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Running
on
Zero
# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. | |
# | |
# NVIDIA CORPORATION & AFFILIATES and its licensors retain all intellectual property | |
# and proprietary rights in and to this software, related documentation | |
# and any modifications thereto. Any use, reproduction, disclosure or | |
# distribution of this software and related documentation without an express | |
# license agreement from NVIDIA CORPORATION & AFFILIATES is strictly prohibited. | |
import torch | |
from . import Camera | |
import numpy as np | |
def projection(x=0.1, n=1.0, f=50.0, near_plane=None): | |
if near_plane is None: | |
near_plane = n | |
return np.array( | |
[[n / x, 0, 0, 0], | |
[0, n / -x, 0, 0], | |
[0, 0, -(f + near_plane) / (f - near_plane), -(2 * f * near_plane) / (f - near_plane)], | |
[0, 0, -1, 0]]).astype(np.float32) | |
class PerspectiveCamera(Camera): | |
def __init__(self, fovy=49.0, focal=None, device='cuda'): | |
super(PerspectiveCamera, self).__init__() | |
self.device = device | |
if focal is None: | |
focal = np.tan(fovy / 180.0 * np.pi * 0.5) | |
self.proj_mtx = torch.from_numpy(projection(x=focal, f=1000.0, n=1.0, near_plane=0.1)).to(self.device).unsqueeze(dim=0) | |
def project(self, points_bxnx4): | |
out = torch.matmul( | |
points_bxnx4, | |
torch.transpose(self.proj_mtx, 1, 2)) | |
return out | |