii, rotation=0.0):
"""
Generate coordinates of points within ellipse bounded by shape.
Parameters
----------
shape : int tuple (nrow, ncol)
Shape of the input image. Must be length 2.
center : iterable of floats
(row, column) position of center inside the given shape.
radii : iterable of floats
Size of two half axes (for row and column)
rotation : float, optional
Rotation of the ellipse defined by the above, in counter-clockwise
direction, with respect to the column-axis.
Unit: [deg]
Returns
-------
rows : iterable of ints
Row coordinates representing values within the ellipse.
cols : iterable of ints
Corresponding column coordinates representing values within
the ellipse.
Credit
------
* scikit-image - skimage/draw/draw.py
"""
rotation = np.deg2rad(rotation)
r_lim, c_lim = np.ogrid[0:float(shape[0]), 0:float(shape[1])]
r_org, c_org = center
r_rad, c_rad = radii
rotation %= np.pi
sin_alpha, cos_alpha = np.sin(rotation), np.cos(rotation)
r, c = (r_lim - r_org), (c_lim - c_org)
distances = (((r * cos_alpha + c * sin_alpha) / r_rad) ** 2 +
((r * sin_alpha - c * cos_alpha) / c_rad) ** 2)
return np.nonzero(distances < 1)
def ellipse(center, radii, shape=None, rotation=0.0):
"""
Generate coordinates of pixels within the ellipse.
Parameters
----------
center : int tuple (r0, c0)
Center coordinate of the ellipse.
radii : int tuple (r_radius, c_radius)
Minor and major semi-axes. ``(r/r_radius)**2 + (c/c_radius)**2 <= 1``.
shape : int 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.
rotation : float, optional
Set the ellipse rotation in counter-clockwise direction.
Unit: [deg]
Returns
-------
rr, cc : int `~numpy.ndarray`
Pixel coordinates of the ellipse.
May be used to directly index into an array, e.g.
``img[rr, cc] = 1``.
Notes
-----
The ellipse equation::
((x * cos(alpha) + y * sin(alpha)) / x_radius) ** 2 +
((x * sin(alpha) - y * cos(alpha)) / y_radius) ** 2 = 1
Note that the positions of `ellipse` without specified `shape` can have
also, negative values, as this is correct on the plane. On the other
hand using these ellipse positions for an image afterwards may lead to
appearing on the other side of image, because
``image[-1, -1] = image[end-1, end-1]``
Credit
------
* scikit-image - skimage/draw/draw.py
"""
center = np.asarray(center)
radii = np.asarray(radii)
# allow just rotation with in range +/- 180 degree
rotation %= np.pi
# compute rotated radii by given rotation
r_radius_rot = (abs(radii[0] * np.cos(rotation)) +
radii[1] * np.sin(rotation))
c_radius_rot = (radii[0] * np.sin(rotation) +
abs(radii[1] * np.cos(rotation)))
# The upper_left and lower_right corners of the smallest rectangle
# containing the ellipse.
radii_rot = np.array([r_radius_rot, c_radius_rot])
upper_left = np.ceil(center - radii_rot).astype(int)
lower_right = np.floor(center + radii_rot).astype(int)
if shape is not None:
# 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[:2]) - 1)
shifted_center = center - upper_left
bounding_shape = lower_right - upper_left + 1
rr, cc = _ellipse_in_shape(bounding_shape, shifted_center,
radii, rotation)
rr.flags.writeable = True
cc.flags.writeable = True
rr += upper_left[0]
cc += upper_left[1]
return rr, cc
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