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import sys
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import argparse
import json
import os
import gradio as gr
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import tqdm
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import datetime
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import modules . artists
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from modules . paths import script_path , sd_path
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from modules . devices import get_optimal_device
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import modules . styles
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import modules . interrogate
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import modules . memmon
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import modules . sd_models
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sd_model_file = os . path . join ( script_path , ' model.ckpt ' )
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default_sd_model_file = sd_model_file
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parser = argparse . ArgumentParser ( )
parser . add_argument ( " --config " , type = str , default = os . path . join ( sd_path , " configs/stable-diffusion/v1-inference.yaml " ) , help = " path to config which constructs model " , )
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parser . add_argument ( " --ckpt " , type = str , default = sd_model_file , help = " path to checkpoint of stable diffusion model; this checkpoint will be added to the list of checkpoints and loaded by default if you don ' t have a checkpoint selected in settings " , )
parser . add_argument ( " --ckpt-dir " , type = str , default = os . path . join ( script_path , ' models ' ) , help = " path to directory with stable diffusion checkpoints " , )
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parser . add_argument ( " --gfpgan-dir " , type = str , help = " GFPGAN directory " , default = ( ' ./src/gfpgan ' if os . path . exists ( ' ./src/gfpgan ' ) else ' ./GFPGAN ' ) )
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parser . add_argument ( " --gfpgan-model " , type = str , help = " GFPGAN model file name " , default = None )
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parser . add_argument ( " --no-half " , action = ' store_true ' , help = " do not switch the model to 16-bit floats " )
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parser . add_argument ( " --no-progressbar-hiding " , action = ' store_true ' , help = " do not hide progressbar in gradio UI (we hide it because it slows down ML if you have hardware acceleration in browser) " )
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parser . add_argument ( " --max-batch-count " , type = int , default = 16 , help = " maximum batch count value for the UI " )
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parser . add_argument ( " --embeddings-dir " , type = str , default = os . path . join ( script_path , ' embeddings ' ) , help = " embeddings directory for textual inversion (default: embeddings) " )
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parser . add_argument ( " --allow-code " , action = ' store_true ' , help = " allow custom script execution from webui " )
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parser . add_argument ( " --medvram " , action = ' store_true ' , help = " enable stable diffusion model optimizations for sacrificing a little speed for low VRM usage " )
parser . add_argument ( " --lowvram " , action = ' store_true ' , help = " enable stable diffusion model optimizations for sacrificing a lot of speed for very low VRM usage " )
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parser . add_argument ( " --always-batch-cond-uncond " , action = ' store_true ' , help = " disables cond/uncond batching that is enabled to save memory with --medvram or --lowvram " )
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parser . add_argument ( " --unload-gfpgan " , action = ' store_true ' , help = " does not do anything. " )
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parser . add_argument ( " --precision " , type = str , help = " evaluate at this precision " , choices = [ " full " , " autocast " ] , default = " autocast " )
parser . add_argument ( " --share " , action = ' store_true ' , help = " use share=True for gradio and make the UI accessible through their site (doesn ' t work for me but you might have better luck) " )
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parser . add_argument ( " --esrgan-models-path " , type = str , help = " path to directory with ESRGAN models " , default = os . path . join ( script_path , ' ESRGAN ' ) )
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parser . add_argument ( " --swinir-models-path " , type = str , help = " path to directory with SwinIR models " , default = os . path . join ( script_path , ' SwinIR ' ) )
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parser . add_argument ( " --opt-split-attention " , action = ' store_true ' , help = " force-enables cross-attention layer optimization. By default, it ' s on for torch.cuda and off for other torch devices. " )
parser . add_argument ( " --disable-opt-split-attention " , action = ' store_true ' , help = " force-disables cross-attention layer optimization " )
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parser . add_argument ( " --opt-split-attention-v1 " , action = ' store_true ' , help = " enable older version of split attention optimization that does not consume all the VRAM it can find " )
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parser . add_argument ( " --listen " , action = ' store_true ' , help = " launch gradio with 0.0.0.0 as server name, allowing to respond to network requests " )
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parser . add_argument ( " --port " , type = int , help = " launch gradio with given server port, you need root/admin rights for ports < 1024, defaults to 7860 if available " , default = None )
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parser . add_argument ( " --show-negative-prompt " , action = ' store_true ' , help = " does not do anything " , default = False )
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parser . add_argument ( " --ui-config-file " , type = str , help = " filename to use for ui configuration " , default = os . path . join ( script_path , ' ui-config.json ' ) )
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parser . add_argument ( " --hide-ui-dir-config " , action = ' store_true ' , help = " hide directory configuration from webui " , default = False )
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parser . add_argument ( " --ui-settings-file " , type = str , help = " filename to use for ui settings " , default = os . path . join ( script_path , ' config.json ' ) )
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parser . add_argument ( " --gradio-debug " , action = ' store_true ' , help = " launch gradio with --debug option " )
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parser . add_argument ( " --gradio-auth " , type = str , help = ' set gradio authentication like " username:password " ; or comma-delimit multiple like " u1:p1,u2:p2,u3:p3 " ' , default = None )
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parser . add_argument ( " --opt-channelslast " , action = ' store_true ' , help = " change memory type for stable diffusion to channels last " )
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parser . add_argument ( " --styles-file " , type = str , help = " filename to use for styles " , default = os . path . join ( script_path , ' styles.csv ' ) )
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parser . add_argument ( " --autolaunch " , action = ' store_true ' , help = " open the webui URL in the system ' s default browser upon launch " , default = False )
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parser . add_argument ( " --use-textbox-seed " , action = ' store_true ' , help = " use textbox for seeds in UI (no up/down, but possible to input long seeds) " , default = False )
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cmd_opts = parser . parse_args ( )
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device = get_optimal_device ( )
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batch_cond_uncond = cmd_opts . always_batch_cond_uncond or not ( cmd_opts . lowvram or cmd_opts . medvram )
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parallel_processing_allowed = not cmd_opts . lowvram and not cmd_opts . medvram
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config_filename = cmd_opts . ui_settings_file
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class State :
interrupted = False
job = " "
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job_no = 0
job_count = 0
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job_timestamp = ' 0 '
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sampling_step = 0
sampling_steps = 0
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current_latent = None
current_image = None
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current_image_sampling_step = 0
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def interrupt ( self ) :
self . interrupted = True
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def nextjob ( self ) :
self . job_no + = 1
self . sampling_step = 0
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self . current_image_sampling_step = 0
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def get_job_timestamp ( self ) :
return datetime . datetime . now ( ) . strftime ( " % Y % m %d % H % M % S " )
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state = State ( )
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artist_db = modules . artists . ArtistsDatabase ( os . path . join ( script_path , ' artists.csv ' ) )
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styles_filename = cmd_opts . styles_file
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prompt_styles = modules . styles . StyleDatabase ( styles_filename )
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interrogator = modules . interrogate . InterrogateModels ( " interrogate " )
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face_restorers = [ ]
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modules . sd_models . list_models ( )
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def realesrgan_models_names ( ) :
import modules . realesrgan_model
return [ x . name for x in modules . realesrgan_model . get_realesrgan_models ( ) ]
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class OptionInfo :
def __init__ ( self , default = None , label = " " , component = None , component_args = None , onchange = None ) :
self . default = default
self . label = label
self . component = component
self . component_args = component_args
self . onchange = onchange
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self . section = None
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def options_section ( section_identifer , options_dict ) :
for k , v in options_dict . items ( ) :
v . section = section_identifer
return options_dict
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hide_dirs = { " visible " : not cmd_opts . hide_ui_dir_config }
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options_templates = { }
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options_templates . update ( options_section ( ( ' saving-images ' , " Saving images/grids " ) , {
" samples_save " : OptionInfo ( True , " Always save all generated images " ) ,
" samples_format " : OptionInfo ( ' png ' , ' File format for images ' ) ,
" samples_filename_pattern " : OptionInfo ( " " , " Images filename pattern " ) ,
" grid_save " : OptionInfo ( True , " Always save all generated image grids " ) ,
" grid_format " : OptionInfo ( ' png ' , ' File format for grids ' ) ,
" grid_extended_filename " : OptionInfo ( False , " Add extended info (seed, prompt) to filename when saving grid " ) ,
" grid_only_if_multiple " : OptionInfo ( True , " Do not save grids consisting of one picture " ) ,
" n_rows " : OptionInfo ( - 1 , " Grid row count; use -1 for autodetect and 0 for it to be same as batch size " , gr . Slider , { " minimum " : - 1 , " maximum " : 16 , " step " : 1 } ) ,
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" enable_pnginfo " : OptionInfo ( True , " Save text information about generation parameters as chunks to png files " ) ,
" save_txt " : OptionInfo ( False , " Create a text file next to every image with generation parameters. " ) ,
" save_images_before_face_restoration " : OptionInfo ( False , " Save a copy of image before doing face restoration. " ) ,
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" jpeg_quality " : OptionInfo ( 80 , " Quality for saved jpeg images " , gr . Slider , { " minimum " : 1 , " maximum " : 100 , " step " : 1 } ) ,
" export_for_4chan " : OptionInfo ( True , " If PNG image is larger than 4MB or any dimension is larger than 4000, downscale and save copy as JPG " ) ,
" use_original_name_batch " : OptionInfo ( False , " Use original name for output filename during batch process in extras tab " ) ,
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} ) )
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options_templates . update ( options_section ( ( ' saving-paths ' , " Paths for saving " ) , {
" outdir_samples " : OptionInfo ( " " , " Output directory for images; if empty, defaults to three directories below " , component_args = hide_dirs ) ,
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" outdir_txt2img_samples " : OptionInfo ( " outputs/txt2img-images " , ' Output directory for txt2img images ' , component_args = hide_dirs ) ,
" outdir_img2img_samples " : OptionInfo ( " outputs/img2img-images " , ' Output directory for img2img images ' , component_args = hide_dirs ) ,
" outdir_extras_samples " : OptionInfo ( " outputs/extras-images " , ' Output directory for images from extras tab ' , component_args = hide_dirs ) ,
" outdir_grids " : OptionInfo ( " " , " Output directory for grids; if empty, defaults to two directories below " , component_args = hide_dirs ) ,
" outdir_txt2img_grids " : OptionInfo ( " outputs/txt2img-grids " , ' Output directory for txt2img grids ' , component_args = hide_dirs ) ,
" outdir_img2img_grids " : OptionInfo ( " outputs/img2img-grids " , ' Output directory for img2img grids ' , component_args = hide_dirs ) ,
" outdir_save " : OptionInfo ( " log/images " , " Directory for saving images using the Save button " , component_args = hide_dirs ) ,
} ) )
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options_templates . update ( options_section ( ( ' saving-to-dirs ' , " Saving to a directory " ) , {
" save_to_dirs " : OptionInfo ( False , " Save images to a subdirectory " ) ,
" grid_save_to_dirs " : OptionInfo ( False , " Save grids to subdirectory " ) ,
" directories_filename_pattern " : OptionInfo ( " " , " Directory name pattern " ) ,
" directories_max_prompt_words " : OptionInfo ( 8 , " Max prompt words " , gr . Slider , { " minimum " : 1 , " maximum " : 20 , " step " : 1 } ) ,
} ) )
options_templates . update ( options_section ( ( ' upscaling ' , " Upscaling " ) , {
" ESRGAN_tile " : OptionInfo ( 192 , " Tile size for ESRGAN upscalers. 0 = no tiling. " , gr . Slider , { " minimum " : 0 , " maximum " : 512 , " step " : 16 } ) ,
" ESRGAN_tile_overlap " : OptionInfo ( 8 , " Tile overlap, in pixels for ESRGAN upscalers. Low values = visible seam. " , gr . Slider , { " minimum " : 0 , " maximum " : 48 , " step " : 1 } ) ,
" realesrgan_enabled_models " : OptionInfo ( [ " Real-ESRGAN 4x plus " , " Real-ESRGAN 4x plus anime 6B " ] , " Select which RealESRGAN models to show in the web UI. (Requires restart) " , gr . CheckboxGroup , lambda : { " choices " : realesrgan_models_names ( ) } ) ,
" SWIN_tile " : OptionInfo ( 192 , " Tile size for all SwinIR. " , gr . Slider , { " minimum " : 16 , " maximum " : 512 , " step " : 16 } ) ,
" SWIN_tile_overlap " : OptionInfo ( 8 , " Tile overlap, in pixels for SwinIR. Low values = visible seam. " , gr . Slider , { " minimum " : 0 , " maximum " : 48 , " step " : 1 } ) ,
" ldsr_steps " : OptionInfo ( 100 , " LDSR processing steps. Lower = faster " , gr . Slider , { " minimum " : 1 , " maximum " : 200 , " step " : 1 } ) ,
" ldsr_pre_down " : OptionInfo ( 1 , " LDSR Pre-process downssample scale. 1 = no down-sampling, 4 = 1/4 scale. " , gr . Slider , { " minimum " : 1 , " maximum " : 4 , " step " : 1 } ) ,
" ldsr_post_down " : OptionInfo ( 1 , " LDSR Post-process down-sample scale. 1 = no down-sampling, 4 = 1/4 scale. " , gr . Slider , { " minimum " : 1 , " maximum " : 4 , " step " : 1 } ) ,
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" upscaler_for_img2img " : OptionInfo ( None , " Upscaler for img2img " , gr . Radio , lambda : { " choices " : [ x . name for x in sd_upscalers ] } ) ,
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} ) )
options_templates . update ( options_section ( ( ' face-restoration ' , " Face restoration " ) , {
" face_restoration_model " : OptionInfo ( None , " Face restoration model " , gr . Radio , lambda : { " choices " : [ x . name ( ) for x in face_restorers ] } ) ,
" code_former_weight " : OptionInfo ( 0.5 , " CodeFormer weight parameter; 0 = maximum effect; 1 = minimum effect " , gr . Slider , { " minimum " : 0 , " maximum " : 1 , " step " : 0.01 } ) ,
" face_restoration_unload " : OptionInfo ( False , " Move face restoration model from VRAM into RAM after processing " ) ,
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" save_selected_only " : OptionInfo ( False , " When using ' Save ' button, only save a single selected image " ) ,
} ) )
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options_templates . update ( options_section ( ( ' system ' , " System " ) , {
" memmon_poll_rate " : OptionInfo ( 8 , " VRAM usage polls per second during generation. Set to 0 to disable. " , gr . Slider , { " minimum " : 0 , " maximum " : 40 , " step " : 1 } ) ,
" samples_log_stdout " : OptionInfo ( False , " Always print all generation info to standard output " ) ,
" multiple_tqdm " : OptionInfo ( True , " Add a second progress bar to the console that shows progress for an entire job. Broken in PyCharm console. " ) ,
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} ) )
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options_templates . update ( options_section ( ( ' sd ' , " Stable Diffusion " ) , {
" sd_model_checkpoint " : OptionInfo ( None , " Stable Diffusion checkpoint " , gr . Radio , lambda : { " choices " : [ x . title for x in modules . sd_models . checkpoints_list . values ( ) ] } ) ,
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" img2img_color_correction " : OptionInfo ( False , " Apply color correction to img2img results to match original colors. " ) ,
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" save_images_before_color_correction " : OptionInfo ( False , " Save a copy of image before applying color correction to img2img results " ) ,
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" img2img_fix_steps " : OptionInfo ( False , " With img2img, do exactly the amount of steps the slider specifies (normally you ' d do less with less denoising). " ) ,
" enable_quantization " : OptionInfo ( False , " Enable quantization in K samplers for sharper and cleaner results. This may change existing seeds. Requires restart to apply. " ) ,
" enable_emphasis " : OptionInfo ( True , " Use (text) to make model pay more attention to text and [text] to make it pay less attention " ) ,
" enable_batch_seeds " : OptionInfo ( True , " Make K-diffusion samplers produce same images in a batch as when making a single image " ) ,
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" filter_nsfw " : OptionInfo ( False , " Filter NSFW content " ) ,
" random_artist_categories " : OptionInfo ( [ ] , " Allowed categories for random artists selection when using the Roll button " , gr . CheckboxGroup , { " choices " : artist_db . categories ( ) } ) ,
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} ) )
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options_templates . update ( options_section ( ( ' interrogate ' , " Interrogate Options " ) , {
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" interrogate_keep_models_in_memory " : OptionInfo ( False , " Interrogate: keep models in VRAM " ) ,
" interrogate_use_builtin_artists " : OptionInfo ( True , " Interrogate: use artists from artists.csv " ) ,
" interrogate_clip_num_beams " : OptionInfo ( 1 , " Interrogate: num_beams for BLIP " , gr . Slider , { " minimum " : 1 , " maximum " : 16 , " step " : 1 } ) ,
" interrogate_clip_min_length " : OptionInfo ( 24 , " Interrogate: minimum description length (excluding artists, etc..) " , gr . Slider , { " minimum " : 1 , " maximum " : 128 , " step " : 1 } ) ,
" interrogate_clip_max_length " : OptionInfo ( 48 , " Interrogate: maximum description length " , gr . Slider , { " minimum " : 1 , " maximum " : 256 , " step " : 1 } ) ,
" interrogate_clip_dict_limit " : OptionInfo ( 1500 , " Interrogate: maximum number of lines in text file (0 = No limit) " ) ,
} ) )
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options_templates . update ( options_section ( ( ' ui ' , " User interface " ) , {
" show_progressbar " : OptionInfo ( True , " Show progressbar " ) ,
" show_progress_every_n_steps " : OptionInfo ( 0 , " Show show image creation progress every N sampling steps. Set 0 to disable. " , gr . Slider , { " minimum " : 0 , " maximum " : 32 , " step " : 1 } ) ,
" return_grid " : OptionInfo ( True , " Show grid in results for web " ) ,
" add_model_hash_to_info " : OptionInfo ( True , " Add model hash to generation information " ) ,
" font " : OptionInfo ( " " , " Font for image grids that have text " ) ,
" js_modal_lightbox " : OptionInfo ( True , " Enable full page image viewer " ) ,
" js_modal_lightbox_initialy_zoomed " : OptionInfo ( True , " Show images zoomed in by default in full page image viewer " ) ,
} ) )
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options_templates . update ( options_section ( ( ' sampler-params ' , " Sampler parameters " ) , {
" ddim_eta " : OptionInfo ( 0.0 , " img2img ddim eta " , gr . Slider , { " minimum " : 0.0 , " maximum " : 1.0 , " step " : 0.01 } ) ,
" ddim_discretize " : OptionInfo ( ' uniform ' , " img2img ddim discretize " , gr . Radio , { " choices " : [ ' uniform ' , ' quad ' ] } ) ,
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' s_churn ' : OptionInfo ( 0.0 , " sigma churn " , gr . Slider , { " minimum " : 0.0 , " maximum " : 1.0 , " step " : 0.01 } ) ,
' s_tmin ' : OptionInfo ( 0.0 , " sigma tmin " , gr . Slider , { " minimum " : 0.0 , " maximum " : 1.0 , " step " : 0.01 } ) ,
' s_noise ' : OptionInfo ( 1.0 , " sigma noise " , gr . Slider , { " minimum " : 0.0 , " maximum " : 1.0 , " step " : 0.01 } ) ,
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} ) )
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class Options :
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data = None
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data_labels = options_templates
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typemap = { int : float }
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def __init__ ( self ) :
self . data = { k : v . default for k , v in self . data_labels . items ( ) }
def __setattr__ ( self , key , value ) :
if self . data is not None :
if key in self . data :
self . data [ key ] = value
return super ( Options , self ) . __setattr__ ( key , value )
def __getattr__ ( self , item ) :
if self . data is not None :
if item in self . data :
return self . data [ item ]
if item in self . data_labels :
return self . data_labels [ item ] . default
return super ( Options , self ) . __getattribute__ ( item )
def save ( self , filename ) :
with open ( filename , " w " , encoding = " utf8 " ) as file :
json . dump ( self . data , file )
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def same_type ( self , x , y ) :
if x is None or y is None :
return True
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type_x = self . typemap . get ( type ( x ) , type ( x ) )
type_y = self . typemap . get ( type ( y ) , type ( y ) )
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return type_x == type_y
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def load ( self , filename ) :
with open ( filename , " r " , encoding = " utf8 " ) as file :
self . data = json . load ( file )
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bad_settings = 0
for k , v in self . data . items ( ) :
info = self . data_labels . get ( k , None )
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if info is not None and not self . same_type ( info . default , v ) :
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print ( f " Warning: bad setting value: { k } : { v } ( { type ( v ) . __name__ } ; expected { type ( info . default ) . __name__ } ) " , file = sys . stderr )
bad_settings + = 1
if bad_settings > 0 :
print ( f " The program is likely to not work with bad settings. \n Settings file: { filename } \n Either fix the file, or delete it and restart. " , file = sys . stderr )
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def onchange ( self , key , func ) :
item = self . data_labels . get ( key )
item . onchange = func
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def dumpjson ( self ) :
d = { k : self . data . get ( k , self . data_labels . get ( k ) . default ) for k in self . data_labels . keys ( ) }
return json . dumps ( d )
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opts = Options ( )
if os . path . exists ( config_filename ) :
opts . load ( config_filename )
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sd_upscalers = [ ]
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sd_model = None
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progress_print_out = sys . stdout
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class TotalTQDM :
def __init__ ( self ) :
self . _tqdm = None
def reset ( self ) :
self . _tqdm = tqdm . tqdm (
desc = " Total progress " ,
total = state . job_count * state . sampling_steps ,
position = 1 ,
file = progress_print_out
)
def update ( self ) :
if not opts . multiple_tqdm :
return
if self . _tqdm is None :
self . reset ( )
self . _tqdm . update ( )
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def updateTotal ( self , new_total ) :
if not opts . multiple_tqdm :
return
if self . _tqdm is None :
self . reset ( )
self . _tqdm . total = new_total
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def clear ( self ) :
if self . _tqdm is not None :
self . _tqdm . close ( )
self . _tqdm = None
total_tqdm = TotalTQDM ( )
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mem_mon = modules . memmon . MemUsageMonitor ( " MemMon " , device , opts )
mem_mon . start ( )