示例#1
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 def __getitem__(self, index):
     path = self.paths[index]
     mesh = Mesh(file=path,
                 opt=self.opt,
                 hold_history=True,
                 export_folder=self.opt.export_folder)
     meta = {}
     meta['mesh'] = mesh
     if self.opt.edge_split:
         path_index = os.path.join(
             os.path.dirname(self.seg_paths[index]),
             'cache\\' + os.path.basename(self.seg_paths[index]))
         label = read_seg(path_index) - self.offset
     else:
         label = read_seg(self.seg_paths[index]) - self.offset
     label = pad(label, self.opt.ninput_edges, val=-1, dim=0)
     meta['label'] = label
     if self.opt.edge_split:
         path_index = os.path.join(
             os.path.dirname(self.sseg_paths[index]),
             'cache\\' + os.path.basename(self.sseg_paths[index]))
         soft_label = read_sseg(path_index)
     else:
         soft_label = read_sseg(self.sseg_paths[index])
     meta['soft_label'] = pad(soft_label,
                              self.opt.ninput_edges,
                              val=-1,
                              dim=0)
     # get edge features
     edge_features = mesh.extract_features()
     edge_features = pad(edge_features, self.opt.ninput_edges)
     meta['edge_features'] = (edge_features - self.mean) / self.std
     return meta
示例#2
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 def __getitem__(self, index):
     path = self.paths[index]
     mesh = Mesh(file=path, opt=self.opt, hold_history=True, export_folder=self.opt.export_folder)
     meta = {}
     meta['mesh'] = mesh
     label = read_seg(self.seg_paths[index]) - self.offset
     label = pad(label, self.opt.ninput_edges, val=-1, dim=0)
     meta['label'] = label
     soft_label = read_sseg(self.sseg_paths[index])
     meta['soft_label'] = pad(soft_label, self.opt.ninput_edges, val=-1, dim=0)
     # get edge features
     edge_features = mesh.extract_features()
     edge_features = pad(edge_features, self.opt.ninput_edges)
     meta['edge_features'] = (edge_features - self.mean) / self.std
     return meta
示例#3
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 def __getitem__(self, index):
     path = self.paths[index][0]
     label = self.paths[index][1]
     mesh = Mesh(file=path, opt=self.opt, hold_history=False, export_folder=self.opt.export_folder)
     meta = {'mesh': mesh, 'label': label}
     # get edge features
     face_features = mesh.extract_features()
     face_features = pad(face_features, self.opt.ninput_faces)
     meta['face_features'] = (face_features - self.mean) / self.std
     return meta
 def __getitem__(self, index):
     path = self.paths[index]
     mesh = Mesh(file=path, opt=self.opt, hold_history=True, export_folder=self.opt.export_folder)
     meta = {}
     meta['mesh'] = mesh
     # get edge features
     face_features = mesh.extract_features()
     meta['num_triangle'] = mesh.faces_count
     face_features = pad(face_features, self.opt.ninput_faces)
     meta['face_features'] = (face_features - self.mean) / self.std
     return meta
示例#5
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 def __getitem__(self, index):
     path = self.paths[index]
     mesh = Mesh(file=path,
                 opt=self.opt,
                 hold_history=True,
                 export_folder=self.opt.export_folder)
     # get edge features
     edge_features = mesh.extract_features()
     edge_features = pad(edge_features, self.opt.ninput_edges)
     meta = {'mesh': mesh, 'label': edge_features}
     meta['edge_features'] = (edge_features - self.mean) / self.std
     return meta
示例#6
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    def __getitem__(self, index):
        path = self.paths[index]
        # print("opt: {}, export_folder: {}, phase: {}".format(self.opt, self.opt.export_folder,  self.opt.phase))
        mesh = Mesh(file=path,
                    opt=self.opt,
                    hold_history=True,
                    export_folder=self.opt.export_folder,
                    phase=self.opt.phase)
        meta = {}
        meta["filename"] = mesh.filename
        meta['mesh'] = mesh
        if self.opt.phase != "test":
            label = read_seg(self.seg_paths[index]) - self.offset
            # print("label: ", label.shape, type(label), label)
            # if len(label) > self.opt.ninput_edges:
            #     label = label[mesh.e_masks]
            if len(label) <= self.opt.ninput_edges:
                label = pad(label, self.opt.ninput_edges, val=-1, dim=0)
            meta['label'] = label
            soft_label = read_sseg(self.sseg_paths[index])
            # if len(soft_label) > self.opt.ninput_edges:
            #     soft_label = soft_label[mesh.e_masks]
            if len(soft_label) <= self.opt.ninput_edges:
                soft_label = pad(soft_label,
                                 self.opt.ninput_edges,
                                 val=-1,
                                 dim=0)
            meta['soft_label'] = soft_label

            # get edge features
        edge_features = mesh.extract_features()
        if edge_features.shape[1] <= self.opt.ninput_edges:
            edge_features = pad(edge_features, self.opt.ninput_edges)
            meta['edge_features'] = (edge_features - self.mean) / self.std
        else:
            meta["edge_features"] = np.array([])

        # print("edge_features: ", type(meta["edge_features"]), meta["edge_features"].shape)

        return meta
示例#7
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 def __getitem__(self, index):
     path = self.paths[index][0]
     #print(path)
     mesh = Mesh(file=path,
                 opt=self.opt,
                 hold_history=True,
                 export_folder=self.opt.export_folder)
     meta = {}
     mesh.vs = (mesh.vs - np.mean(mesh.vs, 0)) / np.std(mesh.vs, 0)
     meta['mesh'] = mesh
     meta['export_folder'] = mesh.export_folder
     meta['filename'] = mesh.filename
     # get edge features
     edge_features = mesh.extract_features()
     edge_features = pad(edge_features, self.opt.ninput_edges)
     vs, pad_iter = pad_vertices(mesh.vs, 1402)
     meta['edge_features'] = (edge_features - self.mean) / self.std
     meta['label'] = vs.astype(np.float)
     meta['init_faces'] = mesh.init_faces
     meta['pad_iter'] = pad_iter
     return meta
示例#8
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 def get_random_profile_lines(self):
     profile_lines = util.tokenize_sentences(self.profile)    
     random.seed(keys.RANDOM_SEED + datetime.today().toordinal())    
     random_profile_lines = random.sample(util.pad(profile_lines, '', 3), 3)
     random_profile_lines = [util.shorten_if_long(l) for l in random_profile_lines]
     return random_profile_lines
示例#9
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 def __extract(meshes, nv, device):
     vs = [pad(mesh.vs, nv, dim=0) for mesh in meshes]
     vs = np.array(vs)
     vs = torch.from_numpy(vs).float().to(device)
     vs.requires_grad_()
     return vs