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trajectories.py
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trajectories.py
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import torch
import torch.nn as nn
import numpy as np
import unittest
def look_at_deepvoxels(translation, point):
'''Look at function that conforms with DeepVoxels, DeepSpace and DeepClouds coordinate system: Camera
looks in negative z direction.
:param translation:
:param point:
:return:
'''
target_pose = np.zeros((4,4))
target_pose[:3,3] = translation
direction = point - translation
dir_norm = direction / np.linalg.norm(direction)
tmp = np.array([0.,1.,0.])
right_vector = np.cross(tmp,-1. * dir_norm) # Camera points in negative z-direction
right_vector /= np.linalg.norm(right_vector)
up_vector = np.cross(dir_norm, right_vector)
target_pose[:3,2] = dir_norm
target_pose[:3,1] = up_vector
target_pose[:3,0] = right_vector
target_pose[3,3] = 1.
return target_pose
def look_at_cars(translation, point):
'''Look at function that conforms with DeepVoxels, DeepSpace and DeepClouds coordinate system: Camera
looks in negative z direction.
:param translation:
:param point:
:return:
'''
target_pose = np.zeros((4,4))
target_pose[:3,3] = translation
direction = point - translation
dir_norm = direction / np.linalg.norm(direction)
tmp = np.array([0.,0.,1.])
right_vector = np.cross(tmp,-1. * dir_norm) # Camera points in negative z-direction
right_vector /= np.linalg.norm(right_vector)
up_vector = np.cross(dir_norm, right_vector)
target_pose[:3,2] = dir_norm
target_pose[:3,1] = up_vector
target_pose[:3,0] = right_vector
target_pose[3,3] = 1.
return target_pose
def look_at_rooms(translation, point):
'''Look at function that conforms with DeepVoxels, DeepSpace and DeepClouds coordinate system: Camera
looks in negative z direction.
:param translation:
:param point:
:return:
'''
target_pose = np.zeros((4,4))
target_pose[:3,3] = translation
direction = point - translation
dir_norm = direction / np.linalg.norm(direction)
tmp = np.array([0., 1., 0.])
right_vector = np.cross(tmp, dir_norm) # Camera points in negative z-direction
right_vector /= np.linalg.norm(right_vector)
up_vector = np.cross(dir_norm, right_vector)
target_pose[:3,2] = dir_norm
target_pose[:3,1] = up_vector
target_pose[:3,0] = right_vector
target_pose[3,3] = 1.
return target_pose
def rooms_360(look_at_fn, radius=1, num_samples=200, altitude=45):
trajectory = []
virtual_radius = np.cos(np.deg2rad(altitude)) * radius
for angle in np.linspace(0, 2*np.pi, num_samples):
translation = np.array([virtual_radius*np.sin(angle),
0.75,
virtual_radius*np.cos(angle)])
look_at = 2*radius*translation
look_at[1] = 0.75
cam2world = look_at_fn(translation, look_at)
cam2world = torch.from_numpy(cam2world).float()
cam2world[1, 3] = 0.75
cam2world[:3, 1] = torch.Tensor([0., -1., 0.])
trajectory.append(cam2world)
return trajectory
def around(look_at_fn, radius=1, num_samples=200, altitude=45):
'''
:param radius:
:param num_samples:
:param altitude: Altitude in degree.
:return:
'''
trajectory = []
z_coord = np.sin(np.deg2rad(altitude)) * radius
virtual_radius = np.cos(np.deg2rad(altitude)) * radius
for angle in np.linspace(0, 2*np.pi, num_samples):
translation = np.array([virtual_radius*np.sin(angle),
virtual_radius*np.cos(angle),
z_coord])
cam2world = look_at_fn(translation, np.array([0.,0.,0.]))
cam2world = torch.from_numpy(cam2world).float()
trajectory.append(cam2world)
return trajectory
def back_and_forth(look_at_fn, radius=1, num_samples=200, altitude=0):
'''
:param radius:
:param num_samples:
:param altitude: Altitude in degree.
:return:
'''
trajectory = []
z_coord = np.sin(np.deg2rad(altitude)) * radius
virtual_radius = np.cos(np.deg2rad(altitude)) * radius
distances = np.linspace(1, 5, num_samples)
distances = np.concatenate((distances, distances[::-1]), axis=-1)
for distance in distances:
translation = np.array([virtual_radius*np.sin(0),
virtual_radius*np.cos(0),
z_coord]) * distance
cam2world = look_at_fn(translation, np.array([0.,0.,0.]))
cam2world = torch.from_numpy(cam2world).float()
trajectory.append(cam2world)
return trajectory