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# | |
# Copyright (C) 2023, Inria | |
# GRAPHDECO research group, https://team.inria.fr/graphdeco | |
# All rights reserved. | |
# | |
# This software is free for non-commercial, research and evaluation use | |
# under the terms of the LICENSE.md file. | |
# | |
# For inquiries contact [email protected] | |
# | |
import torch | |
import math | |
import numpy as np | |
from typing import NamedTuple | |
import torch.nn as nn | |
import torch.nn.functional as F | |
from torch.functional import norm | |
class BasicPointCloud(NamedTuple): | |
points : np.array | |
colors : np.array | |
normals : np.array | |
def geom_transform_points(points, transf_matrix): | |
P, _ = points.shape | |
ones = torch.ones(P, 1, dtype=points.dtype, device=points.device) | |
points_hom = torch.cat([points, ones], dim=1) | |
points_out = torch.matmul(points_hom, transf_matrix.unsqueeze(0)) | |
denom = points_out[..., 3:] + 0.0000001 | |
return (points_out[..., :3] / denom).squeeze(dim=0) | |
def getWorld2View(R, t): | |
Rt = np.zeros((4, 4)) | |
Rt[:3, :3] = R.transpose() | |
Rt[:3, 3] = t | |
Rt[3, 3] = 1.0 | |
return np.float32(Rt) | |
def getWorld2View2(R, t, translate=np.array([.0, .0, .0]), scale=1.0): | |
Rt = np.zeros((4, 4)) | |
Rt[:3, :3] = R.transpose() | |
Rt[:3, 3] = t | |
Rt[3, 3] = 1.0 | |
C2W = np.linalg.inv(Rt) | |
cam_center = C2W[:3, 3] | |
cam_center = (cam_center + translate) * scale | |
C2W[:3, 3] = cam_center | |
Rt = np.linalg.inv(C2W) | |
return np.float32(Rt) | |
def getProjectionMatrix(znear, zfar, fovX, fovY): | |
tanHalfFovY = math.tan((fovY / 2)) | |
tanHalfFovX = math.tan((fovX / 2)) | |
top = tanHalfFovY * znear | |
bottom = -top | |
right = tanHalfFovX * znear | |
left = -right | |
P = torch.zeros(4, 4) | |
z_sign = 1.0 | |
P[0, 0] = 2.0 * znear / (right - left) | |
P[1, 1] = 2.0 * znear / (top - bottom) | |
P[0, 2] = (right + left) / (right - left) | |
P[1, 2] = (top + bottom) / (top - bottom) | |
P[3, 2] = z_sign | |
P[2, 2] = z_sign * zfar / (zfar - znear) | |
P[2, 3] = -(zfar * znear) / (zfar - znear) | |
return P | |
def fov2focal(fov, pixels): | |
return pixels / (2 * math.tan(fov / 2)) | |
def focal2fov(focal, pixels): | |
return 2*math.atan(pixels/(2*focal)) | |