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import warnings
import numpy as np
import cv2
from shapely.geometry import Polygon
import pyclipper
from concern.config import Configurable, State
class MakeBorderMap(Configurable):
shrink_ratio = State(default=0.4)
thresh_min = State(default=0.3)
thresh_max = State(default=0.7)
def __init__(self, cmd={}, *args, **kwargs):
self.load_all(cmd=cmd, **kwargs)
warnings.simplefilter("ignore")
def __call__(self, data, *args, **kwargs):
image = data['image']
polygons = data['polygons']
ignore_tags = data['ignore_tags']
canvas = np.zeros(image.shape[:2], dtype=np.float32)
mask = np.zeros(image.shape[:2], dtype=np.float32)
for i in range(len(polygons)):
if ignore_tags[i]:
continue
self.draw_border_map(polygons[i], canvas, mask=mask)
canvas = canvas * (self.thresh_max - self.thresh_min) + self.thresh_min
data['thresh_map'] = canvas
data['thresh_mask'] = mask
return data
def draw_border_map(self, polygon, canvas, mask):
polygon = np.array(polygon)
assert polygon.ndim == 2
assert polygon.shape[1] == 2
polygon_shape = Polygon(polygon)
distance = polygon_shape.area * \
(1 - np.power(self.shrink_ratio, 2)) / polygon_shape.length
subject = [tuple(l) for l in polygon]
padding = pyclipper.PyclipperOffset()
padding.AddPath(subject, pyclipper.JT_ROUND,
pyclipper.ET_CLOSEDPOLYGON)
padded_polygon = np.array(padding.Execute(distance)[0])
cv2.fillPoly(mask, [padded_polygon.astype(np.int32)], 1.0)
xmin = padded_polygon[:, 0].min()
xmax = padded_polygon[:, 0].max()
ymin = padded_polygon[:, 1].min()
ymax = padded_polygon[:, 1].max()
width = xmax - xmin + 1
height = ymax - ymin + 1
polygon[:, 0] = polygon[:, 0] - xmin
polygon[:, 1] = polygon[:, 1] - ymin
xs = np.broadcast_to(
np.linspace(0, width - 1, num=width).reshape(1, width), (height, width))
ys = np.broadcast_to(
np.linspace(0, height - 1, num=height).reshape(height, 1), (height, width))
distance_map = np.zeros(
(polygon.shape[0], height, width), dtype=np.float32)
for i in range(polygon.shape[0]):
j = (i + 1) % polygon.shape[0]
absolute_distance = self.distance(xs, ys, polygon[i], polygon[j])
distance_map[i] = np.clip(absolute_distance / distance, 0, 1)
distance_map = distance_map.min(axis=0)
xmin_valid = min(max(0, xmin), canvas.shape[1] - 1)
xmax_valid = min(max(0, xmax), canvas.shape[1] - 1)
ymin_valid = min(max(0, ymin), canvas.shape[0] - 1)
ymax_valid = min(max(0, ymax), canvas.shape[0] - 1)
canvas[ymin_valid:ymax_valid + 1, xmin_valid:xmax_valid + 1] = np.fmax(
1 - distance_map[
ymin_valid-ymin:ymax_valid-ymax+height,
xmin_valid-xmin:xmax_valid-xmax+width],
canvas[ymin_valid:ymax_valid + 1, xmin_valid:xmax_valid + 1])
def distance(self, xs, ys, point_1, point_2):
'''
compute the distance from point to a line
ys: coordinates in the first axis
xs: coordinates in the second axis
point_1, point_2: (x, y), the end of the line
'''
height, width = xs.shape[:2]
square_distance_1 = np.square(
xs - point_1[0]) + np.square(ys - point_1[1])
square_distance_2 = np.square(
xs - point_2[0]) + np.square(ys - point_2[1])
square_distance = np.square(
point_1[0] - point_2[0]) + np.square(point_1[1] - point_2[1])
cosin = (square_distance - square_distance_1 - square_distance_2) / \
(2 * np.sqrt(square_distance_1 * square_distance_2))
square_sin = 1 - np.square(cosin)
square_sin = np.nan_to_num(square_sin)
result = np.sqrt(square_distance_1 * square_distance_2 *
square_sin / square_distance)
result[cosin < 0] = np.sqrt(np.fmin(
square_distance_1, square_distance_2))[cosin < 0]
# self.extend_line(point_1, point_2, result)
return result
def extend_line(self, point_1, point_2, result):
ex_point_1 = (int(round(point_1[0] + (point_1[0] - point_2[0]) * (1 + self.shrink_ratio))),
int(round(point_1[1] + (point_1[1] - point_2[1]) * (1 + self.shrink_ratio))))
cv2.line(result, tuple(ex_point_1), tuple(point_1),
4096.0, 1, lineType=cv2.LINE_AA, shift=0)
ex_point_2 = (int(round(point_2[0] + (point_2[0] - point_1[0]) * (1 + self.shrink_ratio))),
int(round(point_2[1] + (point_2[1] - point_1[1]) * (1 + self.shrink_ratio))))
cv2.line(result, tuple(ex_point_2), tuple(point_2),
4096.0, 1, lineType=cv2.LINE_AA, shift=0)
return ex_point_1, ex_point_2
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