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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 pixie@tue.mpg.de
# For commercial licensing contact, please contact ps-license@tuebingen.mpg.de
import torch
import torch.nn as nn
import numpy as np
import pickle
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.
texture_basis = tex_space[pc_key].reshape(-1, n_pc) / 255.
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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