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volsdf_nerfpp_blended.yaml
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volsdf_nerfpp_blended.yaml
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expname: volsdf_nerf++_blended_5c0d13
# device_ids: [0] # single gpu ; run on specified GPU
# device_ids: [1, 0] # DP ; run on specified GPU
device_ids: -1 # single GPU / DP / DDP; run on all available GPUs;
data:
type: BlendedMVS
batch_size: 1 # one batch, one image
data_dir: ./data/BlendedMVS/BlendedMVS/5c0d13b795da9479e12e2ee9
downscale: 1 # downscale image for training
scale_radius: 3.0 # scale the dataset's all camera to be within this radius
volume_size: 5.0 # volume size for extracing mesh using marching cube
pin_memory: True
near: 0.0
far: 6.0 # NOTE: in volSDF,far = 2r=2*3=6.0
N_rays: 1024 # N_rays for training
val_rayschunk: 256 # N_rays for validation
val_downscale: 4 # downscale image for validation
model:
framework: VolSDF
obj_bounding_radius: 3.0 # scene sphere, as in the VolSDF paper
outside_scene: "nerf++" # [builtin, nerf++]
max_upsample_iter: 5 # up sample iteratioms, as in the VolSDF paper
W_geometry_feature: 256
surface:
radius_init: 1.0 # as in VolSDF supp B.3, unit sphere
D: 8
skips: [4]
embed_multires: 6
radiance:
D: 4
skips: []
embed_multires: -1
embed_multires_view: -1
training:
speed_factor: 10.0
lr: 5.0e-4
w_eikonal: 0.1
log_root_dir: "logs"
# lr decay
scheduler:
type: warmupcosine
warmup_steps: 0 # unit: itertation steps
num_iters: 200000
ckpt_file: null # will be read by python as None
ckpt_ignore_keys: [] # only change if you want to drop certain keys in the saved checkpionts.
ckpt_only_use_keys: null # only change if you want to only use certain keys in the saved checkpionts.
monitoring: tensorboard
i_save: 900 # unit: seconds
i_backup: 50000 # unit: itertation steps
i_val: 500
i_val_mesh: 10000