def scan_advanced(scanner_object, max_distance = 10.0, evd_file=None, add_blender_mesh = False,
add_noisy_blender_mesh = False, tof_res_x = 176, tof_res_y = 144,
lens_angle_w=43.6, lens_angle_h=34.6, flength = 10.0, evd_last_scan=True,
noise_mu=0.0, noise_sigma=0.004, timestamp = 0.0, backfolding=False,
world_transformation=Matrix()):
inv_scan_x = scanner_object.inv_scan_x
inv_scan_y = scanner_object.inv_scan_y
inv_scan_z = scanner_object.inv_scan_z
start_time = time.time()
#10.0mm is currently the distance between the focal point and the sensor
sensor_width = 2 * math.tan(deg2rad(lens_angle_w/2.0)) * 10.0
sensor_height = 2 * math.tan(deg2rad(lens_angle_h/2.0)) * 10.0
if tof_res_x == 0 or tof_res_y == 0:
raise ValueError("Resolution must be > 0")
pixel_width = sensor_width / float(tof_res_x)
pixel_height = sensor_height / float(tof_res_y)
bpy.context.scene.render.resolution_percentage
width = bpy.context.scene.render.resolution_x
height = bpy.context.scene.render.resolution_y
cx = float(tof_res_x) /2.0
cy = float(tof_res_y) /2.0
evd_buffer = []
rays = []
ray_info = []
ray = Vector([0.0,0.0,0.0])
for x in range(tof_res_x):
for y in range(tof_res_y):
"""Calculate a vector that originates at the principal point
and points to the pixel in the sensor. This vector is then
scaled to the maximum scanning distance
"""
physical_x = float(x-cx) * pixel_width
physical_y = float(y-cy) * pixel_height
physical_z = -float(flength)
ray.xyz = [physical_x, physical_y, physical_z]
ray.normalize()
final_ray = max_distance*ray
rays.extend([final_ray[0],final_ray[1],final_ray[2]])
""" pitch and yaw are added for completeness, normally they are
not provided by a ToF Camera but can be derived
from the pixel position and the camera parameters.
"""
yaw = math.atan(physical_x/flength)
pitch = math.atan(physical_y/flength)
ray_info.append([yaw, pitch, timestamp])
returns = blensor.scan_interface.scan_rays(rays, max_distance, inv_scan_x = inv_scan_x, inv_scan_y = inv_scan_y, inv_scan_z = inv_scan_z)
verts = []
verts_noise = []
evd_storage = evd.evd_file(evd_file, tof_res_x, tof_res_y, max_distance)
reusable_vector = Vector([0.0,0.0,0.0,0.0])
for i in range(len(returns)):
idx = returns[i][-1]
distance_noise = random.gauss(noise_mu, noise_sigma)
#If everything works substitute the previous line with this
#distance_noise = pixel_noise[returns[idx][-1]] + random.gauss(noise_mu, noise_sigma)
reusable_vector.xyzw = [returns[i][1],returns[i][2],returns[i][3],1.0]
vt = (world_transformation * reusable_vector).xyz
v = [returns[i][1],returns[i][2],returns[i][3]]
verts.append ( vt )
vector_length = math.sqrt(v[0]**2+v[1]**2+v[2]**2)
norm_vector = [v[0]/vector_length, v[1]/vector_length, v[2]/vector_length]
vector_length_noise = vector_length+distance_noise
if backfolding:
#Distances > max_distance/2..max_distance are mapped to 0..max_distance/2
if vector_length_noise >= max_distance/2.0:
vector_length_noise = vector_length_noise - max_distance/2.0
reusable_vector.xyzw = [norm_vector[0]*vector_length_noise, norm_vector[1]*vector_length_noise, norm_vector[2]*vector_length_noise,1.0]
v_noise = (world_transformation * reusable_vector).xyz
verts_noise.append( v_noise )
evd_storage.addEntry(timestamp = ray_info[idx][2], yaw =(ray_info[idx][0]+math.pi)%(2*math.pi), pitch=ray_info[idx][1], distance=vector_length, distance_noise=vector_length_noise, x=vt[0], y=vt[1], z=vt[2], x_noise=v_noise[0], y_noise=v_noise[1], z_noise=v_noise[2], object_id=returns[i][4], color=returns[i][5], idx=returns[i][-1])
if evd_file:
evd_storage.appendEvdFile()
if add_blender_mesh:
mesh_utils.add_mesh_from_points_tf(verts, "Scan", world_transformation)
if add_noisy_blender_mesh:
mesh_utils.add_mesh_from_points_tf(verts_noise, "NoisyScan", world_transformation)
bpy.context.scene.update()
end_time = time.time()
scan_time = end_time-start_time
print ("Elapsed time: %.3f"%(scan_time))
return True, 0.0, scan_time
def scan_advanced(scanner_object,
evd_file=None,
evd_last_scan=True,
timestamp=0.0,
world_transformation=Matrix()):
# threshold for comparing projector and camera rays
thresh = 0.01
inv_scan_x = scanner_object.inv_scan_x
inv_scan_y = scanner_object.inv_scan_y
inv_scan_z = scanner_object.inv_scan_z
x_multiplier = -1.0 if inv_scan_x else 1.0
y_multiplier = -1.0 if inv_scan_y else 1.0
z_multiplier = -1.0 if inv_scan_z else 1.0
start_time = time.time()
max_distance = scanner_object.kinect_max_dist
min_distance = scanner_object.kinect_min_dist
add_blender_mesh = scanner_object.add_scan_mesh
add_noisy_blender_mesh = scanner_object.add_noise_scan_mesh
noise_mu = scanner_object.kinect_noise_mu
noise_sigma = scanner_object.kinect_noise_sigma
noise_scale = scanner_object.kinect_noise_scale
noise_smooth = scanner_object.kinect_noise_smooth
res_x = scanner_object.kinect_xres
res_y = scanner_object.kinect_yres
flength = scanner_object.kinect_flength
WINDOW_INLIER_DISTANCE = scanner_object.kinect_inlier_distance
if res_x < 1 or res_y < 1:
raise ValueError("Resolution must be > 0")
pixel_width = max(0.0001, (math.tan(
(parameters["horiz_fov"] / 2.0) * math.pi / 180.0) * flength) /
max(1.0, res_x / 2.0)) #default:0.0078
pixel_height = max(0.0001, (math.tan(
(parameters["vert_fov"] / 2.0) * math.pi / 180.0) * flength) /
max(1.0, res_y / 2.0)) #default:0.0078
print("%f,%f" % (pixel_width, pixel_height))
cx = float(res_x) / 2.0
cy = float(res_y) / 2.0
evd_buffer = []
rays = [0.0] * res_y * res_x * 6
ray_info = [[0.0, 0.0, 0.0]] * res_y * res_x
baseline = Vector([0.075, 0.0,
0.0]) #Kinect has a baseline of 7.5 centimeters
rayidx = 0
ray = Vector([0.0, 0.0, 0.0])
"""Calculate the rays from the projector"""
for y in range(res_y):
for x in range(res_x):
"""Calculate a vector that originates at the principal point
and points to the pixel in the sensor. This vector is then
scaled to the maximum scanning distance
"""
physical_x = float(x - cx) * pixel_width
physical_y = float(y - cy) * pixel_height
physical_z = -float(flength)
#ray = Vector([physical_x, physical_y, physical_z])
ray.xyz = [physical_x, physical_y, physical_z]
ray.normalize()
final_ray = max_distance * ray
rays[rayidx * 6] = final_ray[0]
rays[rayidx * 6 + 1] = final_ray[1]
rays[rayidx * 6 + 2] = final_ray[2]
rays[rayidx * 6 + 3] = baseline.x
rays[rayidx * 6 + 4] = baseline.y
rays[rayidx * 6 + 5] = baseline.z
""" pitch and yaw are added for completeness, normally they are
not provided by a ToF Camera but can be derived
from the pixel position and the camera parameters.
"""
yaw = math.atan(physical_x / flength)
pitch = math.atan(physical_y / flength)
ray_info[rayidx][0] = yaw
ray_info[rayidx][1] = pitch
ray_info[rayidx][2] = timestamp
rayidx += 1
""" Max distance is increased because the kinect is limited by 4m
_normal distance_ to the imaging plane, We don't need shading in the
first pass.
#TODO: the shading requirements might change when transmission
is implemented (the rays might pass through glass)
"""
returns = blensor.scan_interface.scan_rays(rays, 2.0 * max_distance, True,
True, True, True)
camera_rays = []
projector_ray_index = -1 * numpy.ones(len(returns), dtype=numpy.uint32)
kinect_image = numpy.zeros((res_x * res_y, 16))
kinect_image[:, 3:11] = float('NaN')
kinect_image[:, 11] = -1.0
"""Calculate the rays from the camera to the hit points of the projector rays"""
for i in range(len(returns)):
idx = returns[i][-1]
kinect_image[idx, 12:15] = returns[i][5]
if returns[i][0] < max_distance:
camera_rays.extend([
returns[i][1] + baseline.x, returns[i][2] + baseline.y,
returns[i][3] + baseline.z
])
projector_ray_index[i] = idx
camera_returns = blensor.scan_interface.scan_rays(camera_rays,
2 * max_distance, False,
False, False)
evd_storage = evd.evd_file(evd_file,
res_x,
res_y,
max_distance,
output_image=False,
output_noisy=True,
append_frame_counter=False)
all_quantized_disparities = numpy.empty(res_x * res_y)
all_quantized_disparities[:] = INVALID_DISPARITY
disparity_weight = numpy.empty(res_x * res_y)
disparity_weight[:] = INVALID_DISPARITY
all_quantized_disp_mat = all_quantized_disparities.reshape(res_y, res_x)
disp_weight_mat = disparity_weight.reshape(res_y, res_x)
weights = numpy.array([
1.0 / float((1.2 * x)**2 + (1.2 * y)**2) if x != 0 or y != 0 else 1.0
for x in range(-4, 5) for y in range(-4, 5)
]).reshape((9, 9))
"""Build a quantized disparity map"""
for i in range(len(camera_returns)):
idx = camera_returns[i][-1]
projector_idx = projector_ray_index[
idx] # Get the index of the original ray
if (abs(camera_rays[idx * 3] - camera_returns[i][1]) < thresh and
abs(camera_rays[idx * 3 + 1] - camera_returns[i][2]) < thresh
and
abs(camera_rays[idx * 3 + 2] - camera_returns[i][3]) < thresh
and abs(camera_returns[i][3]) <= max_distance
and abs(camera_returns[i][3]) >= min_distance):
"""The ray hit the projected ray, so this is a valid measurement"""
projector_point = get_uv_from_idx(projector_idx, res_x, res_y)
camera_x = get_pixel_from_world(
camera_rays[idx * 3], camera_rays[idx * 3 + 2],
flength / pixel_width) + random.gauss(noise_mu, noise_sigma)
camera_y = get_pixel_from_world(camera_rays[idx * 3 + 1],
camera_rays[idx * 3 + 2],
flength / pixel_width)
""" Kinect calculates the disparity with an accuracy of 1/8 pixel"""
camera_x_quantized = round(camera_x * 8.0) / 8.0
#I don't know if this accurately represents the kinect
camera_y_quantized = round(camera_y * 8.0) / 8.0
disparity_quantized = camera_x_quantized + projector_point[0]
if projector_idx >= 0:
all_quantized_disparities[projector_idx] = disparity_quantized
processed_disparities = numpy.empty(res_x * res_y)
fast_9x9_window(all_quantized_disparities, res_x, res_y,
processed_disparities, noise_smooth, noise_scale)
"""We reuse the vector objects to spare us the object creation every
time
"""
v = Vector([0.0, 0.0, 0.0])
vn = Vector([0.0, 0.0, 0.0])
"""Check if the rays of the camera meet with the rays of the projector and
add them as valid returns if they do"""
image_idx = 0
for i in range(len(camera_returns)):
idx = camera_returns[i][-1]
projector_idx = projector_ray_index[
idx] # Get the index of the original ray
camera_x, camera_y = get_uv_from_idx(projector_idx, res_x, res_y)
if projector_idx >= 0:
disparity_quantized = processed_disparities[projector_idx]
else:
disparity_quantized = INVALID_DISPARITY
if disparity_quantized < INVALID_DISPARITY and disparity_quantized != 0.0:
disparity_quantized = -disparity_quantized
Z_quantized = (flength *
(baseline.x)) / (disparity_quantized * pixel_width)
X_quantized = baseline.x + Z_quantized * camera_x * pixel_width / flength
Y_quantized = baseline.y + Z_quantized * camera_y * pixel_width / flength
Z_quantized = -(Z_quantized + baseline.z)
v.xyz=[x_multiplier*(returns[idx][1]+baseline.x),\
y_multiplier*(returns[idx][2]+baseline.y),\
z_multiplier*(returns[idx][3]+baseline.z)]
vector_length = math.sqrt(v[0]**2 + v[1]**2 + v[2]**2)
vt = (world_transformation * v.to_4d()).xyz
vn.xyz = [
x_multiplier * X_quantized, y_multiplier * Y_quantized,
z_multiplier * Z_quantized
]
vector_length_noise = vn.magnitude
#TODO@mgschwan: prevent object creation here too
v_noise = (world_transformation * vn.to_4d()).xyz
kinect_image[projector_idx] = [
ray_info[projector_idx][2], 0.0, 0.0, -returns[idx][3],
-Z_quantized, vt[0], vt[1], vt[2], v_noise[0], v_noise[1],
v_noise[2], returns[idx][4], returns[idx][5][0],
returns[idx][5][1], returns[idx][5][2], projector_idx
]
image_idx += 1
else:
"""Occlusion"""
#FIXME: Dirty hack to signal we've got an occluded/invalid value
kinect_image[projector_idx] = [
0.0, 0.0, 0.0, 0, numpy.nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
returns[idx][4], returns[idx][5][0], returns[idx][5][1],
returns[idx][5][2], projector_idx
]
pass
for e in kinect_image:
evd_storage.addEntry(timestamp=e[0],
yaw=e[1],
pitch=e[2],
distance=e[3],
distance_noise=e[4],
x=e[5],
y=e[6],
z=e[7],
x_noise=e[8],
y_noise=e[9],
z_noise=e[10],
object_id=e[11],
color=[e[12], e[13], e[14]],
idx=e[15])
if evd_file:
evd_storage.appendEvdFile()
if not evd_storage.isEmpty():
scan_data = numpy.array(evd_storage.buffer)
additional_data = None
if scanner_object.store_data_in_mesh:
additional_data = evd_storage.buffer
if add_blender_mesh:
mesh_utils.add_mesh_from_points_tf(scan_data[:, 5:8],
"Scan",
world_transformation,
buffer=additional_data)
if add_noisy_blender_mesh:
mesh_utils.add_mesh_from_points_tf(scan_data[:, 8:11],
"NoisyScan",
world_transformation,
buffer=additional_data)
bpy.context.scene.update()
end_time = time.time()
scan_time = end_time - start_time
print("Elapsed time: %.3f" % (scan_time))
return True, 0.0, scan_time
def scan_advanced(scanner_object,
simulation_fps=24,
evd_file=None,
noise_mu=0.0,
evd_last_scan=True,
add_blender_mesh=False,
add_noisy_blender_mesh=False,
simulation_time=0.0,
laser_mirror_distance=0.05,
world_transformation=Matrix()):
angle_resolution = scanner_object.generic_angle_resolution
max_distance = scanner_object.generic_max_dist
start_angle = scanner_object.generic_start_angle
end_angle = scanner_object.generic_end_angle
noise_mu = scanner_object.generic_noise_mu
noise_sigma = scanner_object.generic_noise_sigma
laser_angles = scanner_object.generic_laser_angles
rotation_speed = scanner_object.generic_rotation_speed
inv_scan_x = scanner_object.inv_scan_x
inv_scan_y = scanner_object.inv_scan_y
inv_scan_z = scanner_object.inv_scan_z
"""Standard Error model is a Gaussian Distribution"""
model = gaussian_error_model.GaussianErrorModel(noise_mu, noise_sigma)
if scanner_object.generic_advanced_error_model:
"""Advanced error model is a list of distance,mu,sigma tuples"""
model = advanced_error_model.AdvancedErrorModel(
scanner_object.generic_advanced_error_model)
start_time = time.time()
current_time = simulation_time
delta_rot = angle_resolution * math.pi / 180
evd_storage = evd.evd_file(evd_file)
xaxis = Vector([1, 0, 0])
yaxis = Vector([0, 1, 0])
zaxis = Vector([0, 0, 1])
rays = []
ray_info = []
angles = end_angle - start_angle
steps_per_rotation = angles / angle_resolution
time_per_step = (1.0 / rotation_speed) / steps_per_rotation
lines = (end_angle - start_angle) / angle_resolution
laser_angles = angles_from_string(laser_angles)
rays = []
ray_info = []
#Bad code???
#steps_per_rotation = 360.0/angle_resolution
#time_per_step = (1.0 / rotation_speed) / steps_per_rotation
#angles = end_angle-start_angle
lines = (end_angle - start_angle) / angle_resolution
ray = Vector([0.0, 0.0, 0.0])
for line in range(int(lines)):
for laser_idx in range(len(laser_angles)):
ray.xyz = [0, 0, max_distance]
rot_angle = 1e-6 + start_angle + float(
line) * angle_resolution + 180.0
timestamp = (
(rot_angle - 180.0) / angle_resolution) * time_per_step
rot_angle = rot_angle % 360.0
ray_info.append([
deg2rad(rot_angle),
deg2rad(laser_angles[laser_idx]), timestamp
])
rotator = Euler(
[deg2rad(-laser_angles[laser_idx]),
deg2rad(rot_angle), 0.0])
ray.rotate(rotator)
rays.extend([ray[0], ray[1], ray[2]])
returns = blensor.scan_interface.scan_rays(rays,
max_distance,
inv_scan_x=inv_scan_x,
inv_scan_y=inv_scan_y,
inv_scan_z=inv_scan_z)
reusable_vector = Vector([0.0, 0.0, 0.0, 1.0])
if len(laser_angles) != len(laser_noise):
randomize_distance_bias(len(laser_angles), noise_mu, noise_sigma)
vp = (world_transformation * reusable_vector).xyz
for i in range(len(returns)):
idx = returns[i][-1]
# Calculate noise-free point.
reusable_vector.xyzw = [
returns[i][1], returns[i][2], returns[i][3], 1.0
]
vt = (world_transformation * reusable_vector).xyz
v = [returns[i][1], returns[i][2], returns[i][3]]
# Calculate noisy point.
vector_length = math.sqrt(v[0]**2 + v[1]**2 + v[2]**2)
distance_noise = laser_noise[
idx % len(laser_noise)] + model.drawErrorFromModel(vector_length)
norm_vector = [
v[0] / vector_length, v[1] / vector_length, v[2] / vector_length
]
vector_length_noise = vector_length + distance_noise
reusable_vector.xyzw = [
norm_vector[0] * vector_length_noise,
norm_vector[1] * vector_length_noise,
norm_vector[2] * vector_length_noise, 1.0
]
v_noise = (world_transformation * reusable_vector).xyz
evd_storage.addEntry(timestamp=ray_info[idx][2],
yaw=(ray_info[idx][0] + math.pi) % (2 * math.pi),
pitch=ray_info[idx][1],
distance=vector_length,
distance_noise=vector_length_noise,
vp_x=vp[0],
vp_y=vp[1],
vp_z=vp[2],
x=vt[0],
y=vt[1],
z=vt[2],
x_noise=v_noise[0],
y_noise=v_noise[1],
z_noise=v_noise[2],
object_id=returns[i][4],
color=returns[i][5])
current_angle = start_angle + float(float(int(lines)) * angle_resolution)
if evd_file:
evd_storage.appendEvdFile()
if not evd_storage.isEmpty():
scan_data = numpy.array(evd_storage.buffer)
additional_data = None
if scanner_object.store_data_in_mesh:
additional_data = evd_storage.buffer
if add_blender_mesh:
mesh_utils.add_mesh_from_points_tf(scan_data[:, 8:11],
"Scan",
world_transformation,
buffer=additional_data)
if add_noisy_blender_mesh:
mesh_utils.add_mesh_from_points_tf(scan_data[:, 11:14],
"NoisyScan",
world_transformation,
buffer=additional_data)
bpy.context.scene.update()
end_time = time.time()
scan_time = end_time - start_time
print("Elapsed time: %.3f" % (scan_time))
return True, current_angle, scan_time
def scan_advanced(scanner_object, evd_file=None,
evd_last_scan=True,
timestamp = 0.0,
world_transformation=Matrix()):
# threshold for comparing projector and camera rays
thresh = 0.01
inv_scan_x = scanner_object.inv_scan_x
inv_scan_y = scanner_object.inv_scan_y
inv_scan_z = scanner_object.inv_scan_z
x_multiplier = -1.0 if inv_scan_x else 1.0
y_multiplier = -1.0 if inv_scan_y else 1.0
z_multiplier = -1.0 if inv_scan_z else 1.0
start_time = time.time()
max_distance = scanner_object.kinect_max_dist
min_distance = scanner_object.kinect_min_dist
add_blender_mesh = scanner_object.add_scan_mesh
add_noisy_blender_mesh = scanner_object.add_noise_scan_mesh
noise_mu = scanner_object.kinect_noise_mu
noise_sigma = scanner_object.kinect_noise_sigma
noise_scale = scanner_object.kinect_noise_scale
noise_smooth = scanner_object.kinect_noise_smooth
res_x = scanner_object.kinect_xres
res_y = scanner_object.kinect_yres
flength = scanner_object.kinect_flength
WINDOW_INLIER_DISTANCE = scanner_object.kinect_inlier_distance
if res_x < 1 or res_y < 1:
raise ValueError("Resolution must be > 0")
pixel_width = 0.0078
pixel_height = 0.0078
cx = float(res_x) /2.0
cy = float(res_y) /2.0
evd_buffer = []
rays = [0.0]*res_y*res_x*6
ray_info = [[0.0,0.0,0.0]]*res_y*res_x
baseline = Vector([0.075,0.0,0.0]) #Kinect has a baseline of 7.5 centimeters
rayidx=0
ray = Vector([0.0,0.0,0.0])
"""Calculate the rays from the projector"""
for y in range(res_y):
for x in range(res_x):
"""Calculate a vector that originates at the principal point
and points to the pixel in the sensor. This vector is then
scaled to the maximum scanning distance
"""
physical_x = float(x-cx) * pixel_width
physical_y = float(y-cy) * pixel_height
physical_z = -float(flength)
#ray = Vector([physical_x, physical_y, physical_z])
ray.xyz=[physical_x, physical_y, physical_z]
ray.normalize()
final_ray = max_distance*ray
rays[rayidx*6] = final_ray[0]
rays[rayidx*6+1] = final_ray[1]
rays[rayidx*6+2] = final_ray[2]
rays[rayidx*6+3] = baseline.x
rays[rayidx*6+4] = baseline.y
rays[rayidx*6+5] = baseline.z
""" pitch and yaw are added for completeness, normally they are
not provided by a ToF Camera but can be derived
from the pixel position and the camera parameters.
"""
yaw = math.atan(physical_x/flength)
pitch = math.atan(physical_y/flength)
ray_info[rayidx][0] = yaw
ray_info[rayidx][1] = pitch
ray_info[rayidx][2] = timestamp
rayidx += 1
""" Max distance is increased because the kinect is limited by 4m
_normal distance_ to the imaging plane, We don't need shading in the
first pass.
#TODO: the shading requirements might change when transmission
is implemented (the rays might pass through glass)
"""
returns = blensor.scan_interface.scan_rays(rays, 2.0*max_distance, True,True,True,True)
camera_rays = []
projector_ray_index = -1 * numpy.ones(len(returns), dtype=numpy.uint32)
kinect_image = numpy.zeros((res_x*res_y,16))
kinect_image[:,3:11] = float('NaN')
kinect_image[:,11] = -1.0
"""Calculate the rays from the camera to the hit points of the projector rays"""
for i in range(len(returns)):
idx = returns[i][-1]
kinect_image[idx,12:15] = returns[i][5]
if returns[i][0] < max_distance:
camera_rays.extend([returns[i][1]+baseline.x, returns[i][2]+baseline.y,
returns[i][3]+baseline.z])
projector_ray_index[i] = idx
camera_returns = blensor.scan_interface.scan_rays(camera_rays, 2*max_distance, False,False,False)
verts = []
verts_noise = []
evd_storage = evd.evd_file(evd_file, res_x, res_y, max_distance)
all_quantized_disparities = numpy.empty(res_x*res_y)
all_quantized_disparities[:] = INVALID_DISPARITY
disparity_weight = numpy.empty(res_x*res_y)
disparity_weight[:] = INVALID_DISPARITY
all_quantized_disp_mat = all_quantized_disparities.reshape(res_y,res_x)
disp_weight_mat = disparity_weight.reshape(res_y,res_x)
weights = numpy.array([1.0/float((1.2*x)**2+(1.2*y)**2) if x!=0 or y!=0 else 1.0 for x in range(-4,5) for y in range (-4,5)]).reshape((9,9))
"""Build a quantized disparity map"""
for i in range(len(camera_returns)):
idx = camera_returns[i][-1]
projector_idx = projector_ray_index[idx] # Get the index of the original ray
if (abs(camera_rays[idx*3]-camera_returns[i][1]) < thresh and
abs(camera_rays[idx*3+1]-camera_returns[i][2]) < thresh and
abs(camera_rays[idx*3+2]-camera_returns[i][3]) < thresh and
abs(camera_returns[i][3]) <= max_distance and
abs(camera_returns[i][3]) >= min_distance):
"""The ray hit the projected ray, so this is a valid measurement"""
projector_point = get_uv_from_idx(projector_idx, res_x,res_y)
camera_x = get_pixel_from_world(camera_rays[idx*3],camera_rays[idx*3+2],
flength/pixel_width) + random.gauss(noise_mu, noise_sigma)
camera_y = get_pixel_from_world(camera_rays[idx*3+1],camera_rays[idx*3+2],
flength/pixel_width)
""" Kinect calculates the disparity with an accuracy of 1/8 pixel"""
camera_x_quantized = round(camera_x*8.0)/8.0
#I don't know if this accurately represents the kinect
camera_y_quantized = round(camera_y*8.0)/8.0
disparity_quantized = camera_x_quantized + projector_point[0]
if projector_idx >= 0:
all_quantized_disparities[projector_idx] = disparity_quantized
processed_disparities = numpy.empty(res_x*res_y)
fast_9x9_window(all_quantized_disparities, res_x, res_y, processed_disparities, noise_smooth, noise_scale)
"""We reuse the vector objects to spare us the object creation every
time
"""
v = Vector([0.0,0.0,0.0])
vn = Vector([0.0,0.0,0.0])
"""Check if the rays of the camera meet with the rays of the projector and
add them as valid returns if they do"""
image_idx = 0
for i in range(len(camera_returns)):
idx = camera_returns[i][-1]
projector_idx = projector_ray_index[idx] # Get the index of the original ray
camera_x,camera_y = get_uv_from_idx(projector_idx, res_x,res_y)
if projector_idx >= 0:
disparity_quantized = processed_disparities[projector_idx]
else:
disparity_quantized = INVALID_DISPARITY
if disparity_quantized < INVALID_DISPARITY and disparity_quantized != 0.0:
disparity_quantized = -disparity_quantized
Z_quantized = (flength*(baseline.x))/(disparity_quantized*pixel_width)
X_quantized = baseline.x+Z_quantized*camera_x*pixel_width/flength
Y_quantized = baseline.y+Z_quantized*camera_y*pixel_width/flength
Z_quantized = -(Z_quantized+baseline.z)
v.xyz=[x_multiplier*(returns[idx][1]+baseline.x),\
y_multiplier*(returns[idx][2]+baseline.y),\
z_multiplier*(returns[idx][3]+baseline.z)]
vector_length = math.sqrt(v[0]**2+v[1]**2+v[2]**2)
vt = (world_transformation * v.to_4d()).xyz
verts.append ( vt )
vn.xyz = [x_multiplier*X_quantized,y_multiplier*Y_quantized,z_multiplier*Z_quantized]
vector_length_noise = vn.magnitude
#TODO@mgschwan: prevent object creation here too
v_noise = (world_transformation * vn.to_4d()).xyz
verts_noise.append( v_noise )
kinect_image[projector_idx] = [ray_info[projector_idx][2],
0.0, 0.0, -returns[idx][3], -Z_quantized, vt[0],
vt[1], vt[2], v_noise[0], v_noise[1], v_noise[2],
returns[idx][4], returns[idx][5][0], returns[idx][5][1],
returns[idx][5][2],projector_idx]
image_idx += 1
else:
"""Occlusion"""
pass
for e in kinect_image:
evd_storage.addEntry(timestamp = e[0], yaw = e[1], pitch=e[2],
distance=e[3], distance_noise=e[4], x=e[5], y=e[6], z=e[7],
x_noise=e[8], y_noise=e[9], z_noise=e[10], object_id=e[11],
color=[e[12],e[13],e[14]], idx=e[15])
if evd_file:
evd_storage.appendEvdFile()
if add_blender_mesh:
mesh_utils.add_mesh_from_points_tf(verts, "Scan", world_transformation)
if add_noisy_blender_mesh:
mesh_utils.add_mesh_from_points_tf(verts_noise, "NoisyScan", world_transformation)
bpy.context.scene.update()
end_time = time.time()
scan_time = end_time-start_time
print ("Elapsed time: %.3f"%(scan_time))
return True, 0.0, scan_time
def scan_advanced(scanner_object,
rotation_speed=25.0,
simulation_fps=24,
angle_resolution=0.5,
max_distance=90,
evd_file=None,
noise_mu=0.0,
noise_sigma=0.03,
start_angle=-35,
end_angle=50,
evd_last_scan=True,
add_blender_mesh=False,
add_noisy_blender_mesh=False,
simulation_time=0.0,
laser_mirror_distance=0.05,
world_transformation=Matrix()):
inv_scan_x = scanner_object.inv_scan_x
inv_scan_y = scanner_object.inv_scan_y
inv_scan_z = scanner_object.inv_scan_z
start_time = time.time()
current_time = simulation_time
delta_rot = angle_resolution * math.pi / 180
evd_storage = evd.evd_file(evd_file)
xaxis = Vector([1, 0, 0])
yaxis = Vector([0, 1, 0])
zaxis = Vector([0, 0, 1])
rays = []
ray_info = []
angles = end_angle - start_angle
steps_per_rotation = angles / angle_resolution
time_per_step = (1.0 / rotation_speed) / steps_per_rotation
lines = (end_angle - start_angle) / angle_resolution
for line in range(int(lines)):
for laser_idx in range(len(laser_angles)):
current_angle = start_angle + float(line) * angles / float(lines)
[ray, origion, laser_angle] = calculateRay(laser_angles[laser_idx],
deg2rad(current_angle),
laser_mirror_distance)
#TODO: Use the origin to cast the ray. Requires changes to the blender patch
rot_angle = 1e-6 + current_angle + 180.0
timestamp = (
(rot_angle - 180.0) / angle_resolution) * time_per_step
rot_angle = rot_angle % 360.0
ray_info.append([deg2rad(rot_angle), laser_angle, timestamp])
rays.extend([ray[0], ray[1], ray[2]])
returns = blensor.scan_interface.scan_rays(rays,
max_distance,
inv_scan_x=inv_scan_x,
inv_scan_y=inv_scan_y,
inv_scan_z=inv_scan_z)
reusable_vector = Vector([0.0, 0.0, 0.0, 1.0])
vp = (world_transformation * reusable_vector).xyz
for i in range(len(returns)):
idx = returns[i][-1]
# Calculate noise-free point.
reusable_vector.xyzw = [
returns[i][1], returns[i][2], returns[i][3], 1.0
]
vt = (world_transformation * reusable_vector).xyz
v = [returns[i][1], returns[i][2], returns[i][3]]
# Calculate noisy point.
distance_noise = laser_noise[idx % len(laser_noise)] + random.gauss(
noise_mu, noise_sigma)
vector_length = math.sqrt(v[0]**2 + v[1]**2 + v[2]**2)
norm_vector = [
v[0] / vector_length, v[1] / vector_length, v[2] / vector_length
]
vector_length_noise = vector_length + distance_noise
reusable_vector.xyzw = [
norm_vector[0] * vector_length_noise,
norm_vector[1] * vector_length_noise,
norm_vector[2] * vector_length_noise, 1.0
]
v_noise = (world_transformation * reusable_vector).xyz
evd_storage.addEntry(timestamp=ray_info[idx][2],
yaw=(ray_info[idx][0] + math.pi) % (2 * math.pi),
pitch=ray_info[idx][1],
distance=vector_length,
distance_noise=vector_length_noise,
vp_x=vp[0],
vp_y=vp[1],
vp_z=vp[2],
x=vt[0],
y=vt[1],
z=vt[2],
x_noise=v_noise[0],
y_noise=v_noise[1],
z_noise=v_noise[2],
object_id=returns[i][4],
color=returns[i][5])
current_angle = start_angle + float(float(int(lines)) * angle_resolution)
if evd_file:
evd_storage.appendEvdFile()
if not evd_storage.isEmpty():
scan_data = numpy.array(evd_storage.buffer)
additional_data = None
if scanner_object.store_data_in_mesh:
additional_data = evd_storage.buffer
if add_blender_mesh:
mesh_utils.add_mesh_from_points_tf(scan_data[:, 8:11],
"Scan",
world_transformation,
buffer=additional_data)
if add_noisy_blender_mesh:
mesh_utils.add_mesh_from_points_tf(scan_data[:, 11:14],
"NoisyScan",
world_transformation,
buffer=additional_data)
bpy.context.scene.update()
end_time = time.time()
scan_time = end_time - start_time
print("Elapsed time: %.3f" % (scan_time))
return True, current_angle, scan_time
def scan_advanced(scanner_object,
rotation_speed=10.0,
simulation_fps=24,
angle_resolution=0.1728,
max_distance=120,
evd_file=None,
noise_mu=0.0,
noise_sigma=0.03,
start_angle=0.0,
end_angle=360.0,
evd_last_scan=True,
add_blender_mesh=False,
add_noisy_blender_mesh=False,
frame_time=(1.0 / 24.0),
simulation_time=0.0,
world_transformation=Matrix()):
scanner_angles = laser_angles
scanner_noise = laser_noise
if scanner_object.velodyne_model == BLENSOR_VELODYNE_HDL32E:
scanner_angles = laser_angles_32
inv_scan_x = scanner_object.inv_scan_x
inv_scan_y = scanner_object.inv_scan_y
inv_scan_z = scanner_object.inv_scan_z
start_time = time.time()
current_time = simulation_time
delta_rot = angle_resolution * math.pi / 180
evd_storage = evd.evd_file(evd_file)
xaxis = Vector([1, 0, 0])
yaxis = Vector([0, 1, 0])
zaxis = Vector([0, 0, 1])
rays = []
ray_info = []
steps_per_rotation = 360.0 / angle_resolution
time_per_step = (1.0 / rotation_speed) / steps_per_rotation
angles = end_angle - start_angle
lines = (end_angle - start_angle) / angle_resolution
ray = Vector([0.0, 0.0, 0.0])
for line in range(int(lines)):
for laser_idx in range(len(scanner_angles)):
ray.xyz = [0, 0, max_distance]
rot_angle = 1e-6 + start_angle + float(
line) * angle_resolution + 180.0
timestamp = (
(rot_angle - 180.0) / angle_resolution) * time_per_step
rot_angle = rot_angle % 360.0
ray_info.append([
deg2rad(rot_angle),
deg2rad(scanner_angles[laser_idx]), timestamp
])
rotator = Euler(
[deg2rad(-scanner_angles[laser_idx]),
deg2rad(rot_angle), 0.0])
ray.rotate(rotator)
rays.extend([ray[0], ray[1], ray[2]])
returns = blensor.scan_interface.scan_rays(rays,
max_distance,
inv_scan_x=inv_scan_x,
inv_scan_y=inv_scan_y,
inv_scan_z=inv_scan_z)
reusable_vector = Vector([0.0, 0.0, 0.0, 1.0])
vp = (world_transformation * reusable_vector).xyz
for i in range(len(returns)):
idx = returns[i][-1]
# Calculate noise-free point.
reusable_vector.xyzw = (returns[i][1], returns[i][2], returns[i][3],
1.0)
vt = (world_transformation * reusable_vector).xyz
v = [returns[i][1], returns[i][2], returns[i][3]]
# Calculate noisy point.
distance_noise = laser_noise[idx % len(scanner_angles)] + random.gauss(
noise_mu, noise_sigma)
vector_length = math.sqrt(v[0]**2 + v[1]**2 + v[2]**2)
norm_vector = [
v[0] / vector_length, v[1] / vector_length, v[2] / vector_length
]
vector_length_noise = vector_length + distance_noise
reusable_vector.xyzw = [
norm_vector[0] * vector_length_noise,
norm_vector[1] * vector_length_noise,
norm_vector[2] * vector_length_noise, 1.0
]
v_noise = (world_transformation * reusable_vector).xyz
evd_storage.addEntry(timestamp=ray_info[idx][2],
yaw=(ray_info[idx][0] + math.pi) % (2 * math.pi),
pitch=ray_info[idx][1],
distance=vector_length,
distance_noise=vector_length_noise,
vp_x=vp[0],
vp_y=vp[1],
vp_z=vp[2],
x=vt[0],
y=vt[1],
z=vt[2],
x_noise=v_noise[0],
y_noise=v_noise[1],
z_noise=v_noise[2],
object_id=returns[i][4],
color=returns[i][5])
current_angle = start_angle + float(float(int(lines)) * angle_resolution)
pre_write_time = time.time()
if evd_file:
evd_storage.appendEvdFile()
if not evd_storage.isEmpty():
scan_data = numpy.array(evd_storage.buffer)
additional_data = None
if scanner_object.store_data_in_mesh:
additional_data = evd_storage.buffer
if add_blender_mesh:
mesh_utils.add_mesh_from_points_tf(scan_data[:, 8:11],
"Scan",
world_transformation,
buffer=additional_data)
if add_noisy_blender_mesh:
mesh_utils.add_mesh_from_points_tf(scan_data[:, 11:14],
"NoisyScan",
world_transformation,
buffer=additional_data)
bpy.context.scene.update()
end_time = time.time()
scan_time = pre_write_time - start_time
total_time = end_time - start_time
print("Elapsed time: %.3f (scan: %.3f)" % (total_time, scan_time))
return True, current_angle, scan_time
def scan_advanced(scanner_object, rotation_speed = 25.0, simulation_fps=24, angle_resolution = 0.5, max_distance = 90, evd_file=None,noise_mu=0.0, noise_sigma=0.03, start_angle = -35, end_angle = 50, evd_last_scan=True, add_blender_mesh = False, add_noisy_blender_mesh = False, simulation_time = 0.0,laser_mirror_distance=0.05, world_transformation=Matrix()):
inv_scan_x = scanner_object.inv_scan_x
inv_scan_y = scanner_object.inv_scan_y
inv_scan_z = scanner_object.inv_scan_z
start_time = time.time()
current_time = simulation_time
delta_rot = angle_resolution*math.pi/180
evd_storage = evd.evd_file(evd_file)
xaxis = Vector([1,0,0])
yaxis = Vector([0,1,0])
zaxis = Vector([0,0,1])
rays = []
ray_info = []
angles = end_angle-start_angle
steps_per_rotation = angles/angle_resolution
time_per_step = (1.0/rotation_speed) / steps_per_rotation
lines = (end_angle-start_angle)/angle_resolution
for line in range(int(lines)):
for laser_idx in range(len(laser_angles)):
current_angle = start_angle + float(line)*angles/float(lines)
[ray, origion, laser_angle] = calculateRay(laser_angles[laser_idx], deg2rad(current_angle), laser_mirror_distance)
#TODO: Use the origin to cast the ray. Requires changes to the blender patch
rot_angle = 1e-6 + current_angle + 180.0
timestamp = ( (rot_angle-180.0)/angle_resolution) * time_per_step
rot_angle = rot_angle%360.0
ray_info.append([deg2rad(rot_angle), laser_angle, timestamp])
rays.extend([ray[0],ray[1],ray[2]])
returns = blensor.scan_interface.scan_rays(rays, max_distance, inv_scan_x = inv_scan_x, inv_scan_y = inv_scan_y, inv_scan_z = inv_scan_z)
reusable_vector = Vector([0.0,0.0,0.0,0.0])
for i in range(len(returns)):
idx = returns[i][-1]
reusable_vector.xyzw = [returns[i][1],returns[i][2],returns[i][3],1.0]
vt = (world_transformation * reusable_vector).xyz
v = [returns[i][1],returns[i][2],returns[i][3]]
distance_noise = laser_noise[idx%len(laser_noise)] + random.gauss(noise_mu, noise_sigma)
vector_length = math.sqrt(v[0]**2+v[1]**2+v[2]**2)
norm_vector = [v[0]/vector_length, v[1]/vector_length, v[2]/vector_length]
vector_length_noise = vector_length+distance_noise
reusable_vector.xyzw = [norm_vector[0]*vector_length_noise, norm_vector[1]*vector_length_noise, norm_vector[2]*vector_length_noise,1.0]
v_noise = (world_transformation * reusable_vector).xyz
evd_storage.addEntry(timestamp = ray_info[idx][2], yaw =(ray_info[idx][0]+math.pi)%(2*math.pi), pitch=ray_info[idx][1], distance=vector_length, distance_noise=vector_length_noise, x=vt[0], y=vt[1], z=vt[2], x_noise=v_noise[0], y_noise=v_noise[1], z_noise=v_noise[2], object_id=returns[i][4], color=returns[i][5])
current_angle = start_angle+float(float(int(lines))*angle_resolution)
if evd_file:
evd_storage.appendEvdFile()
if not evd_storage.isEmpty():
scan_data = numpy.array(evd_storage.buffer)
additional_data = None
if scanner_object.store_data_in_mesh:
additional_data = evd_storage.buffer
if add_blender_mesh:
mesh_utils.add_mesh_from_points_tf(scan_data[:,5:8], "Scan", world_transformation, buffer=additional_data)
if add_noisy_blender_mesh:
mesh_utils.add_mesh_from_points_tf(scan_data[:,8:11], "NoisyScan", world_transformation, buffer=additional_data)
bpy.context.scene.update()
end_time = time.time()
scan_time = end_time-start_time
print ("Elapsed time: %.3f"%(scan_time))
return True, current_angle, scan_time
def scan_advanced(scanner_object,
simulation_fps=24,
evd_file=None,
noise_mu=0.0,
evd_last_scan=True,
add_blender_mesh=False,
add_noisy_blender_mesh=False,
simulation_time=0.0,
laser_mirror_distance=0.05,
world_transformation=Matrix()):
angle_resolution = scanner_object.generic_angle_resolution
max_distance = scanner_object.generic_max_dist
start_angle = scanner_object.generic_start_angle
end_angle = scanner_object.generic_end_angle
noise_mu = scanner_object.generic_noise_mu
noise_sigma = scanner_object.generic_noise_sigma
laser_angles = scanner_object.generic_laser_angles
rotation_speed = scanner_object.generic_rotation_speed
start_time = time.time()
current_time = simulation_time
delta_rot = angle_resolution * math.pi / 180
evd_storage = evd.evd_file(evd_file)
xaxis = Vector([1, 0, 0])
yaxis = Vector([0, 1, 0])
zaxis = Vector([0, 0, 1])
rays = []
ray_info = []
angles = end_angle - start_angle
steps_per_rotation = angles / angle_resolution
time_per_step = (1.0 / rotation_speed) / steps_per_rotation
lines = (end_angle - start_angle) / angle_resolution
laser_angles = angles_from_string(laser_angles)
rays = []
ray_info = []
steps_per_rotation = 360.0 / angle_resolution
time_per_step = (1.0 / rotation_speed) / steps_per_rotation
angles = end_angle - start_angle
lines = (end_angle - start_angle) / angle_resolution
ray = Vector([0.0, 0.0, 0.0])
for line in range(int(lines)):
for laser_idx in range(len(laser_angles)):
ray.xyz = [0, 0, max_distance]
rot_angle = 1e-6 + start_angle + float(
line) * angle_resolution + 180.0
timestamp = (
(rot_angle - 180.0) / angle_resolution) * time_per_step
rot_angle = rot_angle % 360.0
ray_info.append([
deg2rad(rot_angle),
deg2rad(laser_angles[laser_idx]), timestamp
])
rotator = Euler(
[deg2rad(-laser_angles[laser_idx]),
deg2rad(rot_angle), 0.0])
ray.rotate(rotator)
rays.extend([ray[0], ray[1], ray[2]])
returns = blensor.scan_interface.scan_rays(rays, max_distance)
verts = []
verts_noise = []
reusable_vector = Vector([0.0, 0.0, 0.0, 0.0])
if len(laser_angles) != len(laser_noise):
randomize_distance_bias(len(laser_angles), noise_mu, noise_sigma)
for i in range(len(returns)):
idx = returns[i][-1]
reusable_vector.xyzw = [
returns[i][1], returns[i][2], returns[i][3], 1.0
]
vt = (world_transformation * reusable_vector).xyz
v = [returns[i][1], returns[i][2], returns[i][3]]
verts.append(vt)
distance_noise = laser_noise[idx % len(laser_noise)] + random.gauss(
noise_mu, noise_sigma)
vector_length = math.sqrt(v[0]**2 + v[1]**2 + v[2]**2)
norm_vector = [
v[0] / vector_length, v[1] / vector_length, v[2] / vector_length
]
vector_length_noise = vector_length + distance_noise
reusable_vector.xyzw = [
norm_vector[0] * vector_length_noise,
norm_vector[1] * vector_length_noise,
norm_vector[2] * vector_length_noise, 1.0
]
v_noise = (world_transformation * reusable_vector).xyz
verts_noise.append(v_noise)
evd_storage.addEntry(timestamp=ray_info[idx][2],
yaw=(ray_info[idx][0] + math.pi) % (2 * math.pi),
pitch=ray_info[idx][1],
distance=vector_length,
distance_noise=vector_length_noise,
x=vt[0],
y=vt[1],
z=vt[2],
x_noise=v_noise[0],
y_noise=v_noise[1],
z_noise=v_noise[2],
object_id=returns[i][4],
color=returns[i][5])
current_angle = start_angle + float(float(int(lines)) * angle_resolution)
if evd_file:
evd_storage.appendEvdFile()
if add_blender_mesh:
mesh_utils.add_mesh_from_points_tf(verts, "Scan", world_transformation)
if add_noisy_blender_mesh:
mesh_utils.add_mesh_from_points_tf(verts_noise, "NoisyScan",
world_transformation)
bpy.context.scene.update()
end_time = time.time()
scan_time = end_time - start_time
print("Elapsed time: %.3f" % (scan_time))
return True, current_angle, scan_time
def scan_advanced(scanner_object, rotation_speed = 10.0, simulation_fps=24, angle_resolution = 0.1728, max_distance = 120, evd_file=None,noise_mu=0.0, noise_sigma=0.03, start_angle = 0.0, end_angle = 360.0, evd_last_scan=True, add_blender_mesh = False, add_noisy_blender_mesh = False, frame_time = (1.0 / 24.0), simulation_time = 0.0, world_transformation=Matrix()):
start_time = time.time()
current_time = simulation_time
delta_rot = angle_resolution*math.pi/180
evd_storage = evd.evd_file(evd_file)
xaxis = Vector([1,0,0])
yaxis = Vector([0,1,0])
zaxis = Vector([0,0,1])
rays = []
ray_info = []
steps_per_rotation = 360.0/angle_resolution
time_per_step = (1.0 / rotation_speed) / steps_per_rotation
angles = end_angle-start_angle
lines = (end_angle-start_angle)/angle_resolution
ray = Vector([0.0,0.0,0.0])
for line in range(int(lines)):
for laser_idx in range(len(laser_angles)):
ray.xyz = [0,0,max_distance]
rot_angle = 1e-6 + start_angle+float(line)*angle_resolution + 180.0
timestamp = ( (rot_angle-180.0)/angle_resolution) * time_per_step
rot_angle = rot_angle%360.0
ray_info.append([deg2rad(rot_angle), deg2rad(laser_angles[laser_idx]), timestamp])
rotator = Euler( [deg2rad(-laser_angles[laser_idx]), deg2rad(rot_angle), 0.0] )
ray.rotate( rotator )
rays.extend([ray[0],ray[1],ray[2]])
returns = blensor.scan_interface.scan_rays(rays, max_distance)
verts = []
verts_noise = []
# for idx in range((len(rays)//3)):
reusable_4dvector = Vector([0.0,0.0,0.0,0.0])
for i in range(len(returns)):
idx = returns[i][-1]
reusable_4dvector.xyzw = (returns[i][1],returns[i][2],returns[i][3],1.0)
vt = (world_transformation * reusable_4dvector).xyz
v = [returns[i][1],returns[i][2],returns[i][3]]
verts.append ( vt )
distance_noise = laser_noise[idx%len(laser_noise)] + random.gauss(noise_mu, noise_sigma)
vector_length = math.sqrt(v[0]**2+v[1]**2+v[2]**2)
norm_vector = [v[0]/vector_length, v[1]/vector_length, v[2]/vector_length]
vector_length_noise = vector_length+distance_noise
reusable_4dvector.xyzw=[norm_vector[0]*vector_length_noise, norm_vector[1]*vector_length_noise, norm_vector[2]*vector_length_noise,1.0]
v_noise = (world_transformation * reusable_4dvector).xyz
verts_noise.append( v_noise )
evd_storage.addEntry(timestamp = ray_info[idx][2], yaw =(ray_info[idx][0]+math.pi)%(2*math.pi), pitch=ray_info[idx][1], distance=vector_length, distance_noise=vector_length_noise, x=vt[0], y=vt[1], z=vt[2], x_noise=v_noise[0], y_noise=v_noise[1], z_noise=v_noise[2], object_id=returns[i][4], color=returns[i][5])
current_angle = start_angle+float(float(int(lines))*angle_resolution)
pre_write_time = time.time()
if evd_file:
evd_storage.appendEvdFile()
if add_blender_mesh:
mesh_utils.add_mesh_from_points_tf(verts, "Scan", world_transformation)
if add_noisy_blender_mesh:
mesh_utils.add_mesh_from_points_tf(verts_noise, "NoisyScan", world_transformation)
bpy.context.scene.update()
end_time = time.time()
scan_time = pre_write_time-start_time
total_time = end_time-start_time
print ("Elapsed time: %.3f (scan: %.3f)"%(total_time, scan_time))
return True, current_angle, scan_time
def scan_advanced(scanner_object, simulation_fps=24, evd_file=None,noise_mu=0.0, evd_last_scan=True, add_blender_mesh = False, add_noisy_blender_mesh = False, simulation_time = 0.0,laser_mirror_distance=0.05, world_transformation=Matrix()):
angle_resolution=scanner_object.generic_angle_resolution
max_distance=scanner_object.generic_max_dist
start_angle=scanner_object.generic_start_angle
end_angle=scanner_object.generic_end_angle
noise_mu = scanner_object.generic_noise_mu
noise_sigma=scanner_object.generic_noise_sigma
laser_angles = scanner_object.generic_laser_angles
rotation_speed = scanner_object.generic_rotation_speed
inv_scan_x = scanner_object.inv_scan_x
inv_scan_y = scanner_object.inv_scan_y
inv_scan_z = scanner_object.inv_scan_z
"""Standard Error model is a Gaussian Distribution"""
model = gaussian_error_model.GaussianErrorModel(noise_mu, noise_sigma)
if scanner_object.generic_advanced_error_model:
"""Advanced error model is a list of distance,mu,sigma tuples"""
model = advanced_error_model.AdvancedErrorModel(scanner_object.generic_advanced_error_model)
start_time = time.time()
current_time = simulation_time
delta_rot = angle_resolution*math.pi/180
evd_storage = evd.evd_file(evd_file)
xaxis = Vector([1,0,0])
yaxis = Vector([0,1,0])
zaxis = Vector([0,0,1])
rays = []
ray_info = []
angles = end_angle-start_angle
steps_per_rotation = angles/angle_resolution
time_per_step = (1.0/rotation_speed) / steps_per_rotation
lines = (end_angle-start_angle)/angle_resolution
laser_angles = angles_from_string(laser_angles)
rays = []
ray_info = []
#Bad code???
#steps_per_rotation = 360.0/angle_resolution
#time_per_step = (1.0 / rotation_speed) / steps_per_rotation
#angles = end_angle-start_angle
lines = (end_angle-start_angle)/angle_resolution
ray = Vector([0.0,0.0,0.0])
for line in range(int(lines)):
for laser_idx in range(len(laser_angles)):
ray.xyz = [0,0,max_distance]
rot_angle = 1e-6 + start_angle+float(line)*angle_resolution + 180.0
timestamp = ( (rot_angle-180.0)/angle_resolution) * time_per_step
rot_angle = rot_angle%360.0
ray_info.append([deg2rad(rot_angle), deg2rad(laser_angles[laser_idx]), timestamp])
rotator = Euler( [deg2rad(-laser_angles[laser_idx]), deg2rad(rot_angle), 0.0] )
ray.rotate( rotator )
rays.extend([ray[0],ray[1],ray[2]])
returns = blensor.scan_interface.scan_rays(rays, max_distance, inv_scan_x = inv_scan_x, inv_scan_y = inv_scan_y, inv_scan_z = inv_scan_z)
verts = []
verts_noise = []
reusable_vector = Vector([0.0,0.0,0.0,0.0])
if len(laser_angles) != len(laser_noise):
randomize_distance_bias(len(laser_angles), noise_mu,noise_sigma)
for i in range(len(returns)):
idx = returns[i][-1]
reusable_vector.xyzw = [returns[i][1],returns[i][2],returns[i][3],1.0]
vt = (world_transformation * reusable_vector).xyz
v = [returns[i][1],returns[i][2],returns[i][3]]
verts.append ( vt )
vector_length = math.sqrt(v[0]**2+v[1]**2+v[2]**2)
distance_noise = laser_noise[idx%len(laser_noise)] + model.drawErrorFromModel(vector_length)
norm_vector = [v[0]/vector_length, v[1]/vector_length, v[2]/vector_length]
vector_length_noise = vector_length+distance_noise
reusable_vector.xyzw = [norm_vector[0]*vector_length_noise, norm_vector[1]*vector_length_noise, norm_vector[2]*vector_length_noise,1.0]
v_noise = (world_transformation * reusable_vector).xyz
verts_noise.append( v_noise )
evd_storage.addEntry(timestamp = ray_info[idx][2], yaw =(ray_info[idx][0]+math.pi)%(2*math.pi), pitch=ray_info[idx][1], distance=vector_length, distance_noise=vector_length_noise, x=vt[0], y=vt[1], z=vt[2], x_noise=v_noise[0], y_noise=v_noise[1], z_noise=v_noise[2], object_id=returns[i][4], color=returns[i][5])
current_angle = start_angle+float(float(int(lines))*angle_resolution)
if evd_file:
evd_storage.appendEvdFile()
if add_blender_mesh:
mesh_utils.add_mesh_from_points_tf(verts, "Scan", world_transformation)
if add_noisy_blender_mesh:
mesh_utils.add_mesh_from_points_tf(verts_noise, "NoisyScan", world_transformation)
bpy.context.scene.update()
end_time = time.time()
scan_time = end_time-start_time
print ("Elapsed time: %.3f"%(scan_time))
return True, current_angle, scan_time
def scan_advanced(scanner_object,
max_distance=120,
filename=None,
add_blender_mesh=False,
world_transformation=Matrix()):
start_time = time.time()
inv_scan_x = scanner_object.inv_scan_x
inv_scan_y = scanner_object.inv_scan_y
inv_scan_z = scanner_object.inv_scan_z
x_multiplier = -1.0 if inv_scan_x else 1.0
y_multiplier = -1.0 if inv_scan_y else 1.0
z_multiplier = -1.0 if inv_scan_z else 1.0
add_noisy_blender_mesh = scanner_object.add_noise_scan_mesh
bpy.context.scene.render.resolution_percentage = 100
bpy.context.scene.render.use_antialiasing = False
width = bpy.context.scene.render.resolution_x
height = bpy.context.scene.render.resolution_y
cx = float(width) / 2.0
cy = float(height) / 2.0
if bpy.context.scene.camera.data.lens_unit == "MILLIMETERS":
flength = bpy.context.scene.camera.data.lens
else:
print("Lens unit has to be millimeters")
return False, 0.0, 0.0
cam_name = bpy.context.scene.camera.name
cam = bpy.data.cameras[cam_name]
# TODO
# - This assumes camera sensor is wider than it is taller.
# - Use the sensor mode to figure out which dimensions to use.
sensor_size = cam.sensor_width
pixel_per_mm = blensor.globals.getPixelPerMillimeter(
width, height, sensor_size)
focal_length = flength * pixel_per_mm
bpy.ops.render.render()
zbuffer = blensorintern.copy_zbuf(bpy.data.images["Render Result"])
depthmap = [0.0] * len(zbuffer)
verts = []
evd_storage = evd.evd_file(filename,
width,
height,
max_distance,
output_image=False,
output_noisy=True,
append_frame_counter=False)
reusable_vector = Vector([0.0, 0.0, 0.0, 0.0])
for idx in range(len(zbuffer)):
x = float(idx % width)
y = float(idx // width)
dx = x - cx
dy = y - cy
ddist = math.sqrt(dx**2 + dy**2)
world_ddist = (ddist * zbuffer[idx]) / focal_length
object_distance = math.sqrt(world_ddist**2 + zbuffer[idx]**2)
if object_distance < max_distance:
depthmap[idx] = object_distance
if add_blender_mesh or add_noisy_blender_mesh:
if object_distance < max_distance:
Z = -zbuffer[idx]
X = -(Z * dx) / focal_length
Y = -(Z * dy) / focal_length
reusable_vector.xyzw = [X, Y, Z, 1.0]
vt = (world_transformation * reusable_vector).xyz
verts.append((x_multiplier * vt[0], y_multiplier * vt[1],
z_multiplier * vt[2]))
# Update evd storage for just the depth data
for idx, val in enumerate(depthmap):
evd_storage.addEntry(distance=val, distance_noise=val, idx=idx)
if filename:
# save using evd file pipeline
evd_storage.appendEvdFile()
# save an additional copy using origin method
#fh = open(filename+".backup", "w")
#fh.buffer.write(struct.pack("ii",width,height))
#for idx in range( width*height ):
# fh.buffer.write(struct.pack("d", depthmap[idx]))
#fh.close()
if add_blender_mesh:
mesh_utils.add_mesh_from_points_tf(verts, "Scan", world_transformation)
if add_noisy_blender_mesh:
mesh_utils.add_mesh_from_points_tf(verts, "NoisyScan",
world_transformation)
bpy.context.scene.update()
end_time = time.time()
scan_time = end_time - start_time
print("Elapsed time: %.3f" % (scan_time))
return True, 0.0, scan_time
