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import modules.scripts as scripts
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import gradio as gr
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import os
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import platform
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import subprocess as sp
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from modules import images
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from modules.processing import process_images, Processed
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from modules.processing import Processed
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from modules.shared import opts, cmd_opts, state
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from build_dynamic_prompt import *
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from main import *
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from model_lists import *
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from csv_reader import *
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from one_button_presets import OneButtonPresets
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OBPresets = OneButtonPresets()
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basemodelslist = ["SD1.5", "SDXL", "Stable Cascade", "Anime Model"]
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subjects =["------ all"]
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subjectsubtypesobject = ["all"]
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subjectsubtypeshumanoid = ["all"]
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subjectsubtypesconcept = ["all"]
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artists = ["all", "all (wild)", "none", "popular", "greg mode", "3D", "abstract", "angular", "anime" ,"architecture", "art nouveau", "art deco", "baroque", "bauhaus", "cartoon", "character", "children's illustration", "cityscape", "cinema", "clean", "cloudscape", "collage", "colorful", "comics", "cubism", "dark", "detailed", "digital", "expressionism", "fantasy", "fashion", "fauvism", "figurativism", "gore", "graffiti", "graphic design", "high contrast", "horror", "impressionism", "installation", "landscape", "light", "line drawing", "low contrast", "luminism", "magical realism", "manga", "melanin", "messy", "monochromatic", "nature", "nudity", "photography", "pop art", "portrait", "primitivism", "psychedelic", "realism", "renaissance", "romanticism", "scene", "sci-fi", "sculpture", "seascape", "space", "stained glass", "still life", "storybook realism", "street art", "streetscape", "surrealism", "symbolism", "textile", "ukiyo-e", "vibrant", "watercolor", "whimsical"]
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imagetypes = ["all", "all - force multiple", "all - anime", "none", "photograph", "octane render","digital art","concept art", "painting", "portrait", "anime", "only other types", "only templates mode", "dynamic templates mode", "art blaster mode", "quality vomit mode", "color cannon mode", "unique art mode", "massive madness mode", "photo fantasy mode", "subject only mode", "fixed styles mode", "the tokinator"]
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promptmode = ["at the back", "in the front"]
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promptcompounder = ["1", "2", "3", "4", "5"]
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ANDtogglemode = ["none", "automatic", "prefix AND prompt + suffix", "prefix + prefix + prompt + suffix"]
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seperatorlist = ["comma", "AND", "BREAK"]
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genders = ["all", "male", "female"]
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prompt_enhancers = ["none", "superprompt-v1"]
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qualitymodelist = ["highest", "gated"]
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qualitykeeplist = ["keep used","keep all"]
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amountofflufflist = ["none", "dynamic", "short", "medium", "long"]
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sizelist = ["all", "portrait", "wide", "square", "ultrawide", "ultraheight", "wild"]
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basesizelist = ["512", "768", "1024"]
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modellist = get_models()
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modellist.insert(0,"all")
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modellist.insert(0,"currently selected model")
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upscalerlist = get_upscalers()
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upscalerlist.insert(0,"automatic")
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upscalerlist.insert(0,"all")
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samplerlist = get_samplers()
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samplerlist.insert(0,"all")
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img2imgupscalerlist = get_upscalers_for_img2img()
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img2imgupscalerlist.insert(0,"automatic")
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img2imgupscalerlist.insert(0,"all")
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img2imgsamplerlist = get_samplers_for_img2img()
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img2imgsamplerlist.insert(0,"all")
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seams_fix_types = ["None","Band pass","Half tile offset pass","Half tile offset pass + intersections"]
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redraw_modes = ["Linear","Chess","None"]
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folder_symbol = '\U0001f4c2'
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sys.path.append(os.path.abspath(".."))
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script_dir = os.path.dirname(os.path.abspath(__file__))
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userfilesfolder = os.path.join(script_dir, "../userfiles/" )
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for filename in os.listdir(userfilesfolder):
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if(filename.endswith(".csv") and filename.startswith("personal_artists") and filename != "personal_artists_sample.csv"):
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name = os.path.splitext(filename)[0]
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name = name.replace("_"," ",-1).lower()
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artists.insert(2, name)
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config = load_config_csv()
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generatevehicle = True
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generateobject = True
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generatefood = True
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generatebuilding = True
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generatespace = True
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generateflora = True
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generateanimal = True
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generatebird = True
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generatecat = True
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generatedog = True
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generateinsect = True
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generatepokemon = True
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generatemarinelife = True
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generatemanwoman = True
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generatemanwomanrelation = True
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generatemanwomanmultiple = True
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generatefictionalcharacter = True
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generatenonfictionalcharacter = True
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generatehumanoids = True
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generatejob = True
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generatefirstnames = True
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generatelandscape = True
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generatelocation = True
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generatelocationfantasy = True
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generatelocationscifi = True
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generatelocationvideogame = True
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generatelocationbiome = True
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generatelocationcity = True
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generateevent = True
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generateconcepts = True
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generatepoemline = True
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generatesongline = True
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generatecardname = True
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generateepisodetitle = True
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generateconceptmixer = True
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for item in config:
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if item[0] == 'subject_vehicle' and item[1] != 'on':
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generatevehicle = False
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if item[0] == 'subject_object' and item[1] != 'on':
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generateobject = False
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if item[0] == 'subject_food' and item[1] != 'on':
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generatefood = False
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if item[0] == 'subject_building' and item[1] != 'on':
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generatebuilding = False
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if item[0] == 'subject_space' and item[1] != 'on':
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generatespace = False
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if item[0] == 'subject_flora' and item[1] != 'on':
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generateflora = False
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if item[0] == 'subject_animal' and item[1] != 'on':
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generateanimal = False
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if item[0] == 'subject_bird' and item[1] != 'on':
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generatebird = False
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if item[0] == 'subject_cat' and item[1] != 'on':
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generatecat = False
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if item[0] == 'subject_dog' and item[1] != 'on':
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generatedog = False
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if item[0] == 'subject_insect' and item[1] != 'on':
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generateinsect = False
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if item[0] == 'subject_pokemon' and item[1] != 'on':
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generatepokemon = False
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if item[0] == 'subject_marinelife' and item[1] != 'on':
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generatemarinelife = False
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if item[0] == 'subject_manwoman' and item[1] != 'on':
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generatemanwoman = False
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if item[0] == 'subject_manwomanrelation' and item[1] != 'on':
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generatemanwomanrelation = False
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if item[0] == 'subject_manwomanmultiple' and item[1] != 'on':
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generatemanwomanmultiple = False
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if item[0] == 'subject_fictional' and item[1] != 'on':
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generatefictionalcharacter = False
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if item[0] == 'subject_nonfictional' and item[1] != 'on':
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generatenonfictionalcharacter = False
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if item[0] == 'subject_humanoid' and item[1] != 'on':
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generatehumanoids = False
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if item[0] == 'subject_job' and item[1] != 'on':
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generatejob = False
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if item[0] == 'subject_firstnames' and item[1] != 'on':
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generatefirstnames = False
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if item[0] == 'subject_location' and item[1] != 'on':
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generatelocation = False
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if item[0] == 'subject_location_fantasy' and item[1] != 'on':
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generatelocationfantasy = False
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if item[0] == 'subject_location_scifi' and item[1] != 'on':
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generatelocationscifi = False
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if item[0] == 'subject_location_videogame' and item[1] != 'on':
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generatelocationvideogame = False
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if item[0] == 'subject_location_biome' and item[1] != 'on':
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generatelocationbiome = False
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if item[0] == 'subject_location_city' and item[1] != 'on':
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generatelocationcity = False
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if item[0] == 'subject_event' and item[1] != 'on':
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generateevent = False
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if item[0] == 'subject_concept' and item[1] != 'on':
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generateconcepts = False
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if item[0] == 'subject_poemline' and item[1] != 'on':
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generatepoemline = False
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if item[0] == 'subject_songline' and item[1] != 'on':
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generatesongline = False
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if item[0] == 'subject_cardname' and item[1] != 'on':
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generatecardname = False
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if item[0] == 'subject_episodetitle' and item[1] != 'on':
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generateepisodetitle = False
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if item[0] == 'subject_conceptmixer' and item[1] != 'on':
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generateconceptmixer = False
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if(generatevehicle or generateobject or generatefood or generatebuilding or generatespace or generateflora):
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subjects.append("--- object - all")
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if(generateobject):
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subjects.append("object - generic")
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if(generatevehicle):
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subjects.append("object - vehicle")
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if(generatefood):
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subjects.append("object - food")
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if(generatebuilding):
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subjects.append("object - building")
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if(generatespace):
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subjects.append("object - space")
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if(generateflora):
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subjects.append("object - flora")
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if(generateanimal or generatebird or generatecat or generatedog or generateinsect or generatepokemon or generatemarinelife):
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subjects.append("--- animal - all")
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if(generateanimal):
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subjects.append("animal - generic")
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if(generatebird):
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subjects.append("animal - bird")
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if(generatecat):
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subjects.append("animal - cat")
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if(generatedog):
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subjects.append("animal - dog")
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if(generateinsect):
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subjects.append("animal - insect")
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if(generatemarinelife):
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subjects.append("animal - marine life")
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if(generatepokemon):
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subjects.append("animal - pokémon")
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if(generatemanwoman or generatemanwomanrelation or generatefictionalcharacter or generatenonfictionalcharacter or generatehumanoids or generatejob or generatemanwomanmultiple):
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subjects.append("--- human - all")
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if(generatemanwoman):
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subjects.append("human - generic")
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if(generatemanwomanrelation):
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subjects.append("human - relations")
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if(generatenonfictionalcharacter):
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subjects.append("human - celebrity")
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if(generatefictionalcharacter):
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subjects.append("human - fictional")
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if(generatehumanoids):
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subjects.append("human - humanoids")
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if(generatejob):
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subjects.append("human - job/title")
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if(generatefirstnames):
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subjects.append("human - first name")
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if(generatemanwomanmultiple):
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subjects.append("human - multiple")
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if(generatelandscape or generatelocation or generatelocationfantasy or generatelocationscifi or generatelocationvideogame or generatelocationbiome or generatelocationcity):
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subjects.append("--- landscape - all")
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if(generatelocation):
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subjects.append("landscape - generic")
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if(generatelocationfantasy):
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subjects.append("landscape - fantasy")
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if(generatelocationscifi):
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subjects.append("landscape - sci-fi")
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if(generatelocationvideogame):
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subjects.append("landscape - videogame")
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if(generatelocationbiome):
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subjects.append("landscape - biome")
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if(generatelocationcity):
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subjects.append("landscape - city")
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if(generateevent or generateconcepts or generatepoemline or generatesongline or generatecardname or generateepisodetitle or generateconceptmixer):
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subjects.append("--- concept - all")
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if(generateevent):
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subjects.append("concept - event")
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if(generateconcepts):
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subjects.append("concept - the x of y")
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if(generatepoemline):
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subjects.append("concept - poem lines")
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if(generatesongline):
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subjects.append("concept - song lines")
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if(generatecardname):
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subjects.append("concept - card names")
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if(generateepisodetitle):
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subjects.append("concept - episode titles")
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if(generateconceptmixer):
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subjects.append("concept - mixer")
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if(generateobject):
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subjectsubtypesobject.append("generic objects")
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if(generatevehicle):
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subjectsubtypesobject.append("vehicles")
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if(generatefood):
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subjectsubtypesobject.append("food")
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if(generatebuilding):
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subjectsubtypesobject.append("buildings")
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if(generatespace):
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subjectsubtypesobject.append("space")
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if(generateflora):
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subjectsubtypesobject.append("flora")
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if(generatemanwoman):
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subjectsubtypeshumanoid.append("generic humans")
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if(generatemanwomanrelation):
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subjectsubtypeshumanoid.append("generic human relations")
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if(generatenonfictionalcharacter):
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subjectsubtypeshumanoid.append("celebrities e.a.")
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if(generatefictionalcharacter):
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subjectsubtypeshumanoid.append("fictional characters")
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if(generatehumanoids):
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subjectsubtypeshumanoid.append("humanoids")
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if(generatejob):
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subjectsubtypeshumanoid.append("based on job or title")
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if(generatefirstnames):
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subjectsubtypeshumanoid.append("based on first name")
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if(generatemanwomanmultiple):
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subjectsubtypeshumanoid.append("multiple humans")
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if(generateevent):
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subjectsubtypesconcept.append("event")
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if(generateconcepts):
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subjectsubtypesconcept.append("the X of Y concepts")
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if(generatepoemline):
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subjectsubtypesconcept.append("lines from poems")
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if(generatesongline):
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subjectsubtypesconcept.append("lines from songs")
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if(generatecardname):
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subjectsubtypesconcept.append("names from card based games")
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if(generateepisodetitle):
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subjectsubtypesconcept.append("episode titles from tv shows")
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if(generateconceptmixer):
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subjectsubtypesconcept.append("concept mixer")
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class Script(scripts.Script):
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def title(self):
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return "One Button Prompt"
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def show(self, is_img2img):
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return True
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def ui(self, is_img2img):
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def gen_prompt(insanitylevel, subject, artist, imagetype, antistring, prefixprompt, suffixprompt, promptcompounderlevel, seperator,givensubject,smartsubject,giventypeofimage, imagemodechance,chosengender, chosensubjectsubtypeobject, chosensubjectsubtypehumanoid, chosensubjectsubtypeconcept,givenoutfit, base_model, OBP_preset, amountoffluff, promptenhancer, presetprefix, presetsuffix):
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promptlist = []
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for i in range(5):
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base_prompt = build_dynamic_prompt(insanitylevel,subject,artist, imagetype, False, antistring,prefixprompt,suffixprompt,promptcompounderlevel,seperator,givensubject,smartsubject, giventypeofimage, imagemodechance,chosengender, chosensubjectsubtypeobject, chosensubjectsubtypehumanoid, chosensubjectsubtypeconcept,True,False,-1,givenoutfit,False,base_model, OBP_preset, promptenhancer, "", "", presetprefix, presetsuffix)
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fluffed_prompt = flufferizer(prompt=base_prompt, amountoffluff=amountoffluff)
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promptlist.append(fluffed_prompt)
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return promptlist
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def prompttoworkflowprompt(text):
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return text
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def openfolder():
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script_dir = os.path.dirname(os.path.abspath(__file__))
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automatedoutputsfolder = os.path.join(script_dir, "../automated_outputs/" )
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path = os.path.normpath(automatedoutputsfolder)
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if platform.system() == "Windows":
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os.startfile(path)
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elif platform.system() == "Darwin":
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sp.Popen(["open", path])
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elif "microsoft-standard-WSL2" in platform.uname().release:
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sp.Popen(["wsl-open", path])
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else:
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sp.Popen(["xdg-open", path])
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with gr.Tab("Main"):
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with gr.Row(variant="compact"):
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gr.Markdown("""
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<font size="2">
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One Button Prompt is now active. Just press the normal Generate button to start generating images.
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Presets can be used to store and load settings.
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Set the One Button Preset to __"Custom..."__ to show all settings. The settings will give you more control over what you wish to generate.
|
|
|
|
|
|
Choose __"All (random)..."__ to get a random preset each prompt generation.
|
|
|
</font>
|
|
|
""")
|
|
|
|
|
|
with gr.Row():
|
|
|
OBP_preset = gr.Dropdown(
|
|
|
label="One Button Preset",
|
|
|
choices=[OBPresets.RANDOM_PRESET_OBP] + [OBPresets.CUSTOM_OBP] + list(OBPresets.opb_presets.keys()),
|
|
|
value="Standard",
|
|
|
)
|
|
|
with gr.Group(visible=True) as presetgroup:
|
|
|
with gr.Row():
|
|
|
gr.Markdown("""
|
|
|
<font size="2">
|
|
|
These prefix and suffix are run on top the of preset. Can be used for LoRA's and other general stylings.
|
|
|
</font>
|
|
|
""")
|
|
|
with gr.Row():
|
|
|
presetprefix = gr.Textbox(label="Preset prefix: ", value="")
|
|
|
presetsuffix = gr.Textbox(label="Preset suffix: ", value="")
|
|
|
|
|
|
with gr.Group(visible=False) as maingroup:
|
|
|
gr.Markdown("""
|
|
|
<font size="2">
|
|
|
Type a name and press "Save as Preset" to store the current generation settings.
|
|
|
</font>
|
|
|
""")
|
|
|
with gr.Row():
|
|
|
obp_preset_name = gr.Textbox(
|
|
|
show_label=False,
|
|
|
placeholder="Name of new preset",
|
|
|
interactive=True,
|
|
|
visible=True,
|
|
|
)
|
|
|
obp_preset_save = gr.Button(
|
|
|
value="Save as preset",
|
|
|
visible=True,
|
|
|
)
|
|
|
gr.Markdown("""
|
|
|
<font size="4">
|
|
|
Generation settings:
|
|
|
</font>
|
|
|
""")
|
|
|
|
|
|
|
|
|
|
|
|
with gr.Row(variant="compact"):
|
|
|
insanitylevel = gr.Slider(1, 10, value=5, step=1, label="🎲⬅️❔➡️🎲🎲🎲 Higher levels increases complexity and randomness of generated prompt")
|
|
|
with gr.Row(variant="compact"):
|
|
|
with gr.Column(variant="compact"):
|
|
|
subject = gr.Dropdown(
|
|
|
subjects, label="📸 Subject Types", value="all")
|
|
|
with gr.Column(variant="compact"):
|
|
|
artist = gr.Dropdown(
|
|
|
artists, label="🎨 Artists", value="all")
|
|
|
with gr.Row(variant="compact"):
|
|
|
chosensubjectsubtypeobject = gr.Dropdown(
|
|
|
subjectsubtypesobject, label="🏺 Type of object", value="all", visible=False)
|
|
|
chosensubjectsubtypehumanoid = gr.Dropdown(
|
|
|
subjectsubtypeshumanoid, label="👨👩👧 Type of humanoids", value="all", visible=False)
|
|
|
chosensubjectsubtypeconcept = gr.Dropdown(
|
|
|
subjectsubtypesconcept, label="💡🧠💭 Type of concept", value="all", visible=False)
|
|
|
chosengender = gr.Dropdown(
|
|
|
genders, label="🚻 gender", value="all", visible=False)
|
|
|
with gr.Row(variant="compact"):
|
|
|
with gr.Column(variant="compact"):
|
|
|
imagetype = gr.Dropdown(
|
|
|
imagetypes, label="🖼️ type of image", value="all")
|
|
|
with gr.Column(variant="compact"):
|
|
|
imagemodechance = gr.Slider(
|
|
|
1, 100, value="20", step=1, label="🎲🖼️ One in X chance to use special image type mode")
|
|
|
with gr.Row(variant="compact"):
|
|
|
gr.Markdown("""
|
|
|
<font size="2">
|
|
|
Override options (choose the related subject type first for better results)
|
|
|
</font>
|
|
|
"""
|
|
|
)
|
|
|
with gr.Row(variant="compact"):
|
|
|
givensubject = gr.Textbox(label="🔃📸 Overwrite subject: ", value="")
|
|
|
smartsubject = gr.Checkbox(label="🧠📸 Smart subject", value = True)
|
|
|
with gr.Row(variant="compact"):
|
|
|
givenoutfit = gr.Textbox(label="🔃👗 Overwrite outfit: ", value="")
|
|
|
with gr.Row(variant="compact"):
|
|
|
gr.Markdown("""
|
|
|
<font size="2">
|
|
|
Prompt fields
|
|
|
</font>
|
|
|
"""
|
|
|
)
|
|
|
with gr.Row(variant="compact"):
|
|
|
with gr.Column(variant="compact"):
|
|
|
prefixprompt = gr.Textbox(label="⬅️💬 Place this in front of generated prompt (prefix)",value="")
|
|
|
suffixprompt = gr.Textbox(label="➡️💬 Place this at back of generated prompt (suffix)",value="")
|
|
|
with gr.Row(variant="compact"):
|
|
|
gr.Markdown("""
|
|
|
<font size="2">
|
|
|
Additional options
|
|
|
</font>
|
|
|
"""
|
|
|
)
|
|
|
with gr.Row(variant="compact"):
|
|
|
giventypeofimage = gr.Textbox(label="🔃🖼️ Overwrite type of image: ", value="")
|
|
|
with gr.Row(variant="compact"):
|
|
|
with gr.Column(variant="compact"):
|
|
|
antistring = gr.Textbox(label="❌📝 Filter out following properties (comma seperated). Example ""film grain, purple, cat"" ")
|
|
|
with gr.Accordion("Help", open=False):
|
|
|
gr.Markdown(
|
|
|
"""
|
|
|
### Description
|
|
|
|
|
|
<font size="2">
|
|
|
Just press the normal Generate button.
|
|
|
|
|
|
This generator will generate a complete full prompt for you and generate the image, based on randomness. You can increase the slider, to include more things to put into the prompt.
|
|
|
Recommended is keeping it around 3-7. Use 10 at your own risk.
|
|
|
|
|
|
There are a lot of special things build in, based on various research papers. Just try it, and let it surprise you.
|
|
|
|
|
|
Add additional prompting to the prefix, suffix in this screen. The actual prompt fields are ignored. Negative prompt is in the respective tab.
|
|
|
</font>
|
|
|
|
|
|
### 📸 Subject Types
|
|
|
|
|
|
<font size="2">
|
|
|
You can choose a certain subject type. Choose the all version to randomly choose between the subtypes. Iff you want to generate something more specific, choose the subtype. It has the following types:
|
|
|
|
|
|
1. object - Can be a random object, a building, vehicle, space or flora.
|
|
|
|
|
|
2. animal - A random (fictional) animal. Has a chance to have human characteristics, such as clothing added.
|
|
|
|
|
|
3. humanoid - A random humanoid, males, females, fantasy types, fictional and non-fictional characters. Can add clothing, features and a bunch of other things.
|
|
|
|
|
|
4. landscape - A landscape, choose a cool location.
|
|
|
|
|
|
5. concept - Can be a concept, such as "a X of Y", or an historical event such as "The Trojan War". It can also generate a line from a poem or a song.
|
|
|
|
|
|
After choosing object, humanoid or concept a subselection menu will show. You can pick further details here. When choosing humanoid, you can also select the gender you wish to generate.
|
|
|
|
|
|
|
|
|
🚻 gender (only available for human generations):
|
|
|
|
|
|
1. all - selects randomly
|
|
|
|
|
|
2. male
|
|
|
|
|
|
3. female
|
|
|
|
|
|
</font>
|
|
|
|
|
|
### 🎨 Artists
|
|
|
|
|
|
<font size="2">
|
|
|
Artists have a major impact on the result.
|
|
|
|
|
|
1. all - it will cohesivly add about between 0-3 artists and style description.
|
|
|
|
|
|
2. all (wild) - it will randomly select between 0-3 artists out of 3483 artists for your prompt.
|
|
|
|
|
|
3. greg mode - Will add greg, or many other popular artists into your prompt. Will also add a lot of quality statements.
|
|
|
|
|
|
Others will select within that artist category
|
|
|
|
|
|
You can turn it off and maybe add your own in the prefix or suffix prompt fields
|
|
|
</font>
|
|
|
|
|
|
### 🖼️ type of image
|
|
|
|
|
|
<font size="2">
|
|
|
There are an immense number of image types, not only paintings and photo's, but also isometric renders and funko pops.
|
|
|
You can however, overwrite it with the most popular ones.
|
|
|
|
|
|
|
|
|
1. all --> normally picks a image type as random. Can choose a 'other' more unique type.
|
|
|
|
|
|
2. all - force multiple --> idea by redditor WestWordHoeDown, it forces to choose between 2 and 3 image types
|
|
|
|
|
|
3. all - anime --> Chooses from anime styles, for support of Anime Model mode.
|
|
|
|
|
|
4. none --> Turns off image type generation
|
|
|
|
|
|
5. photograph
|
|
|
|
|
|
6. octane render
|
|
|
|
|
|
7. digital art
|
|
|
|
|
|
8. concept art
|
|
|
|
|
|
9. painting
|
|
|
|
|
|
10. portrait
|
|
|
|
|
|
11. anime
|
|
|
|
|
|
12. only other types --> Will pick only from the more unique types, such as stained glass window or a funko pop
|
|
|
|
|
|
All modes below are considered a special image type mode.
|
|
|
|
|
|
13. only templates mode --> Will only choose from a set of wildcarded prompt templates. Templates have been gathered from various sources, such as CivitAI, prompthero, promptbook, etc.
|
|
|
|
|
|
only templates mode is perfect for beginners, who want to see some good results fast.
|
|
|
|
|
|
14. dynamic templates mode --> A method that uses prompts in a more natural language.
|
|
|
|
|
|
15. art blaster mode --> Special generation mode that focusses on art movements, stylings and artists.
|
|
|
|
|
|
16. quality vomit mode --> Special generation mode that focusses on qualifiers and stylings.
|
|
|
|
|
|
17. color cannon mode --> Special generation mode that focusses on color scheme's and moods.
|
|
|
|
|
|
18. unique art mode --> Special generation mode that focusses on other image types, art movements, stylings and lighting.
|
|
|
|
|
|
19. massive madness mode --> Special generation mode, creates prompt soup. Almost pure randomness.
|
|
|
|
|
|
20. photo fantasy mode --> Special generation mode that focusses on photographs, cameras, lenses and lighting.
|
|
|
|
|
|
21. subject only mode --> Will only generate a subject, with no additional frills.
|
|
|
|
|
|
22. fixed styles mode --> Generate a subject on top of a fixed style.
|
|
|
|
|
|
23. the tokinator --> Complete random word gibberish mode, use at own risk
|
|
|
|
|
|
### 🎲🖼️ One in X chance to use special image type mode
|
|
|
|
|
|
<font size="2">
|
|
|
This controls how often it will pick a special generation mode. It is a 1 in X chance. So lower means more often. This will only be applied of "type of image" is set to "all" and there is no Overwrite type of image set.
|
|
|
|
|
|
When set to 1, it will always pick a random special generation mode. When set to 20, it is a 1 in 20 chance this will happen.
|
|
|
</font>
|
|
|
|
|
|
### 🔃📸 Overwrite subject
|
|
|
|
|
|
When you fill in the Overwrite subject field, that subject will be used to build the dynamic prompt around. It is best, if you set the subject type to match the subject. For example, set it to humanoid if you place a person in the override subject field.
|
|
|
|
|
|
This way, you can create unlimited variants of a subject.
|
|
|
|
|
|
🧠📸 Smart subject tries to determine what to and not to generate based on your subject. Example, if your Overwrite subject is formed like this: Obese man wearing a kimono
|
|
|
|
|
|
It will then recognize the body type and not generate it. It also recognizes the keyword wearing, and will not generate an outfit.
|
|
|
|
|
|
### 🔃👗 Overwrite outfit
|
|
|
|
|
|
When you fill in the override outfit field, it will generate an outfit in the prompt based on the given value. It can be used in combination with override subject, but does not have to be. It works best with smaller descriptions of the outfit.
|
|
|
|
|
|
An example would be: space suit, red dress, cloak.
|
|
|
|
|
|
Works best when you set the subjects to to humanoid.
|
|
|
|
|
|
### Other prompt fields
|
|
|
|
|
|
The existing prompt and negative prompt fields are ignored.
|
|
|
|
|
|
Add a prompt prefix, suffix in the respective fields. Add negative prompt in the negative prompt tab. They will be automatically added during processing.
|
|
|
|
|
|
These can be used to add textual inversion and LoRA's to always apply. They can also be used to add your models trigger words.
|
|
|
|
|
|
Please read the custom_files documentation on how to apply random textual inversion and LoRA's.
|
|
|
|
|
|
</font>
|
|
|
|
|
|
### Filter values
|
|
|
<font size="2">
|
|
|
You can put comma seperated values here, those will be ignored from any list processing. For example, adding ""film grain, sepia"", will make these values not appear during generation.
|
|
|
|
|
|
For advanced users, you can create a permanent file in \\OneButtonPrompt\\userfiles\\ called antilist.csv
|
|
|
|
|
|
This way, you don't ever have to add it manually again. This file won't be overwritten during upgrades.
|
|
|
|
|
|
Idea by redditor jonesaid.
|
|
|
|
|
|
</font>
|
|
|
"""
|
|
|
)
|
|
|
with gr.Tab("Workflow assist"):
|
|
|
with gr.Row(variant="compact"):
|
|
|
silentmode = gr.Checkbox(
|
|
|
label="🛠️ Workflow mode, turns off prompt generation and uses below Workflow prompt instead.")
|
|
|
with gr.Row(variant="compact"):
|
|
|
workprompt = gr.Textbox(label="🛠️💬 Workflow prompt")
|
|
|
with gr.Row(variant="compact"):
|
|
|
promptvariantinsanitylevel = gr.Slider(0, 10, value=0, step=1, label="🎲🔃 🛠️💬 Prompt variant. Strength of variation of workflow prompt. 0 = no variance.")
|
|
|
with gr.Accordion("Help", open=False):
|
|
|
gr.Markdown(
|
|
|
"""
|
|
|
<font size="2">
|
|
|
Workflow assist, suggestions by redditor Woisek.
|
|
|
|
|
|
With 🛠️ Workflow mode, you turn off the automatic generation of new prompts on 'generate', and it will use the Workflow prompt field instead. So you can work and finetune any fun prompts without turning of the script.
|
|
|
|
|
|
You can use One Button Prompt wildcards in the workflow prompt. For example -outfit- .
|
|
|
|
|
|
With the Prompt Variant, you can let One Button Prompt dynamically create small variance in the workflow prompt. 0 means no effect.
|
|
|
|
|
|
Below here, you can generate a set of random prompts, and send them to the Workflow prompt field. The generation of the prompt uses the settings in the Main tab.
|
|
|
</font>
|
|
|
""")
|
|
|
with gr.Row(variant="compact"):
|
|
|
genprom = gr.Button("🔄💬 Generate me some prompts!")
|
|
|
with gr.Row(variant="compact"):
|
|
|
with gr.Column(scale=4, variant="compact"):
|
|
|
prompt1 = gr.Textbox(label="prompt 1")
|
|
|
with gr.Column(variant="compact"):
|
|
|
prompt1toworkflow = gr.Button("⬆️🛠️💬")
|
|
|
with gr.Row(variant="compact"):
|
|
|
with gr.Column(scale=4, variant="compact"):
|
|
|
prompt2 = gr.Textbox(label="prompt 2")
|
|
|
with gr.Column(variant="compact"):
|
|
|
prompt2toworkflow = gr.Button("⬆️🛠️💬")
|
|
|
with gr.Row(variant="compact"):
|
|
|
with gr.Column(scale=4, variant="compact"):
|
|
|
prompt3 = gr.Textbox(label="prompt 3")
|
|
|
with gr.Column(variant="compact"):
|
|
|
prompt3toworkflow = gr.Button("⬆️🛠️💬")
|
|
|
with gr.Row(variant="compact"):
|
|
|
with gr.Column(scale=4, variant="compact"):
|
|
|
prompt4 = gr.Textbox(label="prompt 4")
|
|
|
with gr.Column(variant="compact"):
|
|
|
prompt4toworkflow = gr.Button("⬆️🛠️💬")
|
|
|
with gr.Row(variant="compact"):
|
|
|
with gr.Column(scale=4, variant="compact"):
|
|
|
prompt5 = gr.Textbox(label="prompt 5")
|
|
|
with gr.Column(variant="compact"):
|
|
|
prompt5toworkflow = gr.Button("⬆️🛠️💬")
|
|
|
with gr.Tab("Advanced"):
|
|
|
with gr.Row(variant="compact"):
|
|
|
gr.Markdown("""
|
|
|
<font size="2">
|
|
|
✨Base model will try and generate prompts fitting the selected model.
|
|
|
|
|
|
SD1.5 --> Less natural language
|
|
|
|
|
|
SDXL --> More natural language (default)
|
|
|
|
|
|
Stable Cascade --> More natural language and no prompt weights
|
|
|
|
|
|
Anime Model --> Focussed on characters and tags, adds 1girl/1boy automatically.
|
|
|
|
|
|
⭐ Flufferizer
|
|
|
|
|
|
A simple and quick implementiation of Fooocus prompt magic
|
|
|
|
|
|
🦸♂️💬 Prompt enhancer
|
|
|
|
|
|
Choose for "superprompt-v1" to super prompt the prompts with roborovski superprompt-v1 model.
|
|
|
|
|
|
Please install requirements for superprompt before use.
|
|
|
|
|
|
</font>
|
|
|
"""
|
|
|
)
|
|
|
with gr.Row(variant="compact"):
|
|
|
base_model = gr.Dropdown(
|
|
|
basemodelslist, label="✨ Base model", value="SDXL")
|
|
|
with gr.Row(variant="compact"):
|
|
|
amountoffluff = gr.Dropdown(
|
|
|
amountofflufflist, label="⭐ Flufferizer", value="dynamic")
|
|
|
with gr.Row(variant="compact"):
|
|
|
promptenhancer = gr.Dropdown(
|
|
|
prompt_enhancers, label="🤓 Prompt enhancer", value="none")
|
|
|
with gr.Row(variant="compact"):
|
|
|
gr.Markdown("""
|
|
|
<font size="2">
|
|
|
|
|
|
Other options
|
|
|
|
|
|
---
|
|
|
</font>
|
|
|
"""
|
|
|
)
|
|
|
with gr.Row(variant="compact"):
|
|
|
with gr.Column(variant="compact"):
|
|
|
promptcompounderlevel = gr.Dropdown(
|
|
|
promptcompounder, label="🔂💬 Prompt compounder", value="1")
|
|
|
with gr.Row(variant="compact"):
|
|
|
with gr.Column(variant="compact"):
|
|
|
seperator = gr.Dropdown(
|
|
|
seperatorlist, label="🚧 Prompt seperator", value="comma")
|
|
|
with gr.Column(variant="compact"):
|
|
|
ANDtoggle = gr.Dropdown(
|
|
|
ANDtogglemode, label="🚧🔧 Prompt seperator mode", value="none")
|
|
|
with gr.Accordion("Help", open=False):
|
|
|
gr.Markdown(
|
|
|
"""
|
|
|
### 🔂💬 Prompt compounder
|
|
|
|
|
|
<font size="2">
|
|
|
Normally, it creates a single random prompt. With prompt compounder, it will generate multiple prompts and compound them together.
|
|
|
|
|
|
Keep at 1 for normal behavior.
|
|
|
Set to different values to compound that many prompts together. My suggestion is to try 2 first.
|
|
|
|
|
|
This was originally a bug in the first release when using multiple batches, now brought back as a feature.
|
|
|
Raised by redditor drone2222, to bring this back as a toggle, since it did create interesting results. So here it is.
|
|
|
|
|
|
You can toggle the separator mode. Standardly this is a comma, but you can choose an AND or a BREAK.
|
|
|
|
|
|
You can also choose the prompt seperator mode for use with Latent Couple extension
|
|
|
|
|
|
Example flow:
|
|
|
|
|
|
Set the Latent Couple extension to 2 area's (standard setting)
|
|
|
|
|
|
In the main tab, set the subject to humanoids
|
|
|
|
|
|
In the prefix prompt field then add for example: Art by artistname, 2 people
|
|
|
|
|
|
Set the 🔂💬 prompt compounder to: 2
|
|
|
|
|
|
Set the 🚧 Prompt seperator to: AND
|
|
|
|
|
|
Set the 🚧🔧 Prompt Seperator mode to: prefix AND prompt + suffix
|
|
|
|
|
|
"automatic" is entirely build around Latent Couple. It will pass artists and the amount of people/animals/objects to generate in the prompt automatically. Set the prompt compounder equal to the amount of areas defined in Laten Couple.
|
|
|
|
|
|
Example flow:
|
|
|
|
|
|
Set the Latent Couple extension to 2 area's (standard setting)
|
|
|
|
|
|
In the main tab, set the subject to humanoids
|
|
|
|
|
|
Leave the prompt field empty
|
|
|
|
|
|
Set the 🔂💬 prompt compounder to: 2
|
|
|
|
|
|
Set the 🚧 Prompt seperator to: AND
|
|
|
|
|
|
Set the 🚧🔧 Prompt Seperator mode to: automatic
|
|
|
|
|
|
|
|
|
</font>
|
|
|
|
|
|
"""
|
|
|
)
|
|
|
with gr.Tab("Negative prompt"):
|
|
|
gr.Markdown(
|
|
|
"""
|
|
|
### Negative prompt settings
|
|
|
</font>
|
|
|
"""
|
|
|
)
|
|
|
with gr.Column(variant="compact"):
|
|
|
with gr.Row(variant="compact"):
|
|
|
autonegativeprompt = gr.Checkbox(label="🤖🚫💬 Auto generate negative prompt", value=True)
|
|
|
autonegativepromptenhance = gr.Checkbox(label="📈🚫💬 Enable base enhancement prompt", value=False)
|
|
|
with gr.Row(variant="compact"):
|
|
|
autonegativepromptstrength = gr.Slider(0, 10, value="0", step=1, label="🎲🚫💬 Randomness of negative prompt (lower is more consistency)")
|
|
|
gr.Markdown(
|
|
|
"""
|
|
|
### Base negative prompt is added on
|
|
|
</font>
|
|
|
"""
|
|
|
)
|
|
|
with gr.Row():
|
|
|
negativeprompt = gr.Textbox(label="🚫💬 Base negative prompt",value="")
|
|
|
|
|
|
with gr.Tab("One Button Run and Upscale"):
|
|
|
with gr.Row(variant="compact"):
|
|
|
gr.Markdown(
|
|
|
"""
|
|
|
### TXT2IMG
|
|
|
<font size="2">
|
|
|
Start WebUi with option --api for this to work. This is not needed for Vlad SD Next.
|
|
|
|
|
|
Note: This part is entirely optional and you can use the normal generate button.
|
|
|
|
|
|
This part is only intended for running an upscaling at the same time.
|
|
|
</font>
|
|
|
"""
|
|
|
)
|
|
|
with gr.Row(variant="compact"):
|
|
|
with gr.Column(variant="compact"):
|
|
|
startmain = gr.Button("Start generating and upscaling!")
|
|
|
interrupt = gr.Button("Interrupt current")
|
|
|
automatedoutputsfolderbutton = gr.Button(folder_symbol)
|
|
|
with gr.Column(variant="compact"):
|
|
|
apiurl = gr.Textbox(label="URL", value="http://127.0.0.1:7860")
|
|
|
onlyupscale = gr.Checkbox(label="Don't generate, only upscale", value=False)
|
|
|
increasestability = gr.Checkbox(label="Increase stability", value=False)
|
|
|
with gr.Row(variant="compact"):
|
|
|
with gr.Accordion("help", open=False):
|
|
|
gr.Markdown(
|
|
|
"""
|
|
|
<font size="2">
|
|
|
Only upscale will not use txt2img to generate an image.
|
|
|
|
|
|
Instead it will pick up all files in the \\upscale_me\\ folder and upscale them with below settings.
|
|
|
|
|
|
Increase stability: If you get NaN's or memory issues, turn this on. It will unload and load the base checkpoint.
|
|
|
</font>
|
|
|
"""
|
|
|
)
|
|
|
with gr.Row(variant="compact"):
|
|
|
with gr.Column(variant="compact"):
|
|
|
|
|
|
amountofimages = gr.Slider(1, 50, value="20", step=1, label="Amount of images to generate")
|
|
|
size = gr.Dropdown(
|
|
|
sizelist, label="Size to generate", value="all")
|
|
|
basesize = gr.Dropdown(
|
|
|
basesizelist, label="base size", value="512")
|
|
|
with gr.Row(variant="compact"):
|
|
|
samplingsteps = gr.Slider(1, 100, value="20", step=1, label="Sampling steps")
|
|
|
cfg = gr.Slider(1,20, value="6.0", step=0.1, label="CFG")
|
|
|
with gr.Row(variant="compact"):
|
|
|
hiresfix = gr.Checkbox(label="hires. fix", value=True)
|
|
|
hiressteps = gr.Slider(0, 100, value = "0", step=1, label="Hires steps")
|
|
|
hiresscale = gr.Slider(1, 4, value = "2", step=0.05, label="Scale")
|
|
|
denoisestrength = gr.Slider(0, 1, value="0.60", step=0.01, label="Denoise strength")
|
|
|
with gr.Column(variant="compact"):
|
|
|
|
|
|
model = gr.Dropdown(
|
|
|
modellist, label="model to use", value="currently selected model")
|
|
|
with gr.Column(variant="compact"):
|
|
|
samplingmethod = gr.Dropdown(
|
|
|
samplerlist, label= "Sampler", value="all")
|
|
|
upscaler = gr.Dropdown(
|
|
|
upscalerlist, label="hires upscaler", value="all")
|
|
|
with gr.Row(variant="compact"):
|
|
|
gr.Markdown(
|
|
|
"""
|
|
|
### Quality Gate
|
|
|
""")
|
|
|
with gr.Row(variant="compact"):
|
|
|
with gr.Accordion("quality gate help", open=False):
|
|
|
gr.Markdown(
|
|
|
"""
|
|
|
<font size="2">
|
|
|
Uses aesthetic image scorer extension to check the quality of the image.
|
|
|
|
|
|
Once turned on, it will retry for n amount of times to get an image with the quality score. If not, it will take the best image so far and continue or set it to gated to only take matching or higher quality images.
|
|
|
|
|
|
You can move Hiresfix to be applied afterwards. You can opt to keep all generated images.
|
|
|
|
|
|
Idea and inspiration by xKean. Additional improvements suggested by pto2k.
|
|
|
</font>
|
|
|
"""
|
|
|
)
|
|
|
with gr.Row(variant="compact"):
|
|
|
qualitygate = gr.Checkbox(label="Quality Gate", value=False)
|
|
|
quality = gr.Slider(1, 10, value = "7.2", step=0.1, label="Quality", visible = False)
|
|
|
runs = gr.Slider(1, 50, value = "5", step=1, label="Amount of tries", visible = False)
|
|
|
with gr.Row(variant="compact"):
|
|
|
qualityhiresfix = gr.Checkbox(label="Move Hires fix afterwards", value=False, visible = False)
|
|
|
qualitymode = gr.Dropdown(
|
|
|
qualitymodelist, label= "Mode of operation", value="highest", visible = False)
|
|
|
qualitykeep = gr.Dropdown(
|
|
|
qualitykeeplist, label= "Images", value="keep used", visible = False)
|
|
|
with gr.Row(variant="compact"):
|
|
|
gr.Markdown(
|
|
|
"""
|
|
|
### IMG2IMG upscale
|
|
|
"""
|
|
|
)
|
|
|
with gr.Row(variant="compact"):
|
|
|
img2imgactivate = gr.Checkbox(label="Upscale image with IMG2IMG", value=True)
|
|
|
with gr.Row(variant="compact"):
|
|
|
with gr.Column(variant="compact"):
|
|
|
img2imgbatch = gr.Slider(1, 5, value="1", step=1, label="Amount times to repeat upscaling with IMG2IMG (loopback)")
|
|
|
img2imgsamplingsteps = gr.Slider(1, 100, value="20", step=1, label="img2img Sampling steps")
|
|
|
img2imgcfg = gr.Slider(1,20, value="6", step=0.1, label="img2img CFG")
|
|
|
img2imgdenoisestrength = gr.Slider(0, 1, value="0.30", step=0.01, label="img2img denoise strength")
|
|
|
img2imgdenoisestrengthmod = gr.Slider(-1,1, value = "-0.05", step=0.01, label="adjust denoise each img2img batch")
|
|
|
with gr.Column(variant="compact"):
|
|
|
img2imgmodel = gr.Dropdown(
|
|
|
modellist, label="img2img model to use", value="currently selected model")
|
|
|
img2imgsamplingmethod = gr.Dropdown(
|
|
|
img2imgsamplerlist, label= "img2img sampler", value="all")
|
|
|
img2imgupscaler = gr.Dropdown(
|
|
|
img2imgupscalerlist, label="img2img upscaler", value="all")
|
|
|
with gr.Row(variant="compact"):
|
|
|
img2imgscale = gr.Slider(1, 4, value="2", step=0.05, label="img2img scale")
|
|
|
img2imgpadding = gr.Slider(32, 256, value="64", step=12, label="img2img padding")
|
|
|
with gr.Row(variant="compact"):
|
|
|
ultimatesdupscale = gr.Checkbox(label="Use Ultimate SD Upscale script instead", value=False)
|
|
|
gr.Markdown(
|
|
|
"""
|
|
|
<font size="2">
|
|
|
This requires the Ultimate SD Upscale extension, install this if you haven't
|
|
|
</font>
|
|
|
"""
|
|
|
)
|
|
|
with gr.Row(variant="compact"):
|
|
|
with gr.Column(scale = 1):
|
|
|
|
|
|
|
|
|
usdutilewidth = gr.Slider(0, 2048, value="512", step=12, label="tile width", visible = False)
|
|
|
usdutileheight = gr.Slider(0, 2048, value="0", step=12, label="tile height", visible = False)
|
|
|
usdumaskblur = gr.Slider(0, 64, value="8", step=1, label="Mask blur", visible = False)
|
|
|
usduredraw = gr.Dropdown(
|
|
|
redraw_modes, label="Type", value="Linear", visible = False)
|
|
|
with gr.Column(scale = 1):
|
|
|
usduSeamsfix = gr.Dropdown(
|
|
|
seams_fix_types, label="Seams fix", value="None", visible = False)
|
|
|
usdusdenoise = gr.Slider(0, 1, value="0.35", step=0.01, label="Seams denoise strenght", visible = False)
|
|
|
usduswidth = gr.Slider(0, 128, value="64", step=12, label="Seams Width", visible = False)
|
|
|
usduspadding = gr.Slider(0, 128, value="32", step=12, label="Seams padding", visible = False)
|
|
|
usdusmaskblur = gr.Slider(0, 64, value="8", step=1, label="Seams Mask blur (offset pass only)", visible = False)
|
|
|
with gr.Row(variant="compact"):
|
|
|
with gr.Column(scale = 1):
|
|
|
controlnetenabled = gr.Checkbox(label="Enable controlnet tile resample", value=False)
|
|
|
controlnetblockymode = gr.Checkbox(label="also enable wierd blocky upscale mode", value=False)
|
|
|
with gr.Column(scale = 1):
|
|
|
controlnetmodel = gr.Textbox(label="Controlnet tile model name", value = "control_v11f1e_sd15_tile [a371b31b]")
|
|
|
with gr.Row(variant="compact"):
|
|
|
gr.Markdown(
|
|
|
"""
|
|
|
<font size="2">
|
|
|
This requires Controlnet 1.1 extension and the tile resample model, install this if you haven't
|
|
|
In settings for Controlnet, enable "Allow other script to control this extension"
|
|
|
|
|
|
Don't use wierd blocky upscale mode. Or maybe do?
|
|
|
</font>
|
|
|
"""
|
|
|
)
|
|
|
with gr.Row(variant="compact"):
|
|
|
with gr.Column(scale = 1):
|
|
|
enableextraupscale = gr.Checkbox(label="Enable upscale with extras", value=False)
|
|
|
with gr.Row(variant="compact"):
|
|
|
with gr.Column(scale = 1):
|
|
|
extrasresize = gr.Slider(0, 8, value="2", step=0.05, label="Upscale resize", visible = False)
|
|
|
extrasupscaler1 = gr.Dropdown(
|
|
|
img2imgupscalerlist, label="upscaler 1", value="all", visible = False)
|
|
|
extrasupscaler2 = gr.Dropdown(
|
|
|
img2imgupscalerlist, label="upscaler 2", value="all", visible = False)
|
|
|
extrasupscaler2visiblity = gr.Slider(0, 1, value="0.5", step=0.05, label="Upscaler 2 vis.", visible = False)
|
|
|
with gr.Column(scale = 1):
|
|
|
extrasupscaler2gfpgan = gr.Slider(0, 1, value="0", step=0.05, label="GFPGAN vis.", visible = False)
|
|
|
extrasupscaler2codeformer = gr.Slider(0, 1, value="0.15", step=0.05, label="CodeFormer vis.", visible = False)
|
|
|
extrasupscaler2codeformerweight = gr.Slider(0, 1, value="0.1", step=0.05, label="CodeFormer weight", visible = False)
|
|
|
|
|
|
|
|
|
genprom.click(gen_prompt, inputs=[insanitylevel,subject, artist, imagetype, antistring,prefixprompt, suffixprompt,promptcompounderlevel, seperator, givensubject,smartsubject,giventypeofimage,imagemodechance, chosengender, chosensubjectsubtypeobject, chosensubjectsubtypehumanoid, chosensubjectsubtypeconcept, givenoutfit, base_model, OBP_preset, amountoffluff, promptenhancer, presetprefix, presetsuffix], outputs=[prompt1, prompt2, prompt3,prompt4,prompt5])
|
|
|
|
|
|
prompt1toworkflow.click(prompttoworkflowprompt, inputs=prompt1, outputs=workprompt)
|
|
|
prompt2toworkflow.click(prompttoworkflowprompt, inputs=prompt2, outputs=workprompt)
|
|
|
prompt3toworkflow.click(prompttoworkflowprompt, inputs=prompt3, outputs=workprompt)
|
|
|
prompt4toworkflow.click(prompttoworkflowprompt, inputs=prompt4, outputs=workprompt)
|
|
|
prompt5toworkflow.click(prompttoworkflowprompt, inputs=prompt5, outputs=workprompt)
|
|
|
|
|
|
startmain.click(generateimages, inputs=[amountofimages,size,model,samplingsteps,cfg,hiresfix,hiressteps,denoisestrength,samplingmethod, upscaler,hiresscale, apiurl, qualitygate, quality, runs,insanitylevel,subject, artist, imagetype, silentmode, workprompt, antistring, prefixprompt, suffixprompt,negativeprompt,promptcompounderlevel, seperator, img2imgbatch, img2imgsamplingsteps, img2imgcfg, img2imgsamplingmethod, img2imgupscaler, img2imgmodel,img2imgactivate, img2imgscale, img2imgpadding,img2imgdenoisestrength,ultimatesdupscale,usdutilewidth, usdutileheight, usdumaskblur, usduredraw, usduSeamsfix, usdusdenoise, usduswidth, usduspadding, usdusmaskblur, controlnetenabled, controlnetmodel,img2imgdenoisestrengthmod,enableextraupscale,controlnetblockymode,extrasupscaler1,extrasupscaler2,extrasupscaler2visiblity,extrasupscaler2gfpgan,extrasupscaler2codeformer,extrasupscaler2codeformerweight,extrasresize,onlyupscale,givensubject,smartsubject,giventypeofimage,imagemodechance, chosengender, chosensubjectsubtypeobject, chosensubjectsubtypehumanoid, chosensubjectsubtypeconcept, increasestability, qualityhiresfix, qualitymode, qualitykeep, basesize, promptvariantinsanitylevel, givenoutfit, autonegativeprompt, autonegativepromptstrength, autonegativepromptenhance, base_model, OBP_preset, amountoffluff, promptenhancer, presetprefix, presetsuffix])
|
|
|
interrupt.click(tryinterrupt, inputs=[apiurl])
|
|
|
|
|
|
automatedoutputsfolderbutton.click(openfolder)
|
|
|
|
|
|
obp_outputs = [
|
|
|
obp_preset_name,
|
|
|
obp_preset_save,
|
|
|
insanitylevel,
|
|
|
subject,
|
|
|
artist,
|
|
|
chosensubjectsubtypeobject,
|
|
|
chosensubjectsubtypehumanoid,
|
|
|
chosensubjectsubtypeconcept,
|
|
|
chosengender,
|
|
|
imagetype,
|
|
|
imagemodechance,
|
|
|
givensubject,
|
|
|
smartsubject,
|
|
|
givenoutfit,
|
|
|
prefixprompt,
|
|
|
suffixprompt,
|
|
|
giventypeofimage,
|
|
|
antistring,
|
|
|
]
|
|
|
|
|
|
|
|
|
def act_obp_preset_save(
|
|
|
obp_preset_name,
|
|
|
obp_preset_save,
|
|
|
insanitylevel,
|
|
|
subject,
|
|
|
artist,
|
|
|
chosensubjectsubtypeobject,
|
|
|
chosensubjectsubtypehumanoid,
|
|
|
chosensubjectsubtypeconcept,
|
|
|
chosengender,
|
|
|
imagetype,
|
|
|
imagemodechance,
|
|
|
givensubject,
|
|
|
smartsubject,
|
|
|
givenoutfit,
|
|
|
prefixprompt,
|
|
|
suffixprompt,
|
|
|
giventypeofimage,
|
|
|
antistring,
|
|
|
):
|
|
|
if obp_preset_name != "":
|
|
|
obp_options = OBPresets.load_obp_presets()
|
|
|
opts = {
|
|
|
"insanitylevel": insanitylevel,
|
|
|
"subject": subject,
|
|
|
"artist": artist,
|
|
|
"chosensubjectsubtypeobject": chosensubjectsubtypeobject,
|
|
|
"chosensubjectsubtypehumanoid": chosensubjectsubtypehumanoid,
|
|
|
"chosensubjectsubtypeconcept": chosensubjectsubtypeconcept,
|
|
|
"chosengender": chosengender,
|
|
|
"imagetype": imagetype,
|
|
|
"imagemodechance": imagemodechance,
|
|
|
"givensubject": givensubject,
|
|
|
"smartsubject": smartsubject,
|
|
|
"givenoutfit": givenoutfit,
|
|
|
"prefixprompt": prefixprompt,
|
|
|
"suffixprompt": suffixprompt,
|
|
|
"giventypeofimage": giventypeofimage,
|
|
|
"antistring": antistring
|
|
|
}
|
|
|
obp_options[obp_preset_name] = opts
|
|
|
OBPresets.save_obp_preset(obp_options)
|
|
|
choices = [OBPresets.RANDOM_PRESET_OBP] + list(obp_options.keys()) + [OBPresets.CUSTOM_OBP]
|
|
|
return gr.update(choices=choices, value=obp_preset_name)
|
|
|
else:
|
|
|
return gr.update()
|
|
|
|
|
|
obp_preset_save.click(act_obp_preset_save,
|
|
|
inputs=obp_outputs,
|
|
|
outputs=[OBP_preset],
|
|
|
)
|
|
|
|
|
|
|
|
|
def obppreset_changed(selection):
|
|
|
if selection == OBPresets.CUSTOM_OBP:
|
|
|
return (
|
|
|
[obp_preset_name.update(value="", visible=True)]
|
|
|
+ [maingroup.update(visible=True)]
|
|
|
+ [presetgroup.update(visible=False)]
|
|
|
+ [presetprefix.update(value="")]
|
|
|
+ [presetsuffix.update(value="")]
|
|
|
)
|
|
|
|
|
|
else:
|
|
|
return (
|
|
|
[obp_preset_name.update(visible=False)]
|
|
|
+ [maingroup.update(visible=False)]
|
|
|
+ [presetgroup.update(visible=True)]
|
|
|
+ [presetprefix.update(visible=True)]
|
|
|
+ [presetsuffix.update(visible=True)]
|
|
|
)
|
|
|
OBP_preset.change(obppreset_changed,
|
|
|
inputs=[OBP_preset],
|
|
|
outputs=[obp_preset_name] + [maingroup] + [presetgroup] + [presetprefix] + [presetsuffix]
|
|
|
)
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
def OBPPreset_changed_update_custom(selection):
|
|
|
|
|
|
if selection == OBPresets.CUSTOM_OBP:
|
|
|
return [gr.update()] * 16
|
|
|
|
|
|
|
|
|
if selection == OBPresets.RANDOM_PRESET_OBP:
|
|
|
selected_opb_preset = OBPresets.get_obp_preset("Standard")
|
|
|
else:
|
|
|
selected_opb_preset = OBPresets.get_obp_preset(selection)
|
|
|
return [
|
|
|
insanitylevel.update(value=selected_opb_preset["insanitylevel"]),
|
|
|
subject.update(value=selected_opb_preset["subject"]),
|
|
|
artist.update(value=selected_opb_preset["artist"]),
|
|
|
chosensubjectsubtypeobject.update(value=selected_opb_preset["chosensubjectsubtypeobject"]),
|
|
|
chosensubjectsubtypehumanoid.update(value=selected_opb_preset["chosensubjectsubtypehumanoid"]),
|
|
|
chosensubjectsubtypeconcept.update(value=selected_opb_preset["chosensubjectsubtypeconcept"]),
|
|
|
chosengender.update(value=selected_opb_preset["chosengender"]),
|
|
|
imagetype.update(value=selected_opb_preset["imagetype"]),
|
|
|
imagemodechance.update(value=selected_opb_preset["imagemodechance"]),
|
|
|
givensubject.update(value=selected_opb_preset["givensubject"]),
|
|
|
smartsubject.update(value=selected_opb_preset["smartsubject"]),
|
|
|
givenoutfit.update(value=selected_opb_preset["givenoutfit"]),
|
|
|
prefixprompt.update(value=selected_opb_preset["prefixprompt"]),
|
|
|
suffixprompt.update(value=selected_opb_preset["suffixprompt"]),
|
|
|
giventypeofimage.update(value=selected_opb_preset["giventypeofimage"]),
|
|
|
antistring.update(value=selected_opb_preset["antistring"]),
|
|
|
]
|
|
|
OBP_preset.change(OBPPreset_changed_update_custom,
|
|
|
inputs=[OBP_preset],
|
|
|
outputs=[insanitylevel] +
|
|
|
[subject] +
|
|
|
[artist] +
|
|
|
[chosensubjectsubtypeobject] +
|
|
|
[chosensubjectsubtypehumanoid] +
|
|
|
[chosensubjectsubtypeconcept] +
|
|
|
[chosengender] +
|
|
|
[imagetype] +
|
|
|
[imagemodechance] +
|
|
|
[givensubject] +
|
|
|
[smartsubject] +
|
|
|
[givenoutfit] +
|
|
|
[prefixprompt] +
|
|
|
[suffixprompt] +
|
|
|
[giventypeofimage] +
|
|
|
[antistring],
|
|
|
)
|
|
|
|
|
|
|
|
|
def subjectsvalue(subject):
|
|
|
enable=("human" in subject)
|
|
|
return {
|
|
|
chosengender: gr.update(visible=enable),
|
|
|
}
|
|
|
subject.change(
|
|
|
subjectsvalue,
|
|
|
[subject],
|
|
|
[chosengender]
|
|
|
)
|
|
|
|
|
|
|
|
|
def subjectsvalueforsubtypeobject(subject):
|
|
|
enable=(subject=="object")
|
|
|
return {
|
|
|
chosensubjectsubtypeobject: gr.update(visible=enable),
|
|
|
}
|
|
|
subject.change(
|
|
|
subjectsvalueforsubtypeobject,
|
|
|
[subject],
|
|
|
[chosensubjectsubtypeobject]
|
|
|
)
|
|
|
|
|
|
|
|
|
def subjectsvalueforsubtypeobject(subject):
|
|
|
enable=(subject=="humanoid")
|
|
|
return {
|
|
|
chosensubjectsubtypehumanoid: gr.update(visible=enable),
|
|
|
}
|
|
|
subject.change(
|
|
|
subjectsvalueforsubtypeobject,
|
|
|
[subject],
|
|
|
[chosensubjectsubtypehumanoid]
|
|
|
)
|
|
|
|
|
|
|
|
|
def subjectsvalueforsubtypeconcept(subject):
|
|
|
enable=(subject=="concept")
|
|
|
return {
|
|
|
chosensubjectsubtypeconcept: gr.update(visible=enable),
|
|
|
}
|
|
|
subject.change(
|
|
|
subjectsvalueforsubtypeconcept,
|
|
|
[subject],
|
|
|
[chosensubjectsubtypeconcept]
|
|
|
)
|
|
|
|
|
|
|
|
|
|
|
|
def onlyupscalevalues(onlyupscale):
|
|
|
onlyupscale = not onlyupscale
|
|
|
return {
|
|
|
amountofimages: gr.update(visible=onlyupscale),
|
|
|
size: gr.update(visible=onlyupscale),
|
|
|
samplingsteps: gr.update(visible=onlyupscale),
|
|
|
cfg: gr.update(visible=onlyupscale),
|
|
|
|
|
|
hiresfix: gr.update(visible=onlyupscale),
|
|
|
hiressteps: gr.update(visible=onlyupscale),
|
|
|
hiresscale: gr.update(visible=onlyupscale),
|
|
|
denoisestrength: gr.update(visible=onlyupscale),
|
|
|
upscaler: gr.update(visible=onlyupscale),
|
|
|
|
|
|
model: gr.update(visible=onlyupscale),
|
|
|
samplingmethod: gr.update(visible=onlyupscale),
|
|
|
upscaler: gr.update(visible=onlyupscale),
|
|
|
|
|
|
qualitygate: gr.update(visible=onlyupscale),
|
|
|
quality: gr.update(visible=onlyupscale),
|
|
|
runs: gr.update(visible=onlyupscale),
|
|
|
qualityhiresfix: gr.update(visible=onlyupscale),
|
|
|
qualitymode: gr.update(visible=onlyupscale),
|
|
|
qualitykeep: gr.update(visible=onlyupscale)
|
|
|
|
|
|
|
|
|
}
|
|
|
|
|
|
onlyupscale.change(
|
|
|
onlyupscalevalues,
|
|
|
[onlyupscale],
|
|
|
[amountofimages,size,samplingsteps,cfg,hiresfix,hiressteps,hiresscale,denoisestrength,upscaler,model,samplingmethod,upscaler,qualitygate,quality,runs,qualityhiresfix,qualitymode,qualitykeep]
|
|
|
)
|
|
|
|
|
|
|
|
|
|
|
|
def hireschangevalues(hiresfix):
|
|
|
return {
|
|
|
hiressteps: gr.update(visible=hiresfix),
|
|
|
hiresscale: gr.update(visible=hiresfix),
|
|
|
denoisestrength: gr.update(visible=hiresfix),
|
|
|
upscaler: gr.update(visible=hiresfix)
|
|
|
}
|
|
|
|
|
|
hiresfix.change(
|
|
|
hireschangevalues,
|
|
|
[hiresfix],
|
|
|
[hiressteps,hiresscale,denoisestrength,upscaler]
|
|
|
)
|
|
|
|
|
|
|
|
|
def qgatechangevalues(qualitygate):
|
|
|
return {
|
|
|
quality: gr.update(visible=qualitygate),
|
|
|
runs: gr.update(visible=qualitygate),
|
|
|
qualityhiresfix: gr.update(visible=qualitygate),
|
|
|
qualitymode: gr.update(visible=qualitygate),
|
|
|
qualitykeep: gr.update(visible=qualitygate)
|
|
|
}
|
|
|
|
|
|
qualitygate.change(
|
|
|
qgatechangevalues,
|
|
|
[qualitygate],
|
|
|
[quality,runs,qualityhiresfix,qualitymode,qualitykeep]
|
|
|
)
|
|
|
|
|
|
|
|
|
def ultimatesdupscalechangevalues(ultimatesdupscale):
|
|
|
return {
|
|
|
usdutilewidth: gr.update(visible=ultimatesdupscale),
|
|
|
usdutileheight: gr.update(visible=ultimatesdupscale),
|
|
|
usdumaskblur: gr.update(visible=ultimatesdupscale),
|
|
|
usduredraw: gr.update(visible=ultimatesdupscale),
|
|
|
|
|
|
usduSeamsfix: gr.update(visible=ultimatesdupscale),
|
|
|
usdusdenoise: gr.update(visible=ultimatesdupscale),
|
|
|
usduswidth: gr.update(visible=ultimatesdupscale),
|
|
|
usduspadding: gr.update(visible=ultimatesdupscale),
|
|
|
usdusmaskblur: gr.update(visible=ultimatesdupscale)
|
|
|
}
|
|
|
|
|
|
ultimatesdupscale.change(
|
|
|
ultimatesdupscalechangevalues,
|
|
|
[ultimatesdupscale],
|
|
|
[usdutilewidth,usdutileheight,usdumaskblur,usduredraw,usduSeamsfix,usdusdenoise,usduswidth,usduspadding,usdusmaskblur]
|
|
|
)
|
|
|
|
|
|
|
|
|
def enableextraupscalechangevalues(enableextraupscale):
|
|
|
return {
|
|
|
extrasupscaler1: gr.update(visible=enableextraupscale),
|
|
|
extrasupscaler2: gr.update(visible=enableextraupscale),
|
|
|
extrasupscaler2visiblity: gr.update(visible=enableextraupscale),
|
|
|
extrasresize: gr.update(visible=enableextraupscale),
|
|
|
|
|
|
extrasupscaler2gfpgan: gr.update(visible=enableextraupscale),
|
|
|
extrasupscaler2codeformer: gr.update(visible=enableextraupscale),
|
|
|
extrasupscaler2codeformerweight: gr.update(visible=enableextraupscale)
|
|
|
}
|
|
|
|
|
|
enableextraupscale.change(
|
|
|
enableextraupscalechangevalues,
|
|
|
[enableextraupscale],
|
|
|
[extrasupscaler1,extrasupscaler2,extrasupscaler2visiblity,extrasresize, extrasupscaler2gfpgan,extrasupscaler2codeformer,extrasupscaler2codeformerweight]
|
|
|
)
|
|
|
|
|
|
|
|
|
|
|
|
return [insanitylevel,subject, artist, imagetype, prefixprompt,suffixprompt,negativeprompt, promptcompounderlevel, ANDtoggle, silentmode, workprompt, antistring, seperator, givensubject, smartsubject, giventypeofimage, imagemodechance, chosengender, chosensubjectsubtypeobject, chosensubjectsubtypehumanoid, chosensubjectsubtypeconcept, promptvariantinsanitylevel, givenoutfit, autonegativeprompt, autonegativepromptstrength, autonegativepromptenhance, base_model, OBP_preset, amountoffluff, promptenhancer, presetprefix, presetsuffix]
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
def run(self, p, insanitylevel, subject, artist, imagetype, prefixprompt,suffixprompt,negativeprompt, promptcompounderlevel, ANDtoggle, silentmode, workprompt, antistring,seperator, givensubject, smartsubject, giventypeofimage, imagemodechance, chosengender, chosensubjectsubtypeobject, chosensubjectsubtypehumanoid, chosensubjectsubtypeconcept, promptvariantinsanitylevel, givenoutfit, autonegativeprompt, autonegativepromptstrength, autonegativepromptenhance, base_model, OBP_preset, amountoffluff, promptenhancer, presetprefix, presetsuffix):
|
|
|
|
|
|
images = []
|
|
|
infotexts = []
|
|
|
all_seeds = []
|
|
|
all_prompts = []
|
|
|
|
|
|
batches = p.n_iter
|
|
|
initialbatchsize = p.batch_size
|
|
|
batchsize = p.batch_size
|
|
|
p.n_iter = 1
|
|
|
p.batch_size = 1
|
|
|
|
|
|
initialseed = p.seed
|
|
|
if p.seed == -1:
|
|
|
p.seed = int(random.randrange(4294967294))
|
|
|
|
|
|
if(silentmode and workprompt != ""):
|
|
|
print("Workflow mode turned on, not generating a prompt. Using workflow prompt.")
|
|
|
elif(silentmode):
|
|
|
print("Warning, workflow mode is turned on, but no workprompt has been given.")
|
|
|
elif p.prompt != "" or p.negative_prompt != "":
|
|
|
print("Please note that existing prompt and negative prompt fields are (no longer) used")
|
|
|
|
|
|
if(ANDtoggle == "automatic" and artist == "none"):
|
|
|
print("Automatic and artist mode set to none, don't work together well. Ignoring this setting!")
|
|
|
artist = "all"
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
state.job_count = batches
|
|
|
|
|
|
for i in range(batches):
|
|
|
|
|
|
if(silentmode == False):
|
|
|
|
|
|
print("Starting generating the prompt")
|
|
|
preppedprompt = ""
|
|
|
|
|
|
artistcopy = artist
|
|
|
prefixpromptcopy = prefixprompt
|
|
|
|
|
|
if(ANDtoggle == "automatic"):
|
|
|
if(artist != "none"):
|
|
|
preppedprompt += build_dynamic_prompt(insanitylevel,subject,artist, imagetype, True, antistring, base_model=base_model)
|
|
|
if(subject == "humanoid"):
|
|
|
preppedprompt += ", " + promptcompounderlevel + " people"
|
|
|
if(subject == "landscape"):
|
|
|
preppedprompt += ", landscape"
|
|
|
if(subject == "animal"):
|
|
|
preppedprompt += ", " + promptcompounderlevel + " animals"
|
|
|
if(subject == "object"):
|
|
|
preppedprompt += ", " + promptcompounderlevel + " objects"
|
|
|
|
|
|
|
|
|
artist = "none"
|
|
|
|
|
|
|
|
|
if(ANDtoggle != "none" and ANDtoggle != "automatic"):
|
|
|
preppedprompt += prefixprompt
|
|
|
|
|
|
if(ANDtoggle != "none"):
|
|
|
if(ANDtoggle!="prefix + prefix + prompt + suffix"):
|
|
|
prefixprompt = ""
|
|
|
if(seperator == "comma"):
|
|
|
preppedprompt += " \n , "
|
|
|
else:
|
|
|
preppedprompt += " \n " + seperator + " "
|
|
|
|
|
|
|
|
|
|
|
|
base_prompt = build_dynamic_prompt(insanitylevel,subject,artist, imagetype, False, antistring, prefixprompt, suffixprompt,promptcompounderlevel, seperator,givensubject,smartsubject,giventypeofimage,imagemodechance,chosengender, chosensubjectsubtypeobject, chosensubjectsubtypehumanoid, chosensubjectsubtypeconcept,True,False,-1,givenoutfit, False, base_model, OBP_preset, promptenhancer, "", "", presetprefix, presetsuffix)
|
|
|
fluffed_prompt = flufferizer(prompt=base_prompt, amountoffluff=amountoffluff)
|
|
|
preppedprompt += fluffed_prompt
|
|
|
|
|
|
|
|
|
artist = artistcopy
|
|
|
prefixprompt = prefixpromptcopy
|
|
|
|
|
|
|
|
|
p.prompt = preppedprompt
|
|
|
p.negative_prompt = negativeprompt
|
|
|
|
|
|
if(silentmode == True):
|
|
|
base_prompt = createpromptvariant(workprompt,promptvariantinsanitylevel)
|
|
|
p.prompt = base_prompt
|
|
|
|
|
|
|
|
|
|
|
|
print(" ")
|
|
|
print("Full prompt to be processed:")
|
|
|
print(" ")
|
|
|
print(p.prompt)
|
|
|
|
|
|
if(autonegativeprompt):
|
|
|
p.negative_prompt = build_dynamic_negative(positive_prompt=base_prompt, insanitylevel=autonegativepromptstrength,enhance=autonegativepromptenhance, existing_negative_prompt=p.negative_prompt, base_model=base_model)
|
|
|
|
|
|
|
|
|
promptlist = []
|
|
|
if(batchsize>1):
|
|
|
|
|
|
|
|
|
for i in range(batchsize):
|
|
|
promptlist.append(p.prompt)
|
|
|
|
|
|
p.prompt = promptlist
|
|
|
p.batch_size = batchsize
|
|
|
p.hr_prompt = promptlist
|
|
|
else:
|
|
|
p.batch_size = batchsize
|
|
|
p.hr_prompt = p.prompt
|
|
|
|
|
|
processed = process_images(p)
|
|
|
images += processed.images
|
|
|
infotexts += processed.infotexts
|
|
|
|
|
|
|
|
|
all_seeds.append(processed.seed)
|
|
|
all_prompts.append(processed.prompt)
|
|
|
|
|
|
|
|
|
all_seeds += processed.all_seeds
|
|
|
all_prompts += processed.all_prompts
|
|
|
|
|
|
state.job = f"{state.job_no} out of {state.job_count}"
|
|
|
|
|
|
|
|
|
if initialseed == -1:
|
|
|
p.seed += batchsize
|
|
|
|
|
|
|
|
|
p.n_iter = 0
|
|
|
p.batch_size = 0
|
|
|
return Processed(p=p, images_list=images, info=infotexts[0], infotexts=infotexts, all_seeds=all_seeds, all_prompts=all_prompts) |
