from argparse import Namespace import re from os.path import join as pjoin def is_float(numStr): flag = False numStr = str(numStr).strip().lstrip('-').lstrip('+') try: reg = re.compile(r'^[-+]?[0-9]+\.[0-9]+$') res = reg.match(str(numStr)) if res: flag = True except Exception as ex: print("is_float() - error: " + str(ex)) return flag def is_number(numStr): flag = False numStr = str(numStr).strip().lstrip('-').lstrip('+') if str(numStr).isdigit(): flag = True return flag def get_opt(opt_path, device): opt = Namespace() opt_dict = vars(opt) skip = ('-------------- End ----------------', '------------ Options -------------', '\n') print('Reading', opt_path) with open(opt_path) as f: for line in f: if line.strip() not in skip: # print(line.strip()) key, value = line.strip().split(': ') if value in ('True', 'False'): opt_dict[key] = (value == 'True') # print(key, value) elif is_float(value): opt_dict[key] = float(value) elif is_number(value): opt_dict[key] = int(value) else: opt_dict[key] = str(value) # print(opt) opt_dict['which_epoch'] = 'finest' opt.save_root = pjoin(opt.checkpoints_dir, opt.dataset_name, opt.name) opt.model_dir = pjoin(opt.save_root, 'model') opt.meta_dir = pjoin(opt.save_root, 'meta') if opt.dataset_name == 't2m': opt.data_root = './dataset/HumanML3D/' opt.motion_dir = pjoin(opt.data_root, 'new_joint_vecs') opt.text_dir = pjoin(opt.data_root, 'texts') opt.joints_num = 22 opt.dim_pose = 263 opt.max_motion_length = 196 opt.max_motion_frame = 196 opt.max_motion_token = 55 elif opt.dataset_name == 'kit': opt.data_root = './dataset/KIT-ML/' opt.motion_dir = pjoin(opt.data_root, 'new_joint_vecs') opt.text_dir = pjoin(opt.data_root, 'texts') opt.joints_num = 21 opt.dim_pose = 251 opt.max_motion_length = 196 opt.max_motion_frame = 196 opt.max_motion_token = 55 else: raise KeyError('Dataset not recognized') opt.dim_word = 300 opt.num_classes = 200 // opt.unit_length opt.is_train = False opt.is_continue = False opt.device = device return opt