# SPDX-FileCopyrightText: Copyright (c) 2021-2022 NVIDIA CORPORATION & AFFILIATES. All rights reserved. # SPDX-License-Identifier: LicenseRef-NvidiaProprietary # # NVIDIA CORPORATION, its affiliates and licensors retain all intellectual # property and proprietary rights in and to this material, related # documentation and any modifications thereto. Any use, reproduction, # disclosure or distribution of this material and related documentation # without an express license agreement from NVIDIA CORPORATION or # its affiliates is strictly prohibited. # # Modified by Zexin He # The modifications are subject to the same license as the original. """ The ray sampler is a module that takes in camera matrices and resolution and batches of rays. Expects cam2world matrices that use the OpenCV camera coordinate system conventions. """ import torch class RaySampler(torch.nn.Module): def __init__(self): super().__init__() self.ray_origins_h, self.ray_directions, self.depths, self.image_coords, self.rendering_options = None, None, None, None, None def forward(self, cam2world_matrix, intrinsics, render_size): """ Create batches of rays and return origins and directions. cam2world_matrix: (N, 4, 4) intrinsics: (N, 3, 3) render_size: int ray_origins: (N, M, 3) ray_dirs: (N, M, 2) """ N, M = cam2world_matrix.shape[0], render_size**2 cam_locs_world = cam2world_matrix[:, :3, 3] fx = intrinsics[:, 0, 0] fy = intrinsics[:, 1, 1] cx = intrinsics[:, 0, 2] cy = intrinsics[:, 1, 2] sk = intrinsics[:, 0, 1] uv = torch.stack(torch.meshgrid( torch.arange(render_size, dtype=torch.float32, device=cam2world_matrix.device), torch.arange(render_size, dtype=torch.float32, device=cam2world_matrix.device), indexing='ij', )) uv = uv.flip(0).reshape(2, -1).transpose(1, 0) uv = uv.unsqueeze(0).repeat(cam2world_matrix.shape[0], 1, 1) x_cam = uv[:, :, 0].view(N, -1) * (1./render_size) + (0.5/render_size) y_cam = uv[:, :, 1].view(N, -1) * (1./render_size) + (0.5/render_size) z_cam = torch.ones((N, M), device=cam2world_matrix.device) x_lift = (x_cam - cx.unsqueeze(-1) + cy.unsqueeze(-1)*sk.unsqueeze(-1)/fy.unsqueeze(-1) - sk.unsqueeze(-1)*y_cam/fy.unsqueeze(-1)) / fx.unsqueeze(-1) * z_cam y_lift = (y_cam - cy.unsqueeze(-1)) / fy.unsqueeze(-1) * z_cam cam_rel_points = torch.stack((x_lift, y_lift, z_cam, torch.ones_like(z_cam)), dim=-1) _opencv2blender = torch.tensor([ [1, 0, 0, 0], [0, -1, 0, 0], [0, 0, -1, 0], [0, 0, 0, 1], ], dtype=torch.float32, device=cam2world_matrix.device).unsqueeze(0).repeat(N, 1, 1) cam2world_matrix = torch.bmm(cam2world_matrix, _opencv2blender) world_rel_points = torch.bmm(cam2world_matrix, cam_rel_points.permute(0, 2, 1)).permute(0, 2, 1)[:, :, :3] ray_dirs = world_rel_points - cam_locs_world[:, None, :] ray_dirs = torch.nn.functional.normalize(ray_dirs, dim=2) ray_origins = cam_locs_world.unsqueeze(1).repeat(1, ray_dirs.shape[1], 1) return ray_origins, ray_dirs