| 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:
|
|
|
| key, value = line.strip().split(': ')
|
| if value in ('True', 'False'):
|
| opt_dict[key] = (value == 'True')
|
|
|
| elif is_float(value):
|
| opt_dict[key] = float(value)
|
| elif is_number(value):
|
| opt_dict[key] = int(value)
|
| else:
|
| opt_dict[key] = str(value)
|
|
|
|
|
| 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 |
