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general { | ||
base_exp_dir = ./exp/neus/CASE_NAME/ | ||
recording = [ | ||
./, | ||
./models | ||
] | ||
} | ||
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dataset { | ||
data_dir = ./outputs/ | ||
object_name = CASE_NAME | ||
object_viewidx = 1 | ||
imSize = [256, 256] | ||
load_color = True | ||
stage = coarse | ||
mtype = mlp | ||
normal_system: front | ||
num_views = 6 | ||
} | ||
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train { | ||
learning_rate = 5e-4 | ||
learning_rate_alpha = 0.05 | ||
end_iter = 1000 # longer time, better result. 1w will be ok for most cases | ||
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batch_size = 512 | ||
validate_resolution_level = 1 | ||
warm_up_end = 500 | ||
anneal_end = 0 | ||
use_white_bkgd = True | ||
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save_freq = 5000 | ||
val_freq = 5000 | ||
val_mesh_freq =5000 | ||
report_freq = 100 | ||
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color_weight = 1.0 | ||
igr_weight = 0.1 | ||
mask_weight = 1.0 | ||
normal_weight = 1.0 | ||
sparse_weight = 0.1 | ||
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} | ||
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model { | ||
nerf { | ||
D = 8, | ||
d_in = 4, | ||
d_in_view = 3, | ||
W = 256, | ||
multires = 10, | ||
multires_view = 4, | ||
output_ch = 4, | ||
skips=[4], | ||
use_viewdirs=True | ||
} | ||
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sdf_network { | ||
d_out = 257 | ||
d_in = 3 | ||
d_hidden = 256 | ||
n_layers = 8 | ||
skip_in = [4] | ||
multires = 6 | ||
bias = 0.5 | ||
scale = 1.0 | ||
geometric_init = True | ||
weight_norm = True | ||
} | ||
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variance_network { | ||
init_val = 0.3 | ||
} | ||
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rendering_network { | ||
d_feature = 256 | ||
mode = no_view_dir | ||
d_in = 6 | ||
d_out = 3 | ||
d_hidden = 256 | ||
n_layers = 4 | ||
weight_norm = True | ||
multires_view = 0 | ||
squeeze_out = True | ||
} | ||
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neus_renderer { | ||
n_samples = 64 | ||
n_importance = 64 | ||
n_outside = 0 | ||
up_sample_steps = 4 # 1 for simple coarse-to-fine sampling | ||
perturb = 1.0 | ||
sdf_decay_param = 100 | ||
} | ||
} |
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