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name: ${basename:${dataset.scene}} | |
tag: "" | |
seed: 42 | |
dataset: | |
name: ortho | |
root_dir: /home/xiaoxiao/Workplace/wonder3Dplus/outputs/joint-twice/aigc/cropsize-224-cfg1.0 | |
cam_pose_dir: null | |
scene: scene_name | |
imSize: [1024, 1024] # should use larger res, otherwise the exported mesh has wrong colors | |
camera_type: ortho | |
apply_mask: true | |
camera_params: null | |
view_weights: [1.0, 0.8, 0.2, 1.0, 0.4, 0.7] #['front', 'front_right', 'right', 'back', 'left', 'front_left'] | |
# view_weights: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0] | |
model: | |
name: neus | |
radius: 1.0 | |
num_samples_per_ray: 1024 | |
train_num_rays: 256 | |
max_train_num_rays: 8192 | |
grid_prune: true | |
grid_prune_occ_thre: 0.001 | |
dynamic_ray_sampling: true | |
batch_image_sampling: true | |
randomized: true | |
ray_chunk: 2048 | |
cos_anneal_end: 20000 | |
learned_background: false | |
background_color: black | |
variance: | |
init_val: 0.3 | |
modulate: false | |
geometry: | |
name: volume-sdf | |
radius: ${model.radius} | |
feature_dim: 13 | |
grad_type: finite_difference | |
finite_difference_eps: progressive | |
isosurface: | |
method: mc | |
resolution: 192 | |
chunk: 2097152 | |
threshold: 0. | |
xyz_encoding_config: | |
otype: ProgressiveBandHashGrid | |
n_levels: 10 # 12 modify | |
n_features_per_level: 2 | |
log2_hashmap_size: 19 | |
base_resolution: 32 | |
per_level_scale: 1.3195079107728942 | |
include_xyz: true | |
start_level: 4 | |
start_step: 0 | |
update_steps: 1000 | |
mlp_network_config: | |
otype: VanillaMLP | |
activation: ReLU | |
output_activation: none | |
n_neurons: 64 | |
n_hidden_layers: 1 | |
sphere_init: true | |
sphere_init_radius: 0.5 | |
weight_norm: true | |
texture: | |
name: volume-radiance | |
input_feature_dim: ${add:${model.geometry.feature_dim},3} # surface normal as additional input | |
dir_encoding_config: | |
otype: SphericalHarmonics | |
degree: 4 | |
mlp_network_config: | |
otype: VanillaMLP | |
activation: ReLU | |
output_activation: none | |
n_neurons: 64 | |
n_hidden_layers: 2 | |
color_activation: sigmoid | |
system: | |
name: ortho-neus-system | |
loss: | |
lambda_rgb_mse: 0.5 | |
lambda_rgb_l1: 0. | |
lambda_mask: 1.0 | |
lambda_eikonal: 0.2 # cannot be too large, will cause holes to thin objects | |
lambda_normal: 1.0 # cannot be too large | |
lambda_3d_normal_smooth: 1.0 | |
# lambda_curvature: [0, 0.0, 1.e-4, 1000] # topology warmup | |
lambda_curvature: 0. | |
lambda_sparsity: 0.5 | |
lambda_distortion: 0.0 | |
lambda_distortion_bg: 0.0 | |
lambda_opaque: 0.0 | |
sparsity_scale: 100.0 | |
geo_aware: true | |
rgb_p_ratio: 0.8 | |
normal_p_ratio: 0.8 | |
mask_p_ratio: 0.9 | |
optimizer: | |
name: AdamW | |
args: | |
lr: 0.01 | |
betas: [0.9, 0.99] | |
eps: 1.e-15 | |
params: | |
geometry: | |
lr: 0.001 | |
texture: | |
lr: 0.01 | |
variance: | |
lr: 0.001 | |
constant_steps: 500 | |
scheduler: | |
name: SequentialLR | |
interval: step | |
milestones: | |
- ${system.constant_steps} | |
schedulers: | |
- name: ConstantLR | |
args: | |
factor: 1.0 | |
total_iters: ${system.constant_steps} | |
- name: ExponentialLR | |
args: | |
gamma: ${calc_exp_lr_decay_rate:0.1,${sub:${trainer.max_steps},${system.constant_steps}}} | |
checkpoint: | |
save_top_k: -1 | |
every_n_train_steps: ${trainer.max_steps} | |
export: | |
chunk_size: 2097152 | |
export_vertex_color: True | |
ortho_scale: 1.35 #modify | |
trainer: | |
max_steps: 3000 | |
log_every_n_steps: 100 | |
num_sanity_val_steps: 0 | |
val_check_interval: 4000 | |
limit_train_batches: 1.0 | |
limit_val_batches: 2 | |
enable_progress_bar: true | |
precision: 16 | |