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# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
# 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 marcher takes the raw output of the implicit representation and uses the volume rendering equation to produce composited colors and depths.
Based off of the implementation in MipNeRF (this one doesn't do any cone tracing though!)
"""
import torch
import torch.nn as nn
class MipRayMarcher2(nn.Module):
def __init__(self, activation_factory):
super().__init__()
self.activation_factory = activation_factory
def run_forward(self, colors, densities, depths, rendering_options):
deltas = depths[:, :, 1:] - depths[:, :, :-1]
colors_mid = (colors[:, :, :-1] + colors[:, :, 1:]) / 2
densities_mid = (densities[:, :, :-1] + densities[:, :, 1:]) / 2
depths_mid = (depths[:, :, :-1] + depths[:, :, 1:]) / 2
# using factory mode for better usability
densities_mid = self.activation_factory(rendering_options)(densities_mid)
density_delta = densities_mid * deltas
alpha = 1 - torch.exp(-density_delta)
alpha_shifted = torch.cat([torch.ones_like(alpha[:, :, :1]), 1-alpha + 1e-10], -2)
weights = alpha * torch.cumprod(alpha_shifted, -2)[:, :, :-1]
composite_rgb = torch.sum(weights * colors_mid, -2)
weight_total = weights.sum(2)
composite_depth = torch.sum(weights * depths_mid, -2) / weight_total
# clip the composite to min/max range of depths
composite_depth = torch.nan_to_num(composite_depth, float('inf'))
composite_depth = torch.clamp(composite_depth, torch.min(depths), torch.max(depths))
if rendering_options.get('white_back', False):
composite_rgb = composite_rgb + 1 - weight_total
# rendered value scale is 0-1, comment out original mipnerf scaling
# composite_rgb = composite_rgb * 2 - 1 # Scale to (-1, 1)
return composite_rgb, composite_depth, weights
def forward(self, colors, densities, depths, rendering_options):
composite_rgb, composite_depth, weights = self.run_forward(colors, densities, depths, rendering_options)
return composite_rgb, composite_depth, weights |