ext2.0 / sec /simple_kes_scheduler.yaml
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scheduler:
#Optionally print to a log file for debugging. If false, debug is turned off, and no log file will be created.
#config options: true or false
debug: false
# The minimum value for the noise level (sigma) during image generation.
# Decreasing this value makes the image clearer but less detailed.
# Increasing it makes the image noisier but potentially more artistic or abstract.
sigma_min: 0.01 # Default: 0.01, Suggested range: 0.01 - 0.1
# The maximum value for the noise level (sigma) during image generation.
# Increasing this value can create more variation in the image details.
# Lower values keep the image more stable and less noisy.
sigma_max: 50 # Default: 50, Suggested range:10 - 60
# The device used for running the scheduler. If you have a GPU, set this to "cuda".
# Otherwise, use "cpu", but note that it will be significantly slower.
#device: "cuda" # Options: "cuda" (GPU) or "cpu" (processor)
# Initial blend factor between Karras and Exponential noise methods.
# A higher initial blend makes the image sharper at the start.
# A lower initial blend makes the image smoother early on.
start_blend: 0.1 # Default: 0.1, Suggested range: 0.05 - 0.2
# Final blend factor between Karras and Exponential noise methods.
# Higher values blend more noise at the end, possibly adding more detail.
# Lower values blend less noise for smoother, simpler images at the end.
end_blend: 0.5 # Default: 0.5, Suggested range: 0.4 - 0.6
# Sharpening factor applied to images during generation.
# Higher values increase sharpness but can add unwanted artifacts.
# Lower values reduce sharpness but may make the image look blurry.
sharpness: 0.95 # Default: 0.95, Suggested range: 0.8 - 1.0
# Early stopping threshold for stopping the image generation when changes between steps are minimal.
# Lower values stop early, saving time, but might produce incomplete images.
# Higher values take longer but may give more detailed results.
early_stopping_threshold: 0.01 # Default: 0.01, Suggested range: 0.005 - 0.02
# The number of steps between updates of the blend factor.
# Smaller values update the blend more frequently for smoother transitions.
# Larger values update the blend less frequently for faster processing.
update_interval: 10 # Default: 10, Suggested range: 5 - 15
# Initial step size, which controls how quickly the image evolves early on.
# Higher values make big changes at the start, possibly generating faster but less refined images.
# Lower values make smaller changes, giving more control over details.
initial_step_size: 0.9 # Default, 0.9, Suggested range: 0.5 - 1.0
# Final step size, which controls how much the image changes towards the end.
# Higher values keep details more flexible until the end, which may add complexity.
# Lower values lock the details earlier, making the image simpler.
final_step_size: 0.2 # Default: 0.2, Suggested range: 0.1 - 0.3
# Initial noise scaling applied to the image generation process.
# Higher values add more noise early on, making the initial image more random.
# Lower values reduce noise early on, leading to a smoother initial image.
initial_noise_scale: 1.25 # Default, 1.25, Suggested range: 1.0 - 1.5
# Final noise scaling applied at the end of the image generation.
# Higher values add noise towards the end, possibly adding fine detail.
# Lower values reduce noise towards the end, making the final image smoother.
final_noise_scale: 0.8 # Default, 0.8, Suggested range: 0.6 - 1.0
smooth_blend_factor: 11 #Default: 11, try 6 for more variation
step_size_factor: 0.75 #suggested value (0.8) to avoid oversmoothing
noise_scale_factor: 0.95 #suggested value (0.9) to add more variation
# Enables global randomization.
# If true, all parameters are randomized within specified min/max ranges.
# If false, individual parameters with _rand flags set to true will still be randomized.
randomize: true
#Sigma values typically start very small. Lowering this could allow more gradual noise reduction. Too large would overwhelm the process.
sigma_min_rand: false
sigma_min_rand_min: 0.001
sigma_min_rand_max: 0.05
#Sigma max controls the upper limit of the noise. A lower minimum could allow faster convergence, while a higher max gives more flexibility for noisier images.
sigma_max_rand: false
sigma_max_rand_min: 10
sigma_max_rand_max: 60
#Start blend controls how strongly Karras and Exponential are blended at the start. A slightly lower value introduces more variety in the blending at the beginning.
start_blend_rand: false
start_blend_rand_min: 0.05
start_blend_rand_max: 0.2
# End blend affects how much the blending changes towards the end. Increasing the upper limit would allow more variation.
end_blend_rand: false
end_blend_rand_min: 0.4
end_blend_rand_max: 0.6
# Sharpness controls detail retention. You wouldn’t want to lower it too much, as it might lose detail.
sharpness_rand: false
sharpness_rand_min: 0.85
sharpness_rand_max: 1.0
#A smaller early stopping threshold could lead to earlier stopping if the changes between sigma steps become too small, while the upper value would prevent early stopping until larger changes occur.
early_stopping_rand: false
early_stopping_rand_min: 0.001
early_stopping_rand_max: 0.02
#Update intervals affect how frequently blending factors are updated. More frequent updates allow more flexibility in blending.
update_interval_rand: false
update_interval_rand_min: 5
update_interval_rand_max: 10
# The initial step size defines how large the steps are at the start. A slightly smaller value introduces more gradual transitions.
initial_step_rand: false
initial_step_rand_min: 0.7
initial_step_rand_max: 1.0
# The final step size defines how small the steps become towards the end. A slightly larger range gives more control over the final convergence.
final_step_rand: false
final_step_rand_min: 0.1
final_step_rand_max: 0.3
#Initial noise scale defines how much noise to introduce initially. Larger values make the process start with more randomness, while smaller values keep it controlled.
initial_noise_rand: false
initial_noise_rand_min: 1.0
initial_noise_rand_max: 1.5
# Final noise scale affects how much noise is reduced at the end. A lower minimum allows more noise to persist, while a higher maximum ensures full convergence.
final_noise_rand: false
final_noise_rand_min: 0.6
final_noise_rand_max: 1.0
#The smooth blend factor controls how aggressively the blending is smoothed. Lower values allow more abrupt blending changes, while higher values give smoother transitions.
smooth_blend_factor_rand: false
smooth_blend_factor_rand_min: 6
smooth_blend_factor_rand_max: 11
#Step size factor adjusts the step size dynamically to avoid oversmoothing. A lower minimum increases variety, while a higher max provides smoother results.
step_size_factor_rand: false
step_size_factor_rand_min: 0.65
step_size_factor_rand_max: 0.85
# Noise scale factor controls how noise is scaled throughout the steps. A slightly lower minimum adds more variety, while keeping the maximum value near the suggested ensures more uniform results.
noise_scale_factor_rand: false
noise_scale_factor_rand_min: 0.75
noise_scale_factor_rand_max: 0.95