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# Open Source Model Licensed under the Apache License Version 2.0 | |
# and Other Licenses of the Third-Party Components therein: | |
# The below Model in this distribution may have been modified by THL A29 Limited | |
# ("Tencent Modifications"). All Tencent Modifications are Copyright (C) 2024 THL A29 Limited. | |
# Copyright (C) 2024 THL A29 Limited, a Tencent company. All rights reserved. | |
# The below software and/or models in this distribution may have been | |
# modified by THL A29 Limited ("Tencent Modifications"). | |
# All Tencent Modifications are Copyright (C) THL A29 Limited. | |
# Hunyuan 3D is licensed under the TENCENT HUNYUAN NON-COMMERCIAL LICENSE AGREEMENT | |
# except for the third-party components listed below. | |
# Hunyuan 3D does not impose any additional limitations beyond what is outlined | |
# in the repsective licenses of these third-party components. | |
# Users must comply with all terms and conditions of original licenses of these third-party | |
# components and must ensure that the usage of the third party components adheres to | |
# all relevant laws and regulations. | |
# For avoidance of doubts, Hunyuan 3D means the large language models and | |
# their software and algorithms, including trained model weights, parameters (including | |
# optimizer states), machine-learning model code, inference-enabling code, training-enabling code, | |
# fine-tuning enabling code and other elements of the foregoing made publicly available | |
# by Tencent in accordance with TENCENT HUNYUAN COMMUNITY LICENSE AGREEMENT. | |
import custom_rasterizer_kernel | |
import torch | |
def rasterize(pos, tri, resolution, clamp_depth=torch.zeros(0), use_depth_prior=0): | |
assert (pos.device == tri.device) | |
findices, barycentric = custom_rasterizer_kernel.rasterize_image(pos[0], tri, clamp_depth, resolution[1], | |
resolution[0], 1e-6, use_depth_prior) | |
return findices, barycentric | |
def interpolate(col, findices, barycentric, tri): | |
f = findices - 1 + (findices == 0) | |
vcol = col[0, tri.long()[f.long()]] | |
result = barycentric.view(*barycentric.shape, 1) * vcol | |
result = torch.sum(result, axis=-2) | |
return result.view(1, *result.shape) | |