def measure_target_width_on_segment(self, pt1, pt2):
"""
Given the line segment L defined by 2d points pt1 and pt2 from a camera
frame, find the points pt3 and pt4 the nearest points to pt1 and pt2
on L that are masked according to self.mask8. Then calculate the
distance D between 3d points pt5 and pt6 in self.xyz which
correspond to pt3 and pt4.
return pt3, pt4, D, fx, fy,
where
pt3 = (x, y)
pt4 = (x, y)
fx is the function f(distance from pt3 on L) = x
fy is the function f(distance from pt3 on L) = y
If anything goes wrong, return None
"""
from scipy.interpolate import interp1d
dist2d = distance(pt1, pt2)
interpx = interp1d([0, dist2d], [pt1[0], pt2[0]])
interpy = interp1d([0, dist2d], [pt1[1], pt2[1]])
t = numpy.linspace(0, int(dist2d), int(dist2d)+1)
xs = numpy.int0(interpx(t))
ys = numpy.int0(interpy(t))
ixs, = self.mask8[ys, xs].nonzero()
if len(ixs) >= 2:
x1 = xs[ixs[0]]
y1 = ys[ixs[0]]
x2 = xs[ixs[-1]]
y2 = ys[ixs[-1]]
xyz1 = self.xyz[:, y1, x1]
xyz2 = self.xyz[:, y2, x2]
dist3d = distance(xyz1, xyz2)
interpx2 = lambda d: (x2-x1)*d/dist2d + x1
interpy2 = lambda d: (y2-y1)*d/dist2d + y1
return (x1, y1), (x2, y2), dist3d, interpx2, interpy2
def display_measurement(self, stuff):
pt1, pt2, dist, fx, fy = stuff
dist2d = distance(pt1, pt2)
txt_x = int(fx(dist2d+20))
txt_y = int(fy(dist2d+20))
cv2.circle(self.contour_img, pt1, 2, rgbhex2bgr(0xf7ff1e),
thickness=2)
cv2.circle(self.contour_img, pt2, 2, rgbhex2bgr(0xf7ff1e),
thickness=2)
cv2.putText(self.contour_img,
("%.2f in" % mm_to_in(dist)), (txt_x, txt_y),
cv2.FONT_HERSHEY_SIMPLEX, 0.6, rgbhex2bgr(0xf7ff1e))