|
import argparse |
|
|
|
|
|
def parse_args(): |
|
parser = argparse.ArgumentParser() |
|
parser.add_argument('-net', type=str, default='sam', help='net type') |
|
parser.add_argument('-baseline', type=str, default='unet', help='baseline net type') |
|
parser.add_argument('-encoder', type=str, default='default', help='encoder type') |
|
parser.add_argument('-seg_net', type=str, default='transunet', help='net type') |
|
parser.add_argument('-mod', type=str, default='sam_adpt', help='mod type:seg,cls,val_ad') |
|
parser.add_argument('-exp_name', default='msa_test_isic', type=str, help='net type') |
|
parser.add_argument('-type', type=str, default='map', help='condition type:ave,rand,rand_map') |
|
parser.add_argument('-vis', type=int, default=None, help='visualization') |
|
parser.add_argument('-reverse', type=bool, default=False, help='adversary reverse') |
|
parser.add_argument('-pretrain', type=bool, default=False, help='adversary reverse') |
|
parser.add_argument('-val_freq',type=int,default=5,help='interval between each validation') |
|
parser.add_argument('-gpu', type=bool, default=True, help='use gpu or not') |
|
parser.add_argument('-gpu_device', type=int, default=0, help='use which gpu') |
|
parser.add_argument('-sim_gpu', type=int, default=0, help='split sim to this gpu') |
|
parser.add_argument('-epoch_ini', type=int, default=1, help='start epoch') |
|
parser.add_argument('-image_size', type=int, default=256, help='image_size') |
|
parser.add_argument('-out_size', type=int, default=256, help='output_size') |
|
parser.add_argument('-patch_size', type=int, default=2, help='patch_size') |
|
parser.add_argument('-dim', type=int, default=512, help='dim_size') |
|
parser.add_argument('-depth', type=int, default=1, help='depth') |
|
parser.add_argument('-heads', type=int, default=16, help='heads number') |
|
parser.add_argument('-mlp_dim', type=int, default=1024, help='mlp_dim') |
|
parser.add_argument('-w', type=int, default=4, help='number of workers for dataloader') |
|
parser.add_argument('-b', type=int, default=2, help='batch size for dataloader') |
|
parser.add_argument('-s', type=bool, default=True, help='whether shuffle the dataset') |
|
parser.add_argument('-warm', type=int, default=1, help='warm up training phase') |
|
parser.add_argument('-lr', type=float, default=1e-4, help='initial learning rate') |
|
parser.add_argument('-uinch', type=int, default=1, help='input channel of unet') |
|
parser.add_argument('-imp_lr', type=float, default=3e-4, help='implicit learning rate') |
|
parser.add_argument('-weights', type=str, default = 0, help='the weights file you want to test') |
|
parser.add_argument('-base_weights', type=str, default = 0, help='the weights baseline') |
|
parser.add_argument('-sim_weights', type=str, default = 0, help='the weights sim') |
|
parser.add_argument('-distributed', default='none' ,type=str,help='multi GPU ids to use') |
|
parser.add_argument('-dataset', default='isic' ,type=str,help='dataset name') |
|
parser.add_argument('-sam_ckpt', default=None , help='sam checkpoint address') |
|
parser.add_argument('-thd', type=bool, default=False , help='3d or not') |
|
parser.add_argument('-chunk', type=int, default=None , help='crop volume depth') |
|
parser.add_argument('-num_sample', type=int, default=4 , help='sample pos and neg') |
|
parser.add_argument('-roi_size', type=int, default=96 , help='resolution of roi') |
|
parser.add_argument('-evl_chunk', type=int, default=None , help='evaluation chunk') |
|
parser.add_argument('-mid_dim', type=int, default=None , help='middle dim of adapter or the rank of lora matrix') |
|
parser.add_argument('-multimask_output', type=int, default=1 , help='the number of masks output for multi-class segmentation, set 2 for REFUGE dataset.') |
|
parser.add_argument( |
|
'-data_path', |
|
type=str, |
|
default='../data', |
|
help='The path of segmentation data') |
|
|
|
|
|
opt = parser.parse_args() |
|
|
|
return opt |
|
|
|
|
