# -*- 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