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import numpy as np | |
import matplotlib.pyplot as plt | |
from matplotlib.patches import Circle, Polygon | |
from simplification.cutil import simplify_coords_vw | |
def visualize(min_polygon:np.ndarray): | |
# visualize polygon: | |
polygon = Polygon(min_polygon) | |
_, ax = plt.subplots(1,1) | |
ax.add_patch(polygon) | |
for xy in min_polygon: | |
_circle = Circle(xy, radius=0.5, color="red") | |
ax.add_patch(_circle) | |
plt.ylim(0,1080) | |
plt.xlim(0,1920) | |
plt.gca().invert_yaxis() | |
plt.show() | |
# load in good points: | |
# if you comment this block out, the next visualization will work: | |
# or if you run this block twice, the next one will break | |
good_points = np.loadtxt("good_points.txt") | |
min_polygon = simplify_coords_vw(good_points, 30) | |
visualize(min_polygon) | |
# load in bad points: | |
# always the first point is 0,0 | |
bad_points = np.loadtxt("bad_points.txt") | |
min_polygon = simplify_coords_vw(bad_points, 30) | |
print(min_polygon[0]) # [6.93229666e-310 6.93229666e-310] | |
visualize(min_polygon) |
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