| general { | |
| base_exp_dir = ./exp/neus/CASE_NAME/ | |
| recording = [ | |
| ./, | |
| ./models | |
| ] | |
| } | |
| 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 | |
| } | |
| train { | |
| learning_rate = 5e-4 | |
| learning_rate_alpha = 0.05 | |
| end_iter = 1000 # longer time, better result. 1w will be ok for most cases | |
| batch_size = 512 | |
| validate_resolution_level = 1 | |
| warm_up_end = 500 | |
| anneal_end = 0 | |
| use_white_bkgd = True | |
| save_freq = 5000 | |
| val_freq = 5000 | |
| val_mesh_freq =5000 | |
| report_freq = 100 | |
| color_weight = 1.0 | |
| igr_weight = 0.1 | |
| mask_weight = 1.0 | |
| normal_weight = 1.0 | |
| sparse_weight = 0.1 | |
| } | |
| 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 | |
| } | |
| 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 | |
| } | |
| variance_network { | |
| init_val = 0.3 | |
| } | |
| 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 | |
| } | |
| 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 | |
| } | |
| } | |