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opt.py
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opt.py
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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='',
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("--device", type=int, default=0,
help='which gpu to use')
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='SMURF')
# loader options
parser.add_argument("--batch_size", type=int, default=4096)
parser.add_argument("--n_iters", type=int, default=40000)
parser.add_argument("--blur_start", type=int, default=500,
help='start iteration to blur the data')
parser.add_argument("--rm_near_plane", type=int, default=0,
help='remove near plane in ray marching')
parser.add_argument("--hold_every", type=int, default=8)
parser.add_argument("--height", type=int, default=400)
parser.add_argument("--width", type=int, default=600)
parser.add_argument('--dataset_name', type=str, default='llff',
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=1.0,
help='loss weight')
parser.add_argument("--TV_weight_app", type=float, default=1.0,
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_Fea",
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=0,
help='number of pe for view')
parser.add_argument("--fea_pe", type=int, default=0,
help='number of pe for features')
parser.add_argument("--featureC", type=int, default=128,
help='hidden feature channel in MLP')
# Kernel Options
parser.add_argument("--num_warp", type=int, default=8)
parser.add_argument("--img_embed", type=int, default=32)
parser.add_argument("--spatial_embed_freq", type=int, default=2)
parser.add_argument("--embed_dim", type=int, default=64)
parser.add_argument("--method", type=str, default="euler")
parser.add_argument("--chrono_view_embed_dim", type=int, default=16)
parser.add_argument("--adjoint", type=bool, default=False)
parser.add_argument("--point_float", type=bool, default=False)
parser.add_argument("--chrono_view", type=bool, default=True)
parser.add_argument("--res_momentum", type=bool, default=True)
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("--render_all", 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=2.0)
parser.add_argument('--focuspoint_scale', type=float, default=1.0)
parser.add_argument('--radius_scale', type=float, default=1.0)
parser.add_argument("--tonemapping", type=str, default='gamma', choices=['none', 'gamma', 'learn'])
## 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=128**3)
parser.add_argument('--N_voxel_final',
type=int,
default=480**3)
parser.add_argument("--upsamp_list", type=int, action="append")
parser.add_argument("--update_AlphaMask_list", type=int, action="append")
# logging/saving options
parser.add_argument("--N_vis", type=int, default=-1,
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()