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# -*- coding: utf-8 -*-
#
# Max-Planck-Gesellschaft zur Förderung der Wissenschaften e.V. (MPG) is
# holder of all proprietary rights on this computer program.
# Using this computer program means that you agree to the terms
# in the LICENSE file included with this software distribution.
# Any use not explicitly granted by the LICENSE is prohibited.
#
# Copyright©2019 Max-Planck-Gesellschaft zur Förderung
# der Wissenschaften e.V. (MPG). acting on behalf of its Max Planck Institute
# for Intelligent Systems. All rights reserved.
#
# For comments or questions, please email us at [email protected]
# For commercial licensing contact, please contact [email protected]
import pickle
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
class FLAMETex(nn.Module):
"""
FLAME texture:
https://github.com/TimoBolkart/TF_FLAME/blob/ade0ab152300ec5f0e8555d6765411555c5ed43d/sample_texture.py#L64
FLAME texture converted from BFM:
https://github.com/TimoBolkart/BFM_to_FLAME
"""
def __init__(self, config):
super(FLAMETex, self).__init__()
if config.tex_type == "BFM":
mu_key = "MU"
pc_key = "PC"
n_pc = 199
tex_path = config.tex_path
tex_space = np.load(tex_path)
texture_mean = tex_space[mu_key].reshape(1, -1)
texture_basis = tex_space[pc_key].reshape(-1, n_pc)
elif config.tex_type == "FLAME":
mu_key = "mean"
pc_key = "tex_dir"
n_pc = 200
tex_path = config.flame_tex_path
tex_space = np.load(tex_path)
texture_mean = tex_space[mu_key].reshape(1, -1) / 255.0
texture_basis = tex_space[pc_key].reshape(-1, n_pc) / 255.0
else:
print("texture type ", config.tex_type, "not exist!")
raise NotImplementedError
n_tex = config.n_tex
num_components = texture_basis.shape[1]
texture_mean = torch.from_numpy(texture_mean).float()[None, ...]
texture_basis = torch.from_numpy(texture_basis[:, :n_tex]).float()[None, ...]
self.register_buffer("texture_mean", texture_mean)
self.register_buffer("texture_basis", texture_basis)
def forward(self, texcode=None):
"""
texcode: [batchsize, n_tex]
texture: [bz, 3, 256, 256], range: 0-1
"""
texture = self.texture_mean + (self.texture_basis * texcode[:, None, :]).sum(-1)
texture = texture.reshape(texcode.shape[0], 512, 512, 3).permute(0, 3, 1, 2)
texture = F.interpolate(texture, [256, 256])
texture = texture[:, [2, 1, 0], :, :]
return texture
def texture_flame2smplx(cached_data, flame_texture, smplx_texture):
"""Convert flame texture map (face-only) into smplx texture map (includes body texture)
TODO: pytorch version ==> grid sample
"""
if smplx_texture.shape[0] != smplx_texture.shape[1]:
print("SMPL-X texture not squared (%d != %d)" % (smplx_texture[0], smplx_texture[1]))
return
if smplx_texture.shape[0] != cached_data["target_resolution"]:
print(
"SMPL-X texture size does not match cached image resolution (%d != %d)" %
(smplx_texture.shape[0], cached_data["target_resolution"])
)
return
x_coords = cached_data["x_coords"]
y_coords = cached_data["y_coords"]
target_pixel_ids = cached_data["target_pixel_ids"]
source_uv_points = cached_data["source_uv_points"]
source_tex_coords = np.zeros_like((source_uv_points)).astype(int)
source_tex_coords[:, 0] = np.clip(
flame_texture.shape[0] * (1.0 - source_uv_points[:, 1]),
0.0,
flame_texture.shape[0],
).astype(int)
source_tex_coords[:, 1] = np.clip(
flame_texture.shape[1] * (source_uv_points[:, 0]), 0.0, flame_texture.shape[1]
).astype(int)
smplx_texture[y_coords[target_pixel_ids].astype(int),
x_coords[target_pixel_ids].astype(int), :, ] = flame_texture[source_tex_coords[:,
0],
source_tex_coords[:,
1]]
return smplx_texture
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