Commit
·
4ddd995
1
Parent(s):
ec8745e
Add initial defaults
Browse files- default.cfg +75 -0
- disco_diffusion_defaults.cfg +72 -0
default.cfg
ADDED
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#Optimized to run on Colab Free
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#If you like your setting consider sharing it to the settings library at https://github.com/multimodalart/MajestyDiffusion
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[model_list]
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model_list = ['openimages']
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[clip_list]
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perceptors = ['[clip - mlfoundations - ViT-B-16--openai]', '[clip - mlfoundations - ViT-B-32--laion2b_e16]']
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[basic_settings]
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#Perceptor things
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clip_guidance_scale = 2400
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step = 100
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aesthetic_loss_scale = 100
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augment_cuts=True
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#Init image settings
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starting_timestep = 0.9
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init_scale = 1000
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mask_scale = 0
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[advanced_settings]
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#Add CLIP Guidance and all the flavors or just run normal Latent Diffusion
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use_secondary_model=False
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use_original_as_clip_in=0
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lerp=True
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#Cut settings
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cut_overview = [16]*1000
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cut_innercut = [0]*1200
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cut_ic_pow = 0.3
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cut_icgray_p = [0.2]*100 + [0]*1200
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cutn_batches = 2
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sat_index = [0]*1040
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range_index = [1500000]*100 + [0]*1000
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eta_index = [1.2]*100
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active_function = "softsign"
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tv_scales = [150]*4
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tv_scale_2 = []
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n_batches = 1
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unified_cutouts = True
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ns_cutn = 10
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step_enhance=True
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mid_point = 0.6
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steps_pow = 1
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#cfg_scale only for cc12m_cfg
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cfg_scale = 3
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#If you uncomment this line you can schedule the CLIP guidance across the steps. Otherwise the clip_guidance_scale will be used
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clip_guidance_schedule = [2400]*1000
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#Apply symmetric loss (force simmetry to your results)
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symmetric_loss_scale = 0
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#Grad and mag advanced settings
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grad_center = False
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#Lower value result in more coherent and detailed result, higher value makes it focus on more dominent concept
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grad_scale=0.1
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mag_mul = 10
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clamp_start_=0
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clamp_index = [0.05]*200 + [0.04]*800
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#More settings
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RGB_min = -0.95
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RGB_max = 0.95
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#How to pad the image with cut_overview
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padargs = {'mode': 'constant', 'value': -1}
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flip_aug=False
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cc = 6
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#Internal upscaler settings
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activate_upscaler = False
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upscale_model = "yfcc_2"
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multiply_image_size_by = 2
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disco_diffusion_defaults.cfg
ADDED
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#Settings similar to the default ones on the Disco Diffusion Colab Notebook (https://colab.research.google.com/github/alembics/disco-diffusion/blob/main/Disco_Diffusion.ipynb)
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[model_list]
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model_list = ['openimages']
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[basic_settings]
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#Perceptor things
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width = 512
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height = 512
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clip_guidance_scale = 5000
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step = 100
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aesthetic_loss_scale = 100
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augment_cuts=True
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#Init image settings
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starting_timestep = 0.9
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init_scale = 1000
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mask_scale = 0
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[advanced_settings]
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#Add CLIP Guidance and all the flavors or just run normal Latent Diffusion
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+
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+
use_secondary_model=False
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use_original_as_clip_in=0
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lerp=True
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#Cut settings
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cut_overview = [12]*400+[4]*600
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cut_innercut = [4]*400+[12]*600
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cut_ic_pow = 1
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cut_icgray_p = [0.2]*100 + [0]*1200
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cutn_batches = 4
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sat_index = [0]*1040
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range_index = [1500000]*100 + [0]*1000
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eta_index = [0.8]*100
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active_function = "softsign"
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tv_scales = [150]*4
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tv_scale_2 = []
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n_batches = 1
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unified_cutouts = True
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ns_cutn = 10
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step_enhance=True
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mid_point = 0.6
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steps_pow = 1
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#cfg_scale only for cc12m_cfg
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cfg_scale = 3
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#If you uncomment this line you can schedule the CLIP guidance across the steps. Otherwise the clip_guidance_scale will be used
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clip_guidance_schedule = [2400]*1000
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#Apply symmetric loss (force simmetry to your results)
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symmetric_loss_scale = 0
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+
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+
#Grad and mag advanced settings
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+
grad_center = False
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+
#Lower value result in more coherent and detailed result, higher value makes it focus on more dominent concept
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+
grad_scale=0.1
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+
mag_mul = 10
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+
clamp_start_=0
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+
clamp_index = [0.05]*200 + [0.04]*800
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+
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#More settings
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+
RGB_min = -0.95
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+
RGB_max = 0.95
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+
#How to pad the image with cut_overview
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+
padargs = {'mode': 'constant', 'value': -1}
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flip_aug=False
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cc = 6
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#Internal upscaler settings
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activate_upscaler = False
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upscale_model = "yfcc_2"
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multiply_image_size_by = 2
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