def Dubins_msg(UAV, target, R0):
v = UAV.v
phi0 = UAV.phi
UAV_p = Point(UAV.site)
target_p = Point(target[0:2])
c1 = Point(UAV_p.x + R0 * np.sin(phi0), UAV_p.y - R0 * np.cos(phi0))
c2 = Point(UAV_p.x - R0 * np.sin(phi0), UAV_p.y + R0 * np.cos(phi0))
len1 = c1.distance(target_p)
len2 = c2.distance(target_p)
center = c1
if len2 > len1:
center = c2
center = Point(round(center.x.evalf(), 4), round(center.y.evalf(), 4))
circle = Circle(center, R0)
tangent_lines = Tangent_lines(circle, target_p)
tangent_line1 = tangent_lines[0]
tangent_line1 = Line(tangent_line1.p2, tangent_line1.p1)
tangent_point1 = tangent_line1.p1
y = float((target_p.y - tangent_point1.y).evalf())
x = float((target_p.x - tangent_point1.x).evalf())
tangent_angle1 = np.arctan2(y, x)
tangent_line2 = tangent_lines[1]
tangent_line2 = Line(tangent_line2.p2, tangent_line2.p1)
tangent_point2 = tangent_line2.p1
y = float((target_p.y - tangent_point2.y).evalf())
x = float((target_p.x - tangent_point2.x).evalf())
tangent_angle2 = np.arctan2(y, x)
vec1 = [UAV_p.x - center.x, UAV_p.y - center.y]
vec2 = [np.cos(phi0), np.sin(phi0)]
direction = np.sign(vec1[0] * vec2[1] - vec1[1] * vec2[0])
sin1 = float(tangent_point1.distance(UAV_p).evalf()) / (2 * R0)
angle1 = 2 * np.arcsin(sin1)
sin2 = float(tangent_point2.distance(UAV_p).evalf()) / (2 * R0)
angle2 = 2 * np.arcsin(sin2)
tangent_point = []
radian = 0
if abs(modf(abs(direction * angle1 + phi0 - tangent_angle1) / (2 * np.pi))[0] - 0.5) > 0.5 - deviation:
tangent_point = tangent_point1
radian = angle1
elif abs(modf(abs(direction * (2 * np.pi - angle1) + phi0 - tangent_angle1) / (2 * np.pi))[
0] - 0.5) > 0.5 - deviation:
tangent_point = tangent_point1
radian = 2 * np.pi - angle1
elif abs(modf(abs(direction * angle2 + phi0 - tangent_angle2) / (2 * np.pi))[0] - 0.5) > 0.5 - deviation:
tangent_point = tangent_point2
radian = angle2
elif abs(modf(abs(direction * (2 * np.pi - angle2) + phi0 - tangent_angle2) / (2 * np.pi))[
0] - 0.5) > 0.5 - deviation:
tangent_point = tangent_point2
radian = 2 * np.pi - angle2
return direction, radian, (float(tangent_point.x.evalf()), float(tangent_point.y.evalf())), (
float(center.x.evalf()), float(center.y.evalf()))
def distance(self, other):
"""The Euclidean distance between self and another GeometricEntity.
Returns
=======
distance : number or symbolic expression.
Raises
======
AttributeError : if other is a GeometricEntity for which
distance is not defined.
TypeError : if other is not recognized as a GeometricEntity.
See Also
========
sympy.geometry.line.Segment.length
sympy.geometry.point.Point.taxicab_distance
Examples
========
>>> from sympy.geometry import Point, Line
>>> p1, p2 = Point(1, 1), Point(4, 5)
>>> l = Line((3, 1), (2, 2))
>>> p1.distance(p2)
5
>>> p1.distance(l)
sqrt(2)
The computed distance may be symbolic, too:
>>> from sympy.abc import x, y
>>> p3 = Point(x, y)
>>> p3.distance((0, 0))
sqrt(x**2 + y**2)
"""
if not isinstance(other, GeometryEntity):
try:
other = Point(other, dim=self.ambient_dimension)
except TypeError:
raise TypeError("not recognized as a GeometricEntity: %s" %
type(other))
if isinstance(other, Point):
s, p = Point._normalize_dimension(self, Point(other))
return sqrt(Add(*((a - b)**2 for a, b in zip(s, p))))
try:
return other.distance(self)
except AttributeError:
raise AttributeError(
"distance between Point and %s is not defined" % type(other))
def distance(self, other):
"""The Euclidean distance between self and another GeometricEntity.
Returns
=======
distance : number or symbolic expression.
Raises
======
AttributeError : if other is a GeometricEntity for which
distance is not defined.
TypeError : if other is not recognized as a GeometricEntity.
See Also
========
sympy.geometry.line.Segment.length
sympy.geometry.point.Point.taxicab_distance
Examples
========
>>> from sympy.geometry import Point, Line
>>> p1, p2 = Point(1, 1), Point(4, 5)
>>> l = Line((3, 1), (2, 2))
>>> p1.distance(p2)
5
>>> p1.distance(l)
sqrt(2)
The computed distance may be symbolic, too:
>>> from sympy.abc import x, y
>>> p3 = Point(x, y)
>>> p3.distance((0, 0))
sqrt(x**2 + y**2)
"""
if not isinstance(other , GeometryEntity) :
try :
other = Point(other, dim=self.ambient_dimension)
except TypeError :
raise TypeError("not recognized as a GeometricEntity: %s" % type(other))
if isinstance(other , Point) :
s, p = Point._normalize_dimension(self, Point(other))
return sqrt(Add(*((a - b)**2 for a, b in zip(s, p))))
try :
return other.distance(self)
except AttributeError :
raise AttributeError("distance between Point and %s is not defined" % type(other))
def Angle(self):
yAxis = Line(Point(0, 1), Point(0, 0))
point1 = Point(self.Box[1][0], self.Box[1][1])
point2 = Point(self.Box[0][0], self.Box[0][1])
point3 = Point(self.Box[2][0], self.Box[2][1])
if point1.distance(point2) > point1.distance(point3):
longerLine = Line(point1, point2)
else:
longerLine = Line(point1, point3)
angle = int(math.degrees(yAxis.angle_between(longerLine)))
if (int(angle) > 90):
if angle - 180 + 80 >= 0:
return angle - 180 + 80
else:
return 0
else:
if angle + 80 >= 0:
return angle + 80
else:
return 0
def Dubins_msg(UAV, target, R0):
# 单架无人机到达目标点所需时间
# 这里的UAV和target是无人机和目标对象
v = UAV.v # 飞机速度
phi0 = UAV.phi # 转化为弧度，[0,2pi]
UAV_p = Point(UAV.site)
target_p = Point(target[0:2])
# 以上为所有已知信息
# 1. 求两个圆心，判断出采用哪一个圆
# 2. 求切线
# 3. 确定用那一段弧长
# 1.求两个圆心，判断出采用哪一个圆
c1 = Point(UAV_p.x + R0 * np.sin(phi0), UAV_p.y - R0 * np.cos(phi0))
c2 = Point(UAV_p.x - R0 * np.sin(phi0), UAV_p.y + R0 * np.cos(phi0))
len1 = c1.distance(target_p)
len2 = c2.distance(target_p)
center = c1
if len2 > len1:
center = c2
# 2. 求切线
center = Point(round(center.x.evalf(), 4), round(center.y.evalf(), 4))
circle = Circle(center, R0)
# start=time.time()
# tangent_lines = circle.tangent_lines(target_p)
tangent_lines = Tangent_lines(circle, target_p)
# end=time.time()
# print(end-start)
tangent_line1 = tangent_lines[0] # 注意这里的切线方向是从target-> 切点
tangent_line1 = Line(tangent_line1.p2, tangent_line1.p1) # 改为从切点->target
tangent_point1 = tangent_line1.p1 # 切点1
y = float((target_p.y - tangent_point1.y).evalf())
x = float((target_p.x - tangent_point1.x).evalf())
tangent_angle1 = np.arctan2(y, x) # arctan2(y,x) 向量(x,y)的角度[-pi,pi]
tangent_line2 = tangent_lines[1]
tangent_line2 = Line(tangent_line2.p2, tangent_line2.p1) # 改为从切点->target
tangent_point2 = tangent_line2.p1 # 切点２
y = float((target_p.y - tangent_point2.y).evalf())
x = float((target_p.x - tangent_point2.x).evalf())
tangent_angle2 = np.arctan2(y, x) # arctan2(y,x) 向量(x,y)的角度[-pi,pi]
# 3. 确定用哪一段弧长
# a. 确定用顺时针还是逆时针
vec1 = [UAV_p.x - center.x, UAV_p.y - center.y]
vec2 = [np.cos(phi0), np.sin(phi0)]
direction = np.sign(vec1[0] * vec2[1] - vec1[1] * vec2[0]) # 1 表示逆时针 -1 表示顺时针
# b. 判断是哪一个切点，哪一段弧
sin1 = float(tangent_point1.distance(UAV_p).evalf()) / (2 * R0)
angle1 = 2 * np.arcsin(sin1) # 无人机位置与切点之间的弧度[0,pi] 小弧
sin2 = float(tangent_point2.distance(UAV_p).evalf()) / (2 * R0)
angle2 = 2 * np.arcsin(sin2)
tangent_point = []
hudu = 0
# 判断式的意思 角度要在误差范围内相隔2kpi，使用modf(abs 把值控制在0-1之内，误差范围内靠近1，靠近0 都ok 用于0.5之间的距离来判断
if abs(modf(abs(direction * angle1 + phi0 - tangent_angle1) / (2 * np.pi))[0] - 0.5) > 0.5 - deviation:
tangent_point = tangent_point1
hudu = angle1
# modf 返回浮点数的小数部分和整数部分modf(1.23) return [0.23,1]
elif abs(modf(abs(direction * (2 * np.pi - angle1) + phi0 - tangent_angle1) / (2 * np.pi))[
0] - 0.5) > 0.5 - deviation:
tangent_point = tangent_point1
hudu = 2 * np.pi - angle1
elif abs(modf(abs(direction * angle2 + phi0 - tangent_angle2) / (2 * np.pi))[0] - 0.5) > 0.5 - deviation:
tangent_point = tangent_point2
hudu = angle2
elif abs(modf(abs(direction * (2 * np.pi - angle2) + phi0 - tangent_angle2) / (2 * np.pi))[
0] - 0.5) > 0.5 - deviation:
tangent_point = tangent_point2
hudu = 2 * np.pi - angle2
# 返回 旋转方向 弧度 切点坐标 圆心坐标
return direction, hudu, (float(tangent_point.x.evalf()), float(tangent_point.y.evalf())), (
float(center.x.evalf()), float(center.y.evalf()))
def __abs__(self):
"""Returns the distance between this point and the origin."""
origin = Point([0] * len(self.args))
return Point.distance(origin, self)
gray = rotateImage(gray, angle, tuple(shape[33]))
# gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
rects = detector(gray, 1)
# loop over the face detections
for (k, rect) in enumerate(rects):
shape = predictor(gray, rect)
shape = face_utils.shape_to_np(shape)
eye = Point(shape[37])
eyebrow = Point(shape[19])
left = Point(min(shape, key=itemgetter(0)))
top = Point(min(shape, key=itemgetter(1)))
right = Point(max(shape, key=itemgetter(0)))
bottom = Point(max(shape, key=itemgetter(1)))
gray = gray[int(top.y - eye.distance(eyebrow) / 2):int(top.y + top.distance(bottom)),
int(left.x):int(left.x + left.distance(right))]
# ujednacavanje histograma
clahe = cv2.createCLAHE(clipLimit=2.0, tileGridSize=(8, 8))
gray = clahe.apply(gray)
# gray = cv2.bilateralFilter(gray, 9, 75, 75)
ratio = 300.0 / gray.shape[1]
dimensions = (300, int(gray.shape[0] * ratio))
gray = cv2.resize(gray, dimensions, interpolation=cv2.INTER_AREA)
cv2.imwrite("Users/" + person + "/processed/" + faceImageFile, gray)
print("File: " + faceImageFile)
# faceImage = cv2.imread("Users/" + person + "/" + faceImageFile, 0)
def __abs__(self):
"""Returns the distance between this point and the origin."""
origin = Point([0]*len(self.args))
return Point.distance(origin, self)
def biarc_avg(w0, p0, p1, t0, t1, r0=1., r1=1.):
global IN_DEBUG
DEBUG = 'IN_DEBUG' in globals()
if DEBUG and IN_DEBUG:
fig = plt.figure()
#_, _, _ = create_input_log_spiral()
numpy_io = False
if isinstance(p0, np.ndarray):
numpy_io = True
p0 = Point(p0[0], p0[1], evaluate=False)
p1 = Point(p1[0], p1[1], evaluate=False)
t0 = Point(t0[0], t0[1], evaluate=False)
t1 = Point(t1[0], t1[1], evaluate=False)
t0 = Point(float(t0.unit.x), float(t0.unit.y), evaluate=False)
t1 = Point(float(t1.unit.x), float(t1.unit.y), evaluate=False)
p0p1_segm_vec = Line(p0, p1).direction.unit
tangents_equal = t1.distance(t0) < 0.0001
segm_tang_collinear = t1.distance(p0p1_segm_vec) < 0.0001 or \
t1.distance(-p0p1_segm_vec) < 0.0001
if tangents_equal and segm_tang_collinear:
res_pt = (1. - w0) * p0 + w0 * p1
res_tg = Point(t0[0], t0[1]) if numpy_io else t0
else:
# --- try 2 ----------------------------------------------------------
prevInDebg = IN_DEBUG
jnc_cntr, jnc_radius = get_junction_circle(p0, p1, t0, t1)
osc_seg0_start, osc_seg0_end = get_arc_seg(p0, t0, r0, jnc_cntr,
jnc_radius, p0, p1)
osc_seg1_start, osc_seg1_end = get_arc_seg(p1, t1, r1, jnc_cntr,
jnc_radius, osc_seg0_start,
osc_seg0_end)
target_arc = CircArc(osc_seg1_start, osc_seg1_end, jnc_cntr)
target_len = w0 * target_arc.get_length()
res_pt, res_tg = target_arc.eval_pt_tang(target_len)
res_radius = jnc_radius #target_arc.radius
#oscul_cntr0 = get_osculating_center(p0, t0, r0, jnc_cntr)
#oscul_cntr1 = get_osculating_center(p1, t1, r1, jnc_cntr)
#c0_jnc_intr = get_circles_intersection(jnc_cntr, jnc_radius, oscul_cntr0, r0)
#c1_jnc_intr = get_circles_intersection(jnc_cntr, jnc_radius, oscul_cntr1, r1)
#IN_DEBUG = prevInDebg
#jnc_pts_cands = c0_jnc_intr + c1_jnc_intr
#if DEBUG and IN_DEBUG:
# for inx_pt in jnc_pts_cands:
# draw_point(inx_pt, "#A569BD")
# draw_circle(jnc_cntr, jnc_radius, "#76D7C4")
# draw_circle(oscul_cntr0, r0, "#85C1E9")
# draw_circle(oscul_cntr1, r1, "#85C1E9")
#p0_ang_jnc_circ = get_angle(float(p0.x - jnc_cntr.x),
# float(p0.y - jnc_cntr.y))
#p1_ang_jnc_circ = get_angle(float(p1.x - jnc_cntr.x),
# float(p1.y - jnc_cntr.y))
#min_ang_jnc_circ = min(p0_ang_jnc_circ, p1_ang_jnc_circ)
#max_ang_jnc_circ = max(p0_ang_jnc_circ, p1_ang_jnc_circ)
#if (max_ang_jnc_circ - min_ang_jnc_circ) > np.pi:
# # we pass zero angle
# pass
#jnc_pt_angles = [get_angle(float(inx_pt.x - jnc_cntr.x),
# float(inx_pt.y - jnc_cntr.y))
# for inx_pt in jnc_pts_cands]
#for ang in jnc_pt_angles:
# if min_ang_jnc_circ <= ang <= max_ang_jnc_circ:
# --- try 2 ----------------------------------------------------------
# --- try 1 ----------------------------------------------------------
#anchor_pt = get_anchor_pt(p0, p1, t0, t1, r0, r1)
#left_biarc = get_secondary_biarc(p0, t0, anchor_pt, True)
#rght_biarc = get_secondary_biarc(p1, t1, anchor_pt, False)
#left_len = float(left_biarc.get_length())
#rght_len = float(rght_biarc.get_length())
#trgt_len = float(w0*(left_len + rght_len))
#if np.abs(trgt_len - left_len) < 0.0001:
# res_pt = anchor_pt
# res_tg = left_biarc.eval_end_pt_tang(False)
#else:
# if float(trgt_len) < float(left_len):
# trgt_biarc = left_biarc
# else:
# trgt_biarc = rght_biarc
# trgt_len -= left_len
# res_pt, res_tg = trgt_biarc.eval_pt_tang(trgt_len)
# --------------------------------------------------------------------
res_radius = (1. - w0) * r0 + w0 * r1
DEBUG = 'IN_DEBUG' in globals()
if DEBUG and IN_DEBUG:
#left_biarc.draw(plt.gca(), "#FF99FF")
#rght_biarc.draw(plt.gca(), "#7F00FF")
rnr = mpt.Arrow(float(res_pt.x),
float(res_pt.y),
float(res_tg.x),
float(res_tg.y),
width=0.6,
fc="r",
ec='none')
plt.gca().add_patch(rnr)
crc = mpt.Circle([float(res_pt.x), float(res_pt.y)],
radius=float(0.4),
ec="r",
fill=False)
plt.gca().add_patch(crc)
plt.axis('equal')
plt.xlim([-5, 20])
plt.ylim([-15, 10])
plt.show()
if numpy_io:
res_pt = np.array([float(res_pt.x), float(res_pt.y)])
res_tg = np.array([float(res_tg.x), float(res_tg.y)])
if np.linalg.norm(res_tg) < 0.0001:
a = 5
res_tg /= np.linalg.norm(res_tg)
return res_pt, res_tg, res_radius
def circular_random_walk(step_options = [0, 0.5, 1], size = 100000):
fig, axs = plt.subplots()
plt.xlabel("Position - x")
plt.ylabel("Position - y")
Radius = 100
step_addition = 0
randomWalk_x= [0]
randomWalk_y= [0]
counter = 1
while counter < (size + 1):
i = counter
angle = np.random.uniform(0, 2*np.pi, size = 1)
distance = np.random.choice(step_options, size = 1)
x_coordinate = distance[0] * np.cos(angle[0])
y_coordinate = distance[0] * np.sin(angle[0])
new_x = randomWalk_x[-1] + x_coordinate
new_y = randomWalk_y[-1] + y_coordinate
distance_from_origin = math.sqrt((new_x)**2 + (new_y)**2)
if distance_from_origin >= (Radius):
new_x = ('%.3f'%(new_x))
new_y = ('%.3f'%(new_y))
old_x = randomWalk_x[-1]
old_y = randomWalk_y[-1]
old_x = ('%.3f'%(old_x))
old_y = ('%.3f'%(old_y))
p1, p2 = Point(old_x, old_y) , Point(new_x, new_y)
if p1.equals(p2):
randomWalk_x.append(old_x)
randomWalk_y.append(old_y)
counter+=1
continue
line = Line(p1, p2)
a, b, c = line.coefficients
x, y = symbols('x,y')
eq1 = Eq((x)**2 + (y)**2 - (Radius)**2, 0, evaluate=False)
eq2 = Eq((a*x) + (b*y) + c, 0, evaluate=False)
sol = solve([eq1, eq2], [x, y])
#find the point on the circumference where our line will touch, call it circpoint
try:
sol1 = Point(sol[0][0], sol[0][1])
sol2 = Point(sol[1][0], sol[1][1])
dist_sol1 = p1.distance(sol1)
dist_sol2 = p1.distance(sol2)
if dist_sol1 > dist_sol2:
circ_point = sol[1]
elif dist_sol1 < dist_sol2:
circ_point = sol[0]
else:
d1 = sol1.distance(p2)
d2 = sol2.distance(p2)
if d1 < d2:
circ_point = sol[0]
else:
circ_point = sol[1]
circ_point = Point(circ_point[0], circ_point[1])
except:
randomWalk_x.append(old_x)
randomWalk_y.append(old_y)
counter+=1
continue
#we know the overflow amount, call that overflowed
overflowed = p2.distance(circ_point)
#get the vector from our curr_pos to circpoint, call it incident
incident = np.array([circ_point[0] - p1[0], circ_point[1] - p1[1]])
#circpoint to origin vector
normal = np.array([circ_point[0], circ_point[1]])
#-find the angle between incident and normal using dot product wali equation, call that theta
if p1.equals(circ_point):
randomWalk_x.append(old_x)
randomWalk_y.append(old_y)
counter+=1
continue
dot = (circ_point[0]*incident[0]) + (circ_point[1]*incident[1])
magnitude1 = (circ_point[0]**2 + circ_point[1]**2)**(0.5)
magnitude2 = (incident[0]**2 + incident[1]**2)**(0.5)
ang = dot / (magnitude1 * magnitude2)
main_ang = math.acos(ang)
Theta = main_ang
if p2[0] < 0 and p2[1] > 0: #second
Theta = -Theta
elif p2[0] > 0 and p2[1] > 0: #first
if incident[1] >= incident[0]:
Theta = (-Theta)
else:
Theta = (Theta)
elif p2[0] > 0 and p2[1] < 0:
if incident[1] > -incident[0]: #fourth
Theta = (-Theta)
elif p2[0] < 0 and p2[1] < 0:
if incident[1] <= incident[0]:
Theta = (-Theta)
#-form a 2x2 rotation matrix, uska format dekh lo aram se mile ga
rotation_matrix = np.array([[np.cos(Theta), -np.sin(Theta)],[np.sin(Theta), np.cos(Theta)]])
#-multiply the rotation matrix by the normal vector to get another 2x1 vector, call it reflected
reflected = np.dot(rotation_matrix, normal)
reflected *= -1
#-find the unit vector in the direction of reflected, call it ref_unit
ref_unit = reflected / math.sqrt(reflected[0]**2 + reflected[1]**2)
#-scalar multiply ref_unit with overflow
ref_point = ref_unit * overflowed
#-us vector ke components ko add to circpoint ke coordinates to get the final coordinates
final = circ_point + ref_point
#-add both circ point (optional but will look better) and final coord to the arrays
randomWalk_x.append(circ_point[0])
randomWalk_y.append(circ_point[1])
distance_from_origin = math.sqrt((final[0])**2 + (final[1])**2)
counter+=1
if distance_from_origin >= Radius:
continue
else:
randomWalk_x.append(final[0])
randomWalk_y.append(final[1])
step_addition += 1
continue
randomWalk_x.append(new_x)
randomWalk_y.append(new_y)
counter += 1
### Uncomment to see plot
#return distance_from_origin
#########################
size = size + step_addition
#########################################################
#UNCOMMENT FOR ANIMATION
# xdata, ydata = [], []
# ln, = plt.plot(xdata,ydata)
# def init():
# #Radius = 5.64189584 when area of circle = 100 unit^2
# axs.set_xlim(-Radius,Radius)
# axs.set_ylim(-Radius,Radius)
# ln.set_data([], [])
# return ln,
# def update(frame):
# xdata.append(randomWalk_x[int(frame)])
# ydata.append(randomWalk_y[int(frame)])
# ln.set_data(xdata, ydata)
# return ln,
# ani = FuncAnimation(fig, update, frames=np.linspace(0, size, size+1, endpoint=True), interval = 20,
# init_func=init, blit=True, repeat=False)
#ANIMATION CODE
########################################################
circle1=plt.Circle((0,0),Radius,color='r', alpha= 0.2)
plt.gcf().gca().add_artist(circle1)
plt.plot(randomWalk_x, randomWalk_y)
plt.show()
target_p = np.array([300,0])
UAV = Point(UAV_p)
target = Point(target_p)
R0 = 100 # 最小转弯半径
phi0 = 1.745 # 速度方向 [0,2pi]
# 以上为所有已知信息
# 1. 求两个圆心，判断出采用哪一个圆
# 2. 求切线
# 3. 确定用那一段弧长
# 1.求两个圆心，判断出采用哪一个圆
c1 = Point(UAV.x + R0 * np.sin(phi0), UAV.y - R0 * np.cos(phi0))
c2 = Point(UAV.x - R0 * np.sin(phi0), UAV.y + R0 * np.cos(phi0))
len1 = c1.distance(target)
len2 = c2.distance(target)
minc=c1 if len1<len2 else c2
maxc=c1 if len1>len2 else c2
center=minc
type=2
if type == 0:
if minc.distance(target) <= R0:
# 如果小的dubins曲线到达不了，就用大的
print('给定半径最短Dubins路径无法到达，R0=%d', R0)
print(UAV.site)
print(target[0:2])
exec()
elif type == 1:
if minc.distance(target) <= R0:
# 如果小的dubins曲线到达不了，就用大的
def findDistanceBWcomp(comp1, comp2):
point1 = Point(int(comp1[0]), int(comp1[1]))
point2 = Point(int(comp2[0]), int(comp2[1]))
return int(point1.distance(point2))
import numpy as np
from sympy import Matrix, init_printing, eye, symbols, simplify, sqrt, pprint, Point
from sympy.plotting import plot
init_printing(use_unicode=True)
x1, x2 = symbols('x1 x2')
a = Point([1, 0])
b = Point(3, -2)
a.distance(b)
J = Matrix(3, 3, [1, 0, 0, a.distance(b), 1, 0, 0, 0, -1])
M = Matrix(3, 3, [1, 0, 0, a.distance(b), 1, 0, 0, 0, -1])
pprint(M * Matrix([1, 1, 0]))
def sendFaceImages(self):
self.statusLabel.set_text("Obrada uzoraka")
detector = dlib.get_frontal_face_detector()
predictor = dlib.shape_predictor("ldm.dat")
for i in range(0, 7):
gray = cv2.imread("Camera/Resources/" + str(i) + '.png', cv2.CV_8UC1)
#gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
rects = detector(gray, 1)
# loop over the face detections
for (j, rect) in enumerate(rects):
shape = predictor(gray, rect)
shape = face_utils.shape_to_np(shape)
angle = self.calculateFaceTilt(Point(shape[39]), Point(shape[42]))
gray = self.rotateImage(gray, angle, tuple(shape[33]))
#gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
rects = detector(gray, 1)
# loop over the face detections
for (k, rect) in enumerate(rects):
shape = predictor(gray, rect)
shape = face_utils.shape_to_np(shape)
eye = Point(shape[37])
eyebrow = Point(shape[19])
left = Point(min(shape, key=itemgetter(0)))
top = Point(min(shape, key=itemgetter(1)))
right = Point(max(shape, key=itemgetter(0)))
bottom = Point(max(shape, key=itemgetter(1)))
gray = gray[int(top.y - eye.distance(eyebrow) / 2):int(top.y + top.distance(bottom)),
int(left.x):int(left.x + left.distance(right))]
#ujednacavanje histograma
clahe = cv2.createCLAHE(clipLimit=2.0, tileGridSize=(8, 8))
gray = clahe.apply(gray)
#gray = cv2.bilateralFilter(gray, 9, 75, 75)
ratio = 300.0 / gray.shape[1]
dimensions = (300, int(gray.shape[0] * ratio))
gray = cv2.resize(gray, dimensions, interpolation=cv2.INTER_AREA)
cv2.imwrite("Camera/Resources/" + str(i) + '.png', gray)
for i in range(0, 7):
self.statusLabel.set_text("Slanje uzoraka")
client.send("ftp:" + str(i))
self.waitForResponse()
imageFile = open("Camera/Resources/" + str(i) + '.png', "rb")
offset = 0
while True:
sent = sendfile(client.fileno(), imageFile.fileno(), offset, 4096)
if sent == 0:
client.send("EOF")
break # EOF
offset += sent
self.statusLabel.set_text("Potvrdite PIN")
self.btnConfirm.set_sensitive(True)
self.waitForResponse()
