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Running
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T4
File size: 2,533 Bytes
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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 |