mirror of
https://github.com/graphdeco-inria/gaussian-splatting
synced 2024-11-22 08:18:17 +00:00
77 lines
2.0 KiB
Python
77 lines
2.0 KiB
Python
#
|
|
# 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 george.drettakis@inria.fr
|
|
#
|
|
|
|
import torch
|
|
import math
|
|
import numpy as np
|
|
from typing import NamedTuple
|
|
|
|
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)) |