def make_ring(inner_radius: int,
outer_radius: int,
dtype: str = 'uint8') -> np.ndarray:
"""
Make a circle with a given radius.
Args:
inner_radius: the inner radius of the circle to draw
outer_radius: the outer radius of the circle to draw
Returns:
a NumPy matrix of size 2 * radius + 1 with a circle in it.
"""
# if the radius is even, make it odd
length = 2 * outer_radius + 1
# create an RGBA box to house the circle in
box = np.zeros((length, length), dtype=dtype)
# get the coordinates for the outer circle
x_pixels, y_pixels = draw_circle(outer_radius, outer_radius, outer_radius)
# set the coordinates of the circle in the box
box[x_pixels, y_pixels] = 1
# get the coordinates for the inner circle
x_pixels, y_pixels = draw_circle(outer_radius, outer_radius, inner_radius)
# set the coordinates of the circle in the box
box[x_pixels, y_pixels] = 0
return box
def get_label_map(self, parameters, height, width):
label_map = np.zeros((height, width, 1))
dia = np.sqrt(height**2 + width**2)
rr, cc = draw_circle(int(parameters[0] * height),
int(parameters[1] * width),
int(parameters[2] * dia),
shape=(height, width))
label_map[rr, cc, 0] = 1
return label_map
def _drawCircle(self, centro, raggio, image):
'''
args:
centro = coordinates of the center
raggio = radius of the parabola circumference
image = masked array
returns:
circle = circle of one to display
'''
circle = np.zeros((image.shape[0], image.shape[1]))
rr, cc = draw_circle(centro[1], centro[0],
raggio / self._rFiducialPoint)
circle[rr, cc] = 1
return circle
def _generate_circle_mask(point, image, shape, random, angle=0):
if shape[0] == 1 or shape[1] == 1:
raise ValueError('size must be > 1 for circles')
min_radius = shape[0] / 2.0
max_radius = shape[1] / 2.0
left = point[1]
right = image[1] - point[1]
top = point[0]
bottom = image[0] - point[0]
available_radius = min(left, right, top, bottom, max_radius)
if available_radius < min_radius:
raise ArithmeticError('cannot fit shape to image')
radius = random.randint(min_radius, available_radius + 1)
circle = draw_circle(point[0], point[1], radius)
label = ('circle', ((point[0] - radius + 1, point[0] + radius),
(point[1] - radius + 1, point[1] + radius)))
return circle, label
def _generate_circle_mask_new(point, image, shape, random):
"""Generate a mask for a filled circle shape.
The radius of the circle is generated randomly.
Parameters
----------
point : tuple
The row and column of the top left corner of the rectangle.
image : tuple
The height, width and depth of the image into which the shape is placed.
shape : tuple
The minimum and maximum size and color of the shape to fit.
random : np.random.RandomState
The random state to use for random sampling.
Raises
------
ArithmeticError
When a shape cannot be fit into the image with the given starting
coordinates. This usually means the image dimensions are too small or
shape dimensions too large.
Returns
-------
label : tuple
A (category, ((r0, r1), (c0, c1))) tuple specifying the category and
bounding box coordinates of the shape.
indices : 2-D array
A mask of indices that the shape fills.
"""
if shape[0] == 1 or shape[1] == 1:
raise ValueError('size must be > 1 for circles')
min_radius = shape[0] / 2.0
max_radius = shape[1] / 2.0
left = point[1]
right = image[1] - point[1]
top = point[0]
bottom = image[0] - point[0]
available_radius = min(left, right, top, bottom, max_radius)
if available_radius < min_radius:
raise ArithmeticError('cannot fit shape to image')
radius = random.randint(min_radius, available_radius + 1)
circle = draw_circle(point[0], point[1], radius)
label = ('circle', (point[0], point[1], radius))
return circle, label
def _circleImage(image, x, y, raggio_px):
''' Function to create circular cuts of the image.
The function excludes cuts that come out of the edges of the image
and check the threshold for valid point
NOTE: if image is out of conditions return None type
Parameters
----------
image: masked array
image for the analysis
x: int
coordinate x
y: int
coordinate y
radius_px: int
radius of circular patch in pixels
Returns
-------
ima: numpy masked array
cut image
'''
th_validPoint = np.pi * raggio_px**2 * 30 / 100
if image is not None:
circle = np.ones((image.shape[0], image.shape[1])).astype(int)
rr, cc = draw_circle(x, y, raggio_px)
test_r = (len(list(filter(lambda x: x >= image.shape[0], rr))) > 0)
test_r2 = (len(list(filter(lambda x: x <= 0, rr))) > 0)
test_c = (len(list(filter(lambda x: x >= image.shape[0], cc))) > 0)
if test_r == True:
pass
elif test_r2 == True:
pass
elif test_c == True:
pass
else:
circle[rr, cc] = 0
mask_prod = np.ma.mask_or(circle.astype(bool), image.mask)
ima = np.ma.masked_array(image, mask=mask_prod)
valid_point = ima.compressed().shape[0]
if valid_point >= th_validPoint:
return ima
def _generate_circle_mask(point, image, size, p, random, OorA, lean, angle):
if size == 1:
raise ValueError('size must be > 1 for circles')
left = point[1]
right = image[1] - point[1]
top = point[0]
bottom = image[0] - point[0]
available_radius = min(left, right, top, bottom)
radius = int(math.sqrt(size / math.pi))
if radius > available_radius:
raise ArithmeticError('cannot fit shape to image')
circle = draw_circle(point[0], point[1], radius)
label = ('circle', ((point[0] - radius + 1, point[0] + radius),
(point[1] - radius + 1, point[1] + radius)))
return circle, label