StyleNeRF / conf /model /stylenerf_ffhq_ae.yaml
Jiatao Gu
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# @package _group_
name: stylenerf_ffhq
G_kwargs:
class_name: "training.networks.Generator"
z_dim: 512
w_dim: 512
mapping_kwargs:
num_layers: ${spec.map}
synthesis_kwargs:
# global settings
num_fp16_res: ${num_fp16_res}
channel_base: 1
channel_max: 1024
conv_clamp: 256
kernel_size: 1
architecture: skip
upsample_mode: "nn_cat"
z_dim: 0
resolution_vol: 128
resolution_start: 128
rgb_out_dim: 32
use_noise: False
module_name: "training.stylenerf.NeRFSynthesisNetwork"
no_bbox: True
margin: 0
magnitude_ema_beta: 0.999
camera_kwargs:
range_v: [1.4157963267948965, 1.7257963267948966]
range_u: [-0.3, 0.3]
range_radius: [1.0, 1.0]
depth_range: [0.88, 1.12]
fov: 12
gaussian_camera: True
angular_camera: True
depth_transform: ~
dists_normalized: True
ray_align_corner: False
bg_start: 0.5
renderer_kwargs:
n_ray_samples: 32
abs_sigma: False
hierarchical: True
no_background: True
foreground_kwargs:
downscale_p_by: 1
use_style: "StyleGAN2"
predict_rgb: False
use_viewdirs: False
add_rgb: True
n_blocks: 0
input_kwargs:
output_mode: 'tri_plane_reshape'
input_mode: 'random'
in_res: 4
out_res: 256
out_dim: 32
upsampler_kwargs:
no_2d_renderer: False
no_residual_img: False
block_reses: ~
shared_rgb_style: False
upsample_type: "bilinear"
progressive: True
# reuglarization
n_reg_samples: 0
reg_full: False
encoder_kwargs:
class_name: "training.stylenerf.Encoder"
num_fp16_res: ${num_fp16_res}
channel_base: ${spec.fmaps}
channel_max: 512
conv_clamp: 256
architecture: skip
progressive: ${..synthesis_kwargs.progressive}
lowres_head: ${..synthesis_kwargs.resolution_start}
upsample_type: "bilinear"
model_kwargs:
output_mode: "W+"
predict_camera: False
D_kwargs:
class_name: "training.stylenerf.Discriminator"
epilogue_kwargs:
mbstd_group_size: ${spec.mbstd}
num_fp16_res: ${num_fp16_res}
channel_base: ${spec.fmaps}
channel_max: 512
conv_clamp: 256
architecture: skip
predict_camera: True
progressive: ${model.G_kwargs.synthesis_kwargs.progressive}
lowres_head: ${model.G_kwargs.synthesis_kwargs.resolution_start}
upsample_type: "bilinear"
resize_real_early: True
# loss kwargs
loss_kwargs:
pl_batch_shrink: 2
pl_decay: 0.01
pl_weight: 2
style_mixing_prob: 0.9
curriculum: [500,5000]