"ESRGAN_tile":OptionInfo(192,"Tile size for ESRGAN upscalers.",gr.Slider,{"minimum":0,"maximum":512,"step":16}).info("0 = no tiling"),
"ESRGAN_tile":OptionInfo(192,"Tile size for ESRGAN upscalers.",gr.Slider,{"minimum":0,"maximum":512,"step":16}).info("0 = no tiling"),
"ESRGAN_tile_overlap":OptionInfo(8,"Tile overlap for ESRGAN upscalers.",gr.Slider,{"minimum":0,"maximum":48,"step":1}).info("Low values = visible seam"),
"ESRGAN_tile_overlap":OptionInfo(8,"Tile overlap for ESRGAN upscalers.",gr.Slider,{"minimum":0,"maximum":48,"step":1}).info("Low values = visible seam"),
"realesrgan_enabled_models":OptionInfo(["R-ESRGAN 4x+","R-ESRGAN 4x+ Anime6B"],"Select which Real-ESRGAN models to show in the web UI.",gr.CheckboxGroup,lambda:{"choices":shared_items.realesrgan_models_names()}),
"realesrgan_enabled_models":OptionInfo(["R-ESRGAN 4x+","R-ESRGAN 4x+ Anime6B"],"Select which Real-ESRGAN models to show in the web UI.",gr.CheckboxGroup,lambda:{"choices":shared_items.realesrgan_models_names()}),
"upscaler_for_img2img":OptionInfo(None,"Upscaler for img2img",gr.Dropdown,lambda:{"choices":[x.nameforxinshared.sd_upscalers]}),
"upscaler_for_img2img":OptionInfo(None,"Upscaler for img2img",gr.Dropdown,lambda:{"choices":[x.nameforxinshared.sd_upscalers]}),
"face_restoration":OptionInfo(False,"Restore faces",infotext='Face restoration').info("will use a third-party model on generation result to reconstruct faces"),
"face_restoration":OptionInfo(False,"Restore faces",infotext='Face restoration').info("will use a third-party model on generation result to reconstruct faces"),
"unload_models_when_training":OptionInfo(False,"Move VAE and CLIP to RAM when training if possible. Saves VRAM."),
"unload_models_when_training":OptionInfo(False,"Move VAE and CLIP to RAM when training if possible. Saves VRAM."),
"pin_memory":OptionInfo(False,"Turn on pin_memory for DataLoader. Makes training slightly faster but can increase memory usage."),
"pin_memory":OptionInfo(False,"Turn on pin_memory for DataLoader. Makes training slightly faster but can increase memory usage."),
"save_optimizer_state":OptionInfo(False,"Saves Optimizer state as separate *.optim file. Training of embedding or HN can be resumed with the matching optim file."),
"save_optimizer_state":OptionInfo(False,"Saves Optimizer state as separate *.optim file. Training of embedding or HN can be resumed with the matching optim file."),
"sd_checkpoints_limit":OptionInfo(1,"Maximum number of checkpoints loaded at the same time",gr.Slider,{"minimum":1,"maximum":10,"step":1}),
"sd_checkpoints_limit":OptionInfo(1,"Maximum number of checkpoints loaded at the same time",gr.Slider,{"minimum":1,"maximum":10,"step":1}),
"sd_checkpoints_keep_in_cpu":OptionInfo(True,"Only keep one model on device").info("will keep models other than the currently used one in RAM rather than VRAM"),
"sd_checkpoints_keep_in_cpu":OptionInfo(True,"Only keep one model on device").info("will keep models other than the currently used one in RAM rather than VRAM"),
<abbr title='Variational autoencoder'>VAE</abbr> is a neural network that transforms a standard <abbr title='red/green/blue'>RGB</abbr>
<abbr title='Variational autoencoder'>VAE</abbr> is a neural network that transforms a standard <abbr title='red/green/blue'>RGB</abbr>
image into latent space representation and back. Latent space representation is what stable diffusion is working on during sampling
image into latent space representation and back. Latent space representation is what stable diffusion is working on during sampling
...
@@ -176,7 +183,7 @@ For img2img, VAE is used to process user's input image before the sampling, and
...
@@ -176,7 +183,7 @@ For img2img, VAE is used to process user's input image before the sampling, and
"sd_vae_decode_method":OptionInfo("Full","VAE type for decode",gr.Radio,{"choices":["Full","TAESD"]},infotext='VAE Decoder').info("method to decode latent to image"),
"sd_vae_decode_method":OptionInfo("Full","VAE type for decode",gr.Radio,{"choices":["Full","TAESD"]},infotext='VAE Decoder').info("method to decode latent to image"),
"initial_noise_multiplier":OptionInfo(1.0,"Noise multiplier for img2img",gr.Slider,{"minimum":0.0,"maximum":1.5,"step":0.001},infotext='Noise multiplier'),
"initial_noise_multiplier":OptionInfo(1.0,"Noise multiplier for img2img",gr.Slider,{"minimum":0.0,"maximum":1.5,"step":0.001},infotext='Noise multiplier'),
"img2img_extra_noise":OptionInfo(0.0,"Extra noise multiplier for img2img and hires fix",gr.Slider,{"minimum":0.0,"maximum":1.0,"step":0.01},infotext='Extra noise').info("0 = disabled (default); should be lower than denoising strength"),
"img2img_extra_noise":OptionInfo(0.0,"Extra noise multiplier for img2img and hires fix",gr.Slider,{"minimum":0.0,"maximum":1.0,"step":0.01},infotext='Extra noise').info("0 = disabled (default); should be lower than denoising strength"),
"img2img_batch_show_results_limit":OptionInfo(32,"Show the first N batch img2img results in UI",gr.Slider,{"minimum":-1,"maximum":1000,"step":1}).info('0: disable, -1: show all images. Too many images can cause lag'),
"img2img_batch_show_results_limit":OptionInfo(32,"Show the first N batch img2img results in UI",gr.Slider,{"minimum":-1,"maximum":1000,"step":1}).info('0: disable, -1: show all images. Too many images can cause lag'),
"s_min_uncond":OptionInfo(0.0,"Negative Guidance minimum sigma",gr.Slider,{"minimum":0.0,"maximum":15.0,"step":0.01}).link("PR","https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/9177").info("skip negative prompt for some steps when the image is almost ready; 0=disable, higher=faster"),
"s_min_uncond":OptionInfo(0.0,"Negative Guidance minimum sigma",gr.Slider,{"minimum":0.0,"maximum":15.0,"step":0.01}).link("PR","https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/9177").info("skip negative prompt for some steps when the image is almost ready; 0=disable, higher=faster"),
"batch_cond_uncond":OptionInfo(True,"Batch cond/uncond").info("do both conditional and unconditional denoising in one batch; uses a bit more VRAM during sampling, but improves speed; previously this was controlled by --always-batch-cond-uncond comandline argument"),
"batch_cond_uncond":OptionInfo(True,"Batch cond/uncond").info("do both conditional and unconditional denoising in one batch; uses a bit more VRAM during sampling, but improves speed; previously this was controlled by --always-batch-cond-uncond comandline argument"),
"extra_networks_show_hidden_directories":OptionInfo(True,"Show hidden directories").info("directory is hidden if its name starts with \".\"."),
"extra_networks_show_hidden_directories":OptionInfo(True,"Show hidden directories").info("directory is hidden if its name starts with \".\"."),
"extra_networks_hidden_models":OptionInfo("When searched","Show cards for models in hidden directories",gr.Radio,{"choices":["Always","When searched","Never"]}).info('"When searched" option will only show the item when the search string has 4 characters or more'),
"extra_networks_hidden_models":OptionInfo("When searched","Show cards for models in hidden directories",gr.Radio,{"choices":["Always","When searched","Never"]}).info('"When searched" option will only show the item when the search string has 4 characters or more'),
"extra_networks_default_multiplier":OptionInfo(1.0,"Default multiplier for extra networks",gr.Slider,{"minimum":0.0,"maximum":2.0,"step":0.01}),
"extra_networks_default_multiplier":OptionInfo(1.0,"Default multiplier for extra networks",gr.Slider,{"minimum":0.0,"maximum":2.0,"step":0.01}),
"sd_hypernetwork":OptionInfo("None","Add hypernetwork to prompt",gr.Dropdown,lambda:{"choices":["None",*shared.hypernetworks]},refresh=shared_items.reload_hypernetworks),
"sd_hypernetwork":OptionInfo("None","Add hypernetwork to prompt",gr.Dropdown,lambda:{"choices":["None",*shared.hypernetworks]},refresh=shared_items.reload_hypernetworks),
"gradio_theme":OptionInfo("Default","Gradio theme",ui_components.DropdownEditable,lambda:{"choices":["Default"]+shared_gradio_themes.gradio_hf_hub_themes}).info("you can also manually enter any of themes from the <a href='https://huggingface.co/spaces/gradio/theme-gallery'>gallery</a>.").needs_reload_ui(),
"gradio_theme":OptionInfo("Default","Gradio theme",ui_components.DropdownEditable,lambda:{"choices":["Default"]+shared_gradio_themes.gradio_hf_hub_themes}).info("you can also manually enter any of themes from the <a href='https://huggingface.co/spaces/gradio/theme-gallery'>gallery</a>.").needs_reload_ui(),
"gradio_themes_cache":OptionInfo(True,"Cache gradio themes locally").info("disable to update the selected Gradio theme"),
"gradio_themes_cache":OptionInfo(True,"Cache gradio themes locally").info("disable to update the selected Gradio theme"),
"hide_samplers":OptionInfo([],"Hide samplers in user interface",gr.CheckboxGroup,lambda:{"choices":[x.nameforxinshared_items.list_samplers()]}).needs_reload_ui(),
"hide_samplers":OptionInfo([],"Hide samplers in user interface",gr.CheckboxGroup,lambda:{"choices":[x.nameforxinshared_items.list_samplers()]}).needs_reload_ui(),
"eta_ddim":OptionInfo(0.0,"Eta for DDIM",gr.Slider,{"minimum":0.0,"maximum":1.0,"step":0.01},infotext='Eta DDIM').info("noise multiplier; higher = more unpredictable results"),
"eta_ddim":OptionInfo(0.0,"Eta for DDIM",gr.Slider,{"minimum":0.0,"maximum":1.0,"step":0.01},infotext='Eta DDIM').info("noise multiplier; higher = more unpredictable results"),
"eta_ancestral":OptionInfo(1.0,"Eta for k-diffusion samplers",gr.Slider,{"minimum":0.0,"maximum":1.0,"step":0.01},infotext='Eta').info("noise multiplier; currently only applies to ancestral samplers (i.e. Euler a) and SDE samplers"),
"eta_ancestral":OptionInfo(1.0,"Eta for k-diffusion samplers",gr.Slider,{"minimum":0.0,"maximum":1.0,"step":0.01},infotext='Eta').info("noise multiplier; currently only applies to ancestral samplers (i.e. Euler a) and SDE samplers"),
'postprocessing_enable_in_main_ui':OptionInfo([],"Enable postprocessing operations in txt2img and img2img tabs",ui_components.DropdownMulti,lambda:{"choices":[x.nameforxinshared_items.postprocessing_scripts()]}),
'postprocessing_enable_in_main_ui':OptionInfo([],"Enable postprocessing operations in txt2img and img2img tabs",ui_components.DropdownMulti,lambda:{"choices":[x.nameforxinshared_items.postprocessing_scripts()]}),