def test_f():
"""
Test f(input, K, obj_point)
:return:
"""
alpha = 0
belt = 0
r = 1
input = [0.0, 0.0, 0.0]
input[0] = alpha
input[1] = belt
input[2] = r
cam = Camera()
cam.set_K(fx=800, fy=800, cx=640 / 2., cy=480 / 2.)
cam.set_width_heigth(640, 480)
cam.set_R_mat(
Rt_matrix_from_euler_t.R_matrix_from_euler_t(0, np.deg2rad(0), 0))
cam.set_t(0., 0., 0.5, 'world')
pl = CircularPlane(origin=np.array([0., 0., 0.]),
normal=np.array([0, 0, 1]),
radius=0.15,
n=4)
x1 = round(pl.radius * np.cos(np.deg2rad(45)), 3)
y1 = round(pl.radius * np.sin(np.deg2rad(45)), 3)
objectPoints_square = np.array([[x1, -x1, -x1, x1], [y1, y1, -y1, -y1],
[0., 0., 0., 0.], [1., 1., 1., 1.]])
new_objectPoints = np.copy(objectPoints_square)
cms.f(input, cam.K, new_objectPoints)
def accuracy_func(plane_size=(0.3, 0.3),camera_intrinsic_params=(800.,800.,320.,240.), theta_params=(0.0, 180.0, 5), r_params=(0.1, 2.0, 5), z=0, y=0):
"""
Calculate the accuracy degree of given position y,z in world
y:
z:
:return 0 means the cam is out of range of marker
"""
# --------------------------------------accuracy_degree_distribution---------------------
cam = Camera()
fx = camera_intrinsic_params[0]
fy = camera_intrinsic_params[1]
cx = camera_intrinsic_params[2]
cy = camera_intrinsic_params[3]
cam.set_K(fx=fx, fy=fy, cx=cx, cy=cy)
width = cx * 2
height = cy * 2
cam.set_width_heigth(width, height)
cams,accuracy_mat = create_cam_distribution_in_YZ(cam=None, plane_size=plane_size, theta_params=theta_params, r_params=r_params,
plot=False)
accuracy_mat = np.zeros([30, 60]) # define the new acc_mat as 30 x 30 ,which means 3m x 3m area in real world and each cell is 0.1m x 0.1m
inputX, inputY, inputZ, input_ippe1_t, input_ippe1_R, input_ippe2_t, input_ippe2_R, input_pnp_t, input_pnp_R, input_transfer_error, display_mat,accuracy_mat_new = bf.heightGetCondNum(cams,accuracy_mat,theta_params, r_params)
# print accuracy_mat_new
# --------------------------------------------------------------------------------------------
degree = 5 # divide accuracy into 5 degree
r = np.sqrt(z * z + y * y)
# out of range
if r >= r_params[1] or r == 0:
return 0
else:
# according to radius and angle of cam, Calculate the index of accuracy matrix
r_begin = r_params[0]
r_end = r_params[1]
r_num = r_params[2]
r_step = (r_end - r_begin) / (r_num - 1)
# print "r_step",r_step
half_r_step = r_step / 2.0
r_num1 = math.floor(r / r_step)
r_num2 = math.floor((r - r_step * r_num1) / half_r_step)
row_index = int(r_num1 + r_num2) # row index
angle_begin = theta_params[0]
angle_end = theta_params[1]
angle_num = theta_params[2]
angle_step = (angle_end - angle_begin) / (angle_num - 1)
# print "angle_step",angle_step
half_angle_step = angle_step / 2.0
angle = np.rad2deg(np.arccos(y / r)) # deg
angle_num1 = math.floor(angle / angle_step)
angle_num2 = math.floor((angle - angle_step * angle_num1) / half_angle_step)
col_index = int(angle_num1 + angle_num2)
# print "row_index,col_index",row_index,col_index
acc_degree = accuracy_mat_new[row_index, col_index]
# print "acc_degree",acc_degree
return acc_degree
def cam_distribution_study():
"""
cam Distribution in 3D, show the cond num distribution for each cam position
"""
number_of_points = 4
# TODO Change the radius of circular plane
pl = CircularPlane(origin=np.array([0., 0., 0.]), normal=np.array([0, 0, 1]), radius=0.15, n=4)
pl.random(n=number_of_points, r=0.01, min_sep=0.01)
plane_size = (0.3, 0.3)
cam = Camera()
cam.set_K(fx=800, fy=800, cx=640 / 2., cy=480 / 2.)
cam.set_width_heigth(640, 480)
# TODO cam distribution position PARAMETER CHANGE!!!
# cams = create_cam_distribution(cam, plane_size,
# theta_params=(0, 360, 30), phi_params=(0, 70, 10),
# r_params=(0.2, 2.0, 20), plot=False)
angle_begin = 0.0#0.0
angle_end = 180.0#180.0
angle_num = 37 #37 TODO need to set
# angle_step = (angle_end - angle_begin) / (angle_num - 1)
theta_params = (angle_begin,angle_end,angle_num)
r_begin = 0.1 # we cant set this as 0.0 !!! avoid float error!!!
r_end = 3.0
r_num = 30 #30 TODO need to set
# r_step = (r_end - r_begin) / (r_num - 1)
r_params = (r_begin,r_end,r_num)
cams,accuracy_mat = create_cam_distribution_in_YZ(cam=None, plane_size=(0.3, 0.3), theta_params=theta_params, r_params=r_params,
plot=False)
# TODO
accuracy_mat = np.zeros([30, 60])# define the new acc_mat as 30 x 30 ,which means 3m x 3m area in real world and each cel
inputX, inputY, inputZ, input_ippe1_t, input_ippe1_R, input_ippe2_t, input_ippe2_R, input_pnp_t, input_pnp_R, input_transfer_error, display_mat, accuracy_mat_new = bf.heightGetCondNum(
cams, accuracy_mat, theta_params, r_params)
# print "accuracy_mat distribution:\n",accuracy_mat_new
print "----------------Start to show:-------------------"
# print "accuracy_mat_new\n",accuracy_mat_new
# save accuracy matrix in file
print "-----accuracy_mat_new---------\n",accuracy_mat_new
smtf.saveMatToFile(accuracy_mat_new)
# plot condition number distribution
# dc.displayCondNumDistribution(display_mat)
# plot the Rt error
# dc.displayError_YZ_plane_2D(inputY, inputZ, input_ippe1_t, input_ippe1_R, input_ippe2_t, input_ippe2_R, input_pnp_t, input_pnp_R)
# dc.displayError_YZ_plane_3D(inputY, inputZ, input_ippe1_t, input_ippe1_R, input_ippe2_t, input_ippe2_R, input_pnp_t,
# input_pnp_R, input_transfer_error)
# dc.displayRTError3D_ippe12(inputY, inputZ, input_ippe1_t, input_ippe1_R, input_ippe2_t, input_ippe2_R, input_pnp_t,
# input_pnp_R, input_transfer_error)
# dc.displayRTError3D_LM(inputY, inputZ, input_ippe1_t, input_ippe1_R, input_ippe2_t, input_ippe2_R, input_pnp_t,
# input_pnp_R, input_transfer_error)
# dc.displayRTError3D_EPNP(inputY, inputZ, input_ippe1_t, input_ippe1_R, input_ippe2_t, input_ippe2_R, input_pnp_t,
# input_pnp_R, input_transfer_error)
dc.displayRTError3D_DLS(inputY, inputZ, input_ippe1_t, input_ippe1_R, input_ippe2_t, input_ippe2_R, input_pnp_t,
input_pnp_R, input_transfer_error)
print "----------------End-----------------------------"
def test2_covariance_alpha_belt_r():
"""
Test covariance_alpha_belt_r(cam, new_objectPoints)
X Y fixed, Z changed
:return:
"""
pl = CircularPlane(origin=np.array([0., 0., 0.]),
normal=np.array([0, 0, 1]),
radius=0.15,
n=4)
x1 = round(pl.radius * np.cos(np.deg2rad(45)), 3)
y1 = round(pl.radius * np.sin(np.deg2rad(45)), 3)
objectPoints_square = np.array([[x1, -x1, -x1, x1], [y1, y1, -y1, -y1],
[0., 0., 0., 0.], [1., 1., 1., 1.]])
new_objectPoints = np.copy(objectPoints_square)
# -----------------------------X Y fixed, Z changed-----------------------------
cams_XYfixed = []
for i in np.linspace(0.5, 2, 5):
cam1 = Camera()
cam1.set_K(fx=800, fy=800, cx=640 / 2., cy=480 / 2.)
cam1.set_width_heigth(640, 480)
cam1.set_R_axisAngle(1.0, 0.0, 0.0, np.deg2rad(180.0))
cam1.set_t(0, 0, i, frame='world')
# 0.28075725, -0.23558331, 1.31660688
cams_XYfixed.append(cam1)
zInputs = []
volumes = []
ellipsoid_paras = np.array([[0], [0], [0], [0], [0], [0]]) # a,b,c,x,y,z
for cam in cams_XYfixed:
cam_tem = cam.clone()
valid = cms.validCam(cam_tem, new_objectPoints)
if valid:
t = cam.get_world_position()
zInputs.append(t[2])
print "Height", t[2]
cov_mat = cms.covariance_alpha_belt_r(cam, new_objectPoints)
a, b, c = ellipsoid.get_semi_axes_abc(cov_mat, 0.95)
display_array = np.array(
[[0.0], [0.0], [0.0], [0.0], [0.0], [0.0]], dtype=float)
display_array[0:3, 0] = a, b, c
display_array[3:6, 0] = np.copy(t[0:3])
ellipsoid_paras = np.hstack((ellipsoid_paras, display_array))
v = ellipsoid.ellipsoid_Volume(a, b, c)
print "volumn", v
volumes.append(v)
dvm.displayCovVolume_XYfixed3D(zInputs, volumes)
def Z_fixed_study_square():
cams_HeightFixed = []
cam_1 = Camera()
cam_1.set_K(fx=800, fy=800, cx=640 / 2., cy=480 / 2.)
cam_1.set_width_heigth(640, 480)
cam_1.set_R_axisAngle(1.0, 0.0, 0.0, np.deg2rad(180.0))
cam_1.set_t(0.1, 0.1, 1, frame='world')
cams_HeightFixed.append(cam_1)
cam_2 = Camera()
cam_2.set_K(fx=800, fy=800, cx=640 / 2., cy=480 / 2.)
cam_2.set_width_heigth(640, 480)
cam_2.set_R_axisAngle(1.0, 0.0, 0.0, np.deg2rad(180.0))
cam_2.set_t(-0.1, 0.1, 1, frame='world')
# 0.28075725, -0.23558331, 1.31660688
cams_HeightFixed.append(cam_2)
cam_3 = Camera()
cam_3.set_K(fx=800, fy=800, cx=640 / 2., cy=480 / 2.)
cam_3.set_width_heigth(640, 480)
cam_3.set_R_axisAngle(1.0, 0.0, 0.0, np.deg2rad(180.0))
cam_3.set_t(-0.1, -0.1, 1, frame='world')
# 0.28075725, -0.23558331, 1.31660688
cams_HeightFixed.append(cam_3)
cam_4 = Camera()
cam_4.set_K(fx=800, fy=800, cx=640 / 2., cy=480 / 2.)
cam_4.set_width_heigth(640, 480)
cam_4.set_R_axisAngle(1.0, 0.0, 0.0, np.deg2rad(180.0))
cam_4.set_t(0.1, -0.1, 1, frame='world')
# 0.28075725, -0.23558331, 1.31660688
cams_HeightFixed.append(cam_4)
inputX, inputY, inputZ, input_ippe1_t, input_ippe1_R, input_ippe2_t, input_ippe2_R, input_pnp_t, input_pnp_R, input_transfer_error, display_mat = bf.heightGetCondNum(cams_HeightFixed)
def test3_covariance_alpha_belt_r():
"""
Y fixed, study X Z like a half circle above the marker
:return:
"""
pl = CircularPlane(origin=np.array([0., 0., 0.]),
normal=np.array([0, 0, 1]),
radius=0.15,
n=4)
x1 = round(pl.radius * np.cos(np.deg2rad(45)), 3)
y1 = round(pl.radius * np.sin(np.deg2rad(45)), 3)
objectPoints_square = np.array([[x1, -x1, -x1, x1], [y1, y1, -y1, -y1],
[0., 0., 0., 0.], [1., 1., 1., 1.]])
new_objectPoints = np.copy(objectPoints_square)
# ------------------------------Y fixed, study X Z like a half circle -----------------------------------------
cams_Yfixed = []
for angle in np.linspace(np.deg2rad(0), np.deg2rad(180), 20):
x = np.cos(angle)
z = np.sin(angle)
cam1 = Camera()
cam1.set_K(fx=800, fy=800, cx=640 / 2., cy=480 / 2.)
cam1.set_width_heigth(640, 480)
# TODO WE have not set R yet
# print 'cam1.R',cam1.R
cam1.set_t(x, 0, z, frame='world')
cams_Yfixed.append(cam1)
xInputs = []
zInputs = []
volumes = []
for cam in cams_Yfixed:
cam_tem = cam.clone()
valid = cms.validCam(cam_tem, new_objectPoints)
if valid:
t = cam.get_world_position()
xInputs.append(t[0])
zInputs.append(t[2])
print "x = ", t[0]
print "z = ", t[2]
cov_mat = cms.covariance_alpha_belt_r(cam, new_objectPoints)
a, b, c = ellipsoid.get_semi_axes_abc(cov_mat, 0.95)
v = ellipsoid.ellipsoid_Volume(a, b, c)
print "v", v
volumes.append(v)
dvm.displayCovVolume_Zfixed3D(xInputs, zInputs, volumes)
def test_covariance_alpha_belt_r():
"""
Test covariance_alpha_belt_r(cam, new_objectPoints)
Z fixed, study X Y-
:return:
"""
pl = CircularPlane(origin=np.array([0., 0., 0.]),
normal=np.array([0, 0, 1]),
radius=0.15,
n=4)
x1 = round(pl.radius * np.cos(np.deg2rad(45)), 3)
y1 = round(pl.radius * np.sin(np.deg2rad(45)), 3)
objectPoints_square = np.array([[x1, -x1, -x1, x1], [y1, y1, -y1, -y1],
[0., 0., 0., 0.], [1., 1., 1., 1.]])
new_objectPoints = np.copy(objectPoints_square)
# ------------------------------Z fixed, study X Y-----------------------------------------
cams_Zfixed = []
for x in np.linspace(-0.5, 0.5, 5):
for y in np.linspace(-0.5, 0.5, 5):
cam1 = Camera()
cam1.set_K(fx=800, fy=800, cx=640 / 2., cy=480 / 2.)
cam1.set_width_heigth(640, 480)
# TODO WE have not set R yet
# print 'cam1.R',cam1.R
cam1.set_t(x, y, 1.3, frame='world')
cams_Zfixed.append(cam1)
xInputs = []
yInputs = []
volumes = []
for cam in cams_Zfixed:
cam_tem = cam.clone()
valid = cms.validCam(cam_tem, new_objectPoints)
if valid:
t = cam.get_world_position()
xInputs.append(t[0])
yInputs.append(t[1])
cov_mat = cms.covariance_alpha_belt_r(cam, new_objectPoints)
a, b, c = ellipsoid.get_semi_axes_abc(cov_mat, 0.95)
v = ellipsoid.ellipsoid_Volume(a, b, c)
volumes.append(v)
dvm.displayCovVolume_Zfixed3D(xInputs, yInputs, volumes)
class OptimalPointsSim(object):
""" Class that defines and optimization to obtain optimal control points
configurations for homography and plannar pose estimation. """
def __init__(self):
""" Definition of a simulated camera """
self.cam = Camera()
self.cam.set_K(fx=100, fy=100, cx=640, cy=480)
self.cam.set_width_heigth(1280, 960)
""" Initial camera pose looking stratight down into the plane model """
self.cam.set_R_axisAngle(1.0, 0.0, 0.0, np.deg2rad(180))
self.cam.set_t(0.0, 0.0, 1.5, frame='world')
""" Plane for the control points """
self.sph = Sphere(radius=0.5)
self.sph.random_points(p=6, r=0.5, min_dist=0.001)
def run(self):
self.objectPoints = self.sph.get_sphere_points()
self.init_params = flatten_points(self.objectPoints, type='object')
self.objective1 = lambda params: matrix_condition_number_autograd(
params, self.cam.P, normalize=False)
self.objective2 = lambda params, iter: matrix_condition_number_autograd(
params, self.cam.P, normalize=True)
print("Optimizing condition number...")
objective_grad = grad(self.objective2)
self.optimized_params = adam(objective_grad,
self.init_params,
step_size=0.001,
num_iters=200,
callback=self.plot_points)
def plot_points(self, params, iter, gradient):
phisim = np.linspace((-math.pi) / 2., (math.pi / 2.))
thetasim = np.linspace(0, 2 * np.pi)
print params
pointscoord = np.full((3, 6), 0.0)
for i in range(6):
pointscoord[0, i] = params[i]
pointscoord[1, i] = params[i + 1]
pointscoord[2, i] = params[i + 2]
x = np.outer(np.sin(thetasim), np.cos(phisim))
y = np.outer(np.sin(thetasim), np.sin(phisim))
z = np.outer(np.cos(thetasim), np.ones_like(phisim))
fig, ax = plt.subplots(subplot_kw={'projection': '3d'})
ax.plot_wireframe(sph.radius * x,
sph.radius * y,
sph.radius * z,
color='g')
ax.scatter(pointscoord[:3, 0],
pointscoord[:3, 1],
pointscoord[:3, 2],
c='r')
ax.scatter(pointscoord[:3, 3],
pointscoord[:3, 4],
pointscoord[:3, 5],
c='r')
plt.show()
from vision.rt_matrix import *
import numpy as np
from matplotlib import pyplot as plt
#%%
# load points
points = np.loadtxt('house.p3d').T
points = np.vstack((points, np.ones(points.shape[1])))
#%%
# setup camera
#P = hstack((eye(3),array([[0],[0],[-10]])))
cam = Camera()
## Test matrix functions
cam.set_K(1460, 1460, 608, 480)
cam.set_width_heigth(1280, 960) #TODO Yue
# cam.set_R(0.0, 0.0, 1.0, 0.0)
cam.set_t(0.0, 0.0, -8.0)
cam.set_R_axisAngle(1.0, 0.0, 0.0, np.deg2rad(140.0)) #TODO Yue
cam.set_P()
print(cam.factor())
#%%
x = np.array(cam.project(points))
#%%
# plot projection
plt.figure()
plt.plot(x[0], x[1], 'k.')
plt.xlim(0, 1280)
