Image-GS / cfgs /default.yaml
Julien Blanchon
Deploy optimized Image-GS with dynamic dependencies
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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