latent-majesty-diffusion-settings / dango233_princesses.cfg
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Add initial defaults
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#This settings file can be loaded back to Latent Majesty Diffusion. If you like your setting consider sharing it to the settings library at https://github.com/multimodalart/MajestyDiffusion
[clip_list]
perceptors = ['[clip - mlfoundations - ViT-B-16--openai]', '[clip - mlfoundations - ViT-B-16--laion400m_e32]', '[clip - mlfoundations - ViT-B-32--laion2b_e16]']
[basic_settings]
#Perceptor things
#clip_prompts = ['portrait of a princess in sanctuary, hyperrealistic painting trending on artstation']
#atent_prompts = ['portrait of a princess in sanctuary, hyperrealistic painting trending on artstation']
#latent_negatives = ['']
#image_prompts = []
latent_diffusion_guidance_scale = 2
clip_guidance_scale = 5000
aesthetic_loss_scale = 200
augment_cuts=True
#Init image settings
starting_timestep = 0.9
init_scale = 0
init_brightness = 0.0
init_noise = 0.6
[advanced_settings]
#Add CLIP Guidance and all the flavors or just run normal Latent Diffusion
use_cond_fn = True
#Custom schedules for cuts. Check out the schedules documentation here
custom_schedule_setting = [[30, 900.0, 8], 'gfpgan:1', [20, 200, 6]]
#Cut settings
clamp_index = [1]*1000
cut_overview = [8]*500 + [4]*500
cut_innercut = [0]*500 + [4]*500
cut_ic_pow = 0.1
cut_icgray_p = [0.1]*300 + [0]*1000
cutn_batches = 1
range_index = [0]*1300
active_function = "softsign"
tv_scales = [1200]*1 + [600]*3
latent_tv_loss = True
#If you uncomment this line you can schedule the CLIP guidance across the steps. Otherwise the clip_guidance_scale will be used
clip_guidance_schedule = [5000]*1000
#Apply symmetric loss (force simmetry to your results)
symmetric_loss_scale = 0
#Latent Diffusion Advanced Settings
#Use when latent upscale to correct satuation problem
scale_div = 0.5
#Magnify grad before clamping by how many times
opt_mag_mul = 10
opt_ddim_eta = 1.4
opt_eta_end = 1.0
opt_temperature = 0.975
#Grad advanced settings
grad_center = False
#Lower value result in more coherent and detailed result, higher value makes it focus on more dominent concept
grad_scale=0.5
#Init image advanced settings
init_rotate=False
mask_rotate=False
init_magnitude = 0.15
#More settings
RGB_min = -0.95
RGB_max = 0.95
#How to pad the image with cut_overview
padargs = {'mode': 'constant', 'value': -1}
flip_aug=False
cc = 60
#Experimental aesthetic embeddings, work only with OpenAI ViT-B/32 and ViT-L/14
experimental_aesthetic_embeddings = False
#How much you want this to influence your result
experimental_aesthetic_embeddings_weight = 1
#9 are good aesthetic embeddings, 0 are bad ones
experimental_aesthetic_embeddings_score = 8
#Deactivating new stuff from 1.5
score_modifier = False
compress_steps = 0
punish_steps = 0