def __init__(self, opt, is_for_train):
super(FashionPairDataset, self).__init__(opt, is_for_train)
self._name = 'FashionPairDataset'
self.use_src_bg = False
self.bg_ks = 21
self.ft_ks = 7
# read dataset
self._read_dataset_paths()
# prepare mapping function
self.map_fn = mesh.create_mapping(map_name=opt.map_name,
mapping_path=opt.uv_mapping,
contain_bg=True,
fill_back=False)
# prepare head mapping function
self.head_fn = mesh.create_mapping(
'head',
head_info='assets/pretrains/head.json',
contain_bg=True,
fill_back=False)
self.bg_kernel = torch.ones(1,
1,
self.bg_ks,
self.bg_ks,
dtype=torch.float32)
self.ft_kernel = torch.ones(1,
1,
self.ft_ks,
self.ft_ks,
dtype=torch.float32)
def __init__(self, opt):
super(Swapper, self).__init__(opt)
self._name = 'Swapper'
self._create_networks()
# prefetch variables
self.src_info = None
self.tsf_info = None
self.T = None
self.T12 = None
self.T21 = None
self.grid = self.render.create_meshgrid(self._opt.image_size).cuda()
self.part_fn = torch.tensor(mesh.create_mapping('par', self._opt.uv_mapping,
contain_bg=True, fill_back=False)).float().cuda()
self.part_faces_dict = mesh.get_part_face_ids(part_type='par', fill_back=False)
self.part_faces = list(self.part_faces_dict.values())