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())