dataset_name = RealEstate10K
datadir = data/RealEstate10K/00000
expname =  test
basedir = ./log_RealEstate10K
train_frame_num = [10, 20]
test_frame_num = [5,6,7,8,9,11,12,13,14,15,16,17,18,19,21,22,23,24,25]
# val can use [5, 15, 25]

downsample_train = 1.0
ndc_ray = 1

n_iters = 10000
batch_size = 2048
novel_batch_size = 2048

# N_voxel_init = 2097156 # 32**3
N_voxel_init = 512 # 8**3
# N_voxel_final = 262144000 # 640**3
# N_voxel_final = 884736000 # 960**3
N_voxel_final = 27000000 # 300**3
down_sampling_ratio = [2,4]

upsamp_list = [2000,3000,4000,5500,7000]
update_AlphaMask_list = [2000,4000]

N_vis = 2 # vis all testing images
vis_every = 12000

render_train = 0
render_test = 1
render_path = 1

n_lamb_sigma = [16,4,4]
n_lamb_sh = [48,12,12]

shadingMode = MLP_Fea
fea2denseAct = relu

view_pe = 0
fea_pe = 0

MR_color_weight = 1
LR_color_weight = 1

TV_weight_density = 0.1
TV_weight_app = 1
TV_weight_color_density = 0.0

Sparse_Depth_weight = 0.0
Self_Depth_weight = 0.001
Dist_weight = 0.0001
Depth_Smooth_weight = 0.0

self_depth_start_iter = 0
reprojection_error_thr = 1.0
warping_patch_size = 5

lr_init = 0.04
lr_basis = 2e-3
lr_decay_target_ratio = 0.05
