forked from apchenstu/TensoRF
-
Notifications
You must be signed in to change notification settings - Fork 0
/
opt.py
134 lines (113 loc) · 6.34 KB
/
opt.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
import configargparse
def config_parser(cmd=None):
parser = configargparse.ArgumentParser()
parser.add_argument('--config', is_config_file=True,
help='config file path')
parser.add_argument("--expname", type=str,
help='experiment name')
parser.add_argument("--basedir", type=str, default='./log',
help='where to store ckpts and logs')
parser.add_argument("--add_timestamp", type=int, default=0,
help='add timestamp to dir')
parser.add_argument("--datadir", type=str, default='./data/llff/fern',
help='input data directory')
parser.add_argument("--progress_refresh_rate", type=int, default=10,
help='how many iterations to show psnrs or iters')
parser.add_argument('--with_depth', action='store_true')
parser.add_argument('--downsample_train', type=float, default=1.0)
parser.add_argument('--downsample_test', type=float, default=1.0)
parser.add_argument('--model_name', type=str, default='TensorVMSplit',
choices=['TensorVMSplit', 'TensorCP'])
# loader options
parser.add_argument("--batch_size", type=int, default=4096)
parser.add_argument("--n_iters", type=int, default=30000)
parser.add_argument('--dataset_name', type=str, default='blender',
choices=['blender', 'llff', 'nsvf', 'dtu','tankstemple', 'own_data'])
# training options
# learning rate
parser.add_argument("--lr_init", type=float, default=0.02,
help='learning rate')
parser.add_argument("--lr_basis", type=float, default=1e-3,
help='learning rate')
parser.add_argument("--lr_decay_iters", type=int, default=-1,
help = 'number of iterations the lr will decay to the target ratio; -1 will set it to n_iters')
parser.add_argument("--lr_decay_target_ratio", type=float, default=0.1,
help='the target decay ratio; after decay_iters inital lr decays to lr*ratio')
parser.add_argument("--lr_upsample_reset", type=int, default=1,
help='reset lr to inital after upsampling')
# loss
parser.add_argument("--L1_weight_inital", type=float, default=0.0,
help='loss weight')
parser.add_argument("--L1_weight_rest", type=float, default=0,
help='loss weight')
parser.add_argument("--Ortho_weight", type=float, default=0.0,
help='loss weight')
parser.add_argument("--TV_weight_density", type=float, default=0.0,
help='loss weight')
parser.add_argument("--TV_weight_app", type=float, default=0.0,
help='loss weight')
# model
# volume options
parser.add_argument("--n_lamb_sigma", type=int, action="append")
parser.add_argument("--n_lamb_sh", type=int, action="append")
parser.add_argument("--data_dim_color", type=int, default=27)
parser.add_argument("--rm_weight_mask_thre", type=float, default=0.0001,
help='mask points in ray marching')
parser.add_argument("--alpha_mask_thre", type=float, default=0.0001,
help='threshold for creating alpha mask volume')
parser.add_argument("--distance_scale", type=float, default=25,
help='scaling sampling distance for computation')
parser.add_argument("--density_shift", type=float, default=-10,
help='shift density in softplus; making density = 0 when feature == 0')
# network decoder
parser.add_argument("--shadingMode", type=str, default="MLP_PE",
help='which shading mode to use')
parser.add_argument("--pos_pe", type=int, default=6,
help='number of pe for pos')
parser.add_argument("--view_pe", type=int, default=6,
help='number of pe for view')
parser.add_argument("--fea_pe", type=int, default=6,
help='number of pe for features')
parser.add_argument("--featureC", type=int, default=128,
help='hidden feature channel in MLP')
parser.add_argument("--ckpt", type=str, default=None,
help='specific weights npy file to reload for coarse network')
parser.add_argument("--render_only", type=int, default=0)
parser.add_argument("--render_test", type=int, default=0)
parser.add_argument("--render_train", type=int, default=0)
parser.add_argument("--render_path", type=int, default=0)
parser.add_argument("--export_mesh", type=int, default=0)
# rendering options
parser.add_argument('--lindisp', default=False, action="store_true",
help='use disparity depth sampling')
parser.add_argument("--perturb", type=float, default=1.,
help='set to 0. for no jitter, 1. for jitter')
parser.add_argument("--accumulate_decay", type=float, default=0.998)
parser.add_argument("--fea2denseAct", type=str, default='softplus')
parser.add_argument('--ndc_ray', type=int, default=0)
parser.add_argument('--nSamples', type=int, default=1e6,
help='sample point each ray, pass 1e6 if automatic adjust')
parser.add_argument('--step_ratio',type=float,default=0.5)
## blender flags
parser.add_argument("--white_bkgd", action='store_true',
help='set to render synthetic data on a white bkgd (always use for dvoxels)')
parser.add_argument('--N_voxel_init',
type=int,
default=100**3)
parser.add_argument('--N_voxel_final',
type=int,
default=300**3)
parser.add_argument("--upsamp_list", type=int, action="append")
parser.add_argument("--update_AlphaMask_list", type=int, action="append")
parser.add_argument('--idx_view',
type=int,
default=0)
# logging/saving options
parser.add_argument("--N_vis", type=int, default=5,
help='N images to vis')
parser.add_argument("--vis_every", type=int, default=10000,
help='frequency of visualize the image')
if cmd is not None:
return parser.parse_args(cmd)
else:
return parser.parse_args()