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import numpy as np
import scipy
def detect_boundaries(mask, axis):
# calculate the boundaries of the mask
#axis = 0 results in x_from, x_to
#axis = 1 results in y_from, y_to
sum = mask.sum(axis=axis)
ind_from = min(sum.nonzero()[0])
ind_to = max(sum.nonzero()[0])
return ind_from, ind_to
def area(mask):
x1, y1 = detect_boundaries(mask, 0)
a = y1 - x1
x2, y2 = detect_boundaries(mask, 1)
b = y2 - x2
return (a * b, x1, y1, x2, y2)
def calculate_best_angle_from_mask(mask, angles=np.arange(-10,10,0.5)):
areas = []
for angle in angles:
rotated_mask = scipy.ndimage.rotate(mask, angle, reshape=True, order = 0) # order = 0 is the nearest neighbor interpolation, so the mask is not interpolated
this_area = area(rotated_mask)
areas.append(this_area[0])
best_angle = angles[np.argmin(areas)]
return best_angle
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