def centerline(self):
""" determine the center line of the tail """
mask, offset = self.mask
dist_map = cv2.distanceTransform(mask, cv2.DIST_L2, 5)
# setup active contour algorithm
ac = ActiveContour(blur_radius=self.centerline_blur_radius,
closed_loop=False,
alpha=0, #< line length is constraint by beta
beta=self.centerline_bending_stiffness,
gamma=self.centerline_adaptation_rate)
ac.max_iterations = self.centerline_max_iterations
ac.set_potential(dist_map)
# find centerline starting from the ventral_side
points = curves.translate_points(self.ventral_side,
-offset[0], -offset[1])
spacing = self.centerline_spacing
points = curves.make_curve_equidistant(points, spacing=spacing)
# use the active contour algorithm
points = ac.find_contour(points)
points = curves.make_curve_equidistant(points, spacing=spacing)
# translate points back into global coordinate system
points = curves.translate_points(points, offset[0], offset[1])
# orient the centerline such that it starts at the posterior end
dist1 = curves.point_distance(points[0], self.endpoints[0])
dist2 = curves.point_distance(points[-1], self.endpoints[0])
if dist1 > dist2:
points = points[::-1]
return points
def centerline(self):
""" determine the center line of the tail """
mask, offset = self.mask
dist_map = cv2.distanceTransform(mask, cv2.DIST_L2, 5)
# setup active contour algorithm
ac = ActiveContour(
blur_radius=self.centerline_blur_radius,
closed_loop=False,
alpha=0, #< line length is constraint by beta
beta=self.centerline_bending_stiffness,
gamma=self.centerline_adaptation_rate)
ac.max_iterations = self.centerline_max_iterations
ac.set_potential(dist_map)
# find centerline starting from the ventral_side
points = curves.translate_points(self.ventral_side, -offset[0],
-offset[1])
spacing = self.centerline_spacing
points = curves.make_curve_equidistant(points, spacing=spacing)
# use the active contour algorithm
points = ac.find_contour(points)
points = curves.make_curve_equidistant(points, spacing=spacing)
# translate points back into global coordinate system
points = curves.translate_points(points, offset[0], offset[1])
# orient the centerline such that it starts at the posterior end
dist1 = curves.point_distance(points[0], self.endpoints[0])
dist2 = curves.point_distance(points[-1], self.endpoints[0])
if dist1 > dist2:
points = points[::-1]
return points
def measure_single_tail(self, frame, tail):
""" do line scans along the measurement segments of the tails """
l = self.params['measurement/line_scan_width']
w = self.params['measurement/line_scan_step'] #< width of each individual line scan
result = []
for line in self.get_measurement_lines(tail):
ps = curves.make_curve_equidistant(line, spacing=2*w)
profile = []
for pp, p, pn in itertools.izip(ps[:-2], ps[1:-1], ps[2:]):
# slope
dx, dy = pn - pp
dlen = math.hypot(dx, dy)
dx /= dlen; dy /= dlen
# get end points of line scan
p1 = (p[0] + l*dy, p[1] - l*dx)
p2 = (p[0] - l*dy, p[1] + l*dx)
lscan = image.line_scan(frame, p1, p2, half_width=w)
profile.append(lscan.mean())
self.output.add_points([p1, p2], 1, 'w')
result.append(profile)
return result
def contour(self, points):
""" sets the contour of the tail performing some sanity tests """
# do a first regularization
points = regions.regularize_contour_points(points)
spacing = self.contour_spacing
# make the contour line equidistant
points = curves.make_curve_equidistant(points, spacing=spacing)
# regularize again, just to be sure
points = regions.regularize_contour_points(points)
# call parent setter
shapes.Polygon.contour.fset(self, points)
def contour(self, points):
""" sets the contour of the tail performing some sanity tests """
# do a first regularization
points = regions.regularize_contour_points(points)
spacing = self.contour_spacing
# make the contour line equidistant
points = curves.make_curve_equidistant(points, spacing=spacing)
# regularize again, just to be sure
points = regions.regularize_contour_points(points)
# call parent setter
shapes.Polygon.contour.fset(self, points)
def create_from_ground_profile_list(cls, ground_profiles):
# determine the maximal number of points in a single ground
num_points = max(len(ground) for ground in ground_profiles.grounds)
# iterate through all profiles and convert them to have equal number of line
# and store the data
times = ground_profiles.times
profiles = [curves.make_curve_equidistant(ground.points, count=num_points)
for ground in ground_profiles.grounds]
# store information in numpy arrays
# profiles is a 3D array: len(times) x num_points x 2
return cls(times=times, profiles=profiles)
def create_from_ground_profile_list(cls, ground_profiles):
# determine the maximal number of points in a single ground
num_points = max(len(ground) for ground in ground_profiles.grounds)
# iterate through all profiles and convert them to have equal number of line
# and store the data
times = ground_profiles.times
profiles = [curves.make_curve_equidistant(ground.points, count=num_points)
for ground in ground_profiles.grounds]
# store information in numpy arrays
# profiles is a 3D array: len(times) x num_points x 2
return cls(times=times, profiles=profiles)
def _get_burrow_exits(self, contour):
""" determines the exits of a burrow.
Returns a list of exits, where each exit is described by a list of
points lying on the burrow contour
"""
ground_line = self.ground.linestring
dist_max = self.params['burrows/ground_point_distance']
#/2
# dist_max = dist + self.params['burrows/width']
contour = curves.make_curve_equidistant(contour, spacing=2)
# determine burrow points close to the ground
exit_points = [point for point in contour
if ground_line.distance(geometry.Point(point)) < dist_max]
if len(exit_points) < 2:
return exit_points
exit_points = np.array(exit_points)
# cluster the points to detect multiple connections
# this is important when a burrow has multiple exits to the ground
dist_max = self.params['burrows/width']
data = cluster.hierarchy.fclusterdata(exit_points, dist_max,
method='single',
criterion='distance')
exits = [exit_points[data == cluster_id]
for cluster_id in np.unique(data)]
# exits = []
# for cluster_id in np.unique(data):
# points = exit_points[data == cluster_id]
# point = points.mean(axis=0)
# point_ground = curves.get_projection_point(ground_line, point)
# exits.append(point_ground)
return exits
def make_equidistant(self, **kwargs):
""" makes the ground profile equidistant """
self.points = curves.make_curve_equidistant(self.points, **kwargs)
def make_equidistant(self, **kwargs):
""" makes the ground profile equidistant """
self.points = curves.make_curve_equidistant(self.points, **kwargs)
