| 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 |
