def hough(img,theta=None):
"""
Apply a linear hough transform to the input image
Input:
- img <ndarray> : Thresholded input image (ndim=2,dtype=float)
- theta <ndarray> : Angle range to search in trsnform space. (ndim=1,dtype=float)
If None, defaults to (-pi/2,pi/2)
Output:
- hough <ndarray> : The hough transform coefficients (ndim=2,dtype=float)
- dists <ndarray> : Distance values (ndim=1,dtype=float)
- theta <ndarray> : Angle values (ndim=1,dtype=float)
---
"""
if img.ndim != 2:
raise ValueError('Input image must be a 2D array');
if not theta:
theta = np.linspace(-np.pi/2,np.pi/2,180);
# Compute the vertical bins (distances)
dist = np.ceil(np.hypot(*img.shape));
nbins = 2*dist;
bins = np.linspace(-dist,dist,nbins);
map = np.zeros((nbins,len(theta)),dtype=np.uint64);
cos_theta = np.cos(theta);
sen_theta = np.sen(theta);
y,x = np.nonzero(img);
for i,(cT,sT) in enumerate(izip(cos_theta,sen_theta)):
dists = x*cT + y*sT;
shift = np.round(dists) - bins[0];
indxs = shift.astype(np.int);
bincount = np.bincount(indxs);
map[:len(bincount),i] = bincount
return map,theta,bins;
def center_callback(self, data):
try:
while True:
rospy.sleep(0.1)
self.servo_head = data.current_pos #relacao engrenagens = 12 pra 20
ang_kinect = 12 * servo_head / 20 #relacao entre servo e kinect
ang_kinect_correto = 1.56 + ang_kinect #angulo do kinect em radianos, tarado para 0 radianos na posicao horizontal para frente
xk = np.round(self.R * np.cos(ang_servo), 2)
zk = np.round(self.R * np.sen(ang_servo), 2)
if ang_servo >= (math.pi / 2):
x = xk - self.xb
x = math.fabs(x)
else:
x = xk + self.xb
z = zk + self.zb
rotx = (math.pi / 2) - ang_servo
br = tf.TransformBroadcaster()
br.sendTransform((x, 0, z), (rotx, 0, 0), rospy.Time.now(), "/base_link", "/kinect_center")
except KeyboardInterrupt:
print("Shutting down")
def proyectily(t): return v_0*np.sen(a)*t - ((g*(t**2))/2)
def derivproyectil(): return v_0*np.sen(a) - (g*t)
def exata(x):
c2=1./70.*(8-12*np.sen(np.log(2))-4*np.cos(np.log(2)))
c1=11./10.-c2
y=c1*x+c2/(x**2)-3./10.*np.sen(np.log(x))-1./10.*np.cos(np.log(x))
return y
def f(i,h):
ai=1
bi=2/(i*h)
ci=-2/((i*h)**2)
di=np.sen(np.log(i*h))/((i*h)**2)
return ai,bi,ci,di
import numpy as np
import time
t_amostragem = int(conflista[i+1])/0.1
V_inic = int(instrument.read_register(1,0))
amp = int(conflista[i+2])/2
instrument.write_register(100, 1)
instrument.write_register(101, 1)
for i in range (1, t_amostragem):
V_ripple = V_inic + amp*np.sen((np.pi*i/10)+(3*np.pi/2)) + amp
instrument.write_register(683, V_ripple)
print (seno)
time.sleep(0.1)
def F6(x):
return np.array([3*x[0]-np.cos(x[1]*x[2])-1/2,
x[0]**2-81*(x[1]+0.1)**2+np.sen(x[2]+1.06),
np.exp(-x[0]*x[1])+20*x[2]+(10*np.pi-3)/3])
def rotacion(puntox,puntoy):
angulo = input("angulo de rotacion")
rotacion = np.matrix([[np.cos(angulo),-np.sen(angulo),0],[np.sen(angulo),np.cos(angulo),0],[0,0,0]])
puntos = np.matrix([puntox],[puntoy],[1])
return rotacion.dot(puntos)