seed:                  123
device:                "cuda:0"
# Evaluation
eval:                  False # Render the optimized Image-GS representation
render_height:         2048 # Image height for rendering (aspect ratio is maintained)
# Bit precision
quantize:              False # Enable bit precision control of Gaussian parameters
pos_bits:              16 # Bit precision of individual coordinate dimension
scale_bits:            16 # Bit precision of individual scale dimension
rot_bits:              16 # Bit precision of Gaussian orientation angle
feat_bits:             16 # Bit precision of individual feature dimension
# Logging
log_root:              "results"
exp_name:              "test/anime-1_2k" # Path to the logging directory
log_level:             "INFO"
vis_gaussians:         False # Visualize Gaussians during optimization
save_image_steps:      100000 # Frequency of rendering intermediate results during optimization
save_ckpt_steps:       100000 # Frequency of checkpointing during optimization
eval_steps:            100
# Target images
gamma:                 1.0 # Optimize in a gamma-corrected space, modify with caution
data_root:             "media"
input_path:            "images/anime-1_2k.png" # Path to an image file or a directory containing a texture stack
downsample:            False # Load a downsampled version of the input image or texture stack as the optimization target to evaluate image upsampling performance
downsample_ratio:      2.0
# Gaussians
num_gaussians:         10000 # Number of Gaussians (for compression rate control)
init_scale:            5.0 # Initial Gaussian scale in number of pixels
topk:                  10 # Warning: Must match hardcoded value in CUDA kernel, modify with caution
disable_topk_norm:     False # Disable top-K normalization
disable_inverse_scale: False # Disable inverse Gaussian scale optimization
ckpt_file:             ""
disable_color_init:    False
init_mode:             "gradient" # Gaussian position initialization mode, valid values include "gradient", "saliency", and "random"
init_random_ratio:     0.3 # Ratio of Gaussians with randomly initialized position
smap_filter_size:      20 # Gaussian filter size for smoothing saliency maps
# Loss functions
l1_loss_ratio:         1.0
l2_loss_ratio:         0.0
ssim_loss_ratio:       0.1
# Optimization
disable_tiles:         False # Disable tile-based rendering (warning: optimization and rendering without tiles will be way slower)
max_steps:             10000 # Maximum number of optimization steps
pos_lr:                5.0e-4
scale_lr:              2.0e-3
rot_lr:                2.0e-3
feat_lr:               5.0e-3
disable_lr_schedule:   False # Disable learning rate schedule and early stopping
decay_ratio:           10.0
check_decay_steps:     1000
max_decay_times:       1
decay_threshold:       1.0e-3
disable_prog_optim:    False # Disable error-guided progressive optimization
initial_ratio:         0.5
add_steps:             500
add_times:             4
post_min_steps:        3000