mdm / data_loaders /humanml /utils /get_opt.py
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from argparse import Namespace
import re
from os.path import join as pjoin
from data_loaders.humanml.utils.word_vectorizer import POS_enumerator
def is_float(numStr):
flag = False
numStr = str(numStr).strip().lstrip("-").lstrip("+") # 去除正数(+)、负数(-)符号
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("+") # 去除正数(+)、负数(-)符号
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] = bool(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"] = "latest"
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
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
else:
raise KeyError("Dataset not recognized")
opt.dim_word = 300
opt.num_classes = 200 // opt.unit_length
opt.dim_pos_ohot = len(POS_enumerator)
opt.is_train = False
opt.is_continue = False
opt.device = device
return opt