mirror of
https://github.com/vladmandic/automatic
synced 2026-09-19 09:14:35 +02:00
Merge branch 'master' into gradio-theme-support
This commit is contained in:
Vladimir Mandic
GitHub
+157
-155
@@ -1,4 +1,3 @@
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import argparse
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import datetime
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import json
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import os
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@@ -6,7 +5,6 @@ import sys
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import time
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import requests
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from PIL import Image
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import gradio as gr
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import tqdm
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@@ -14,22 +12,25 @@ import modules.interrogate
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import modules.memmon
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import modules.styles
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import modules.devices as devices
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from modules import localization, script_loading, errors, ui_components, shared_items, cmd_args
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from modules.paths_internal import models_path, script_path, data_path, sd_configs_path, sd_default_config, sd_model_file, default_sd_model_file, extensions_dir, extensions_builtin_dir
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from modules import script_loading, errors, ui_components, shared_items, cmd_args
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from modules.paths_internal import models_path, script_path, data_path, sd_configs_path, sd_default_config, sd_model_file, default_sd_model_file, extensions_dir, extensions_builtin_dir # pylint: disable=W0611
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import modules.paths_internal as paths
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from setup import log as setup_log # pylint: disable=E0611
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errors.install(gr)
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demo = None
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log = setup_log
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parser = cmd_args.parser
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script_loading.preload_extensions(extensions_dir, parser)
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script_loading.preload_extensions(extensions_builtin_dir, parser)
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script_loading.preload_extensions(paths.extensions_dir, parser)
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script_loading.preload_extensions(paths.extensions_builtin_dir, parser)
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if os.environ.get('IGNORE_CMD_ARGS_ERRORS', None) is None:
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cmd_opts = parser.parse_args()
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else:
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cmd_opts, _ = parser.parse_known_args()
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restricted_opts = {
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"samples_filename_pattern",
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"directories_filename_pattern",
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@@ -69,30 +70,21 @@ gradio_hf_hub_themes = [
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"ysharma/steampunk"
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]
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cmd_opts.disable_extension_access = (cmd_opts.share or cmd_opts.listen or cmd_opts.server_name) and not cmd_opts.enable_insecure_extension_access
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cmd_opts.disable_extension_access = (cmd_opts.share or cmd_opts.listen or cmd_opts.server_name) and not cmd_opts.enable_insecure
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devices.device, devices.device_interrogate, devices.device_gfpgan, devices.device_esrgan, devices.device_codeformer = \
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(devices.cpu if any(y in cmd_opts.use_cpu for y in [x, 'all']) else devices.get_optimal_device() for x in ['sd', 'interrogate', 'gfpgan', 'esrgan', 'codeformer'])
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device = devices.device
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weight_load_location = None if cmd_opts.lowram else "cpu"
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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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xformers_available = False
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config_filename = cmd_opts.ui_settings_file
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os.makedirs(cmd_opts.hypernetwork_dir, exist_ok=True)
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hypernetworks = {}
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loaded_hypernetworks = []
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sd_upscalers = []
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sd_model = None
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clip_model = None
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def reload_hypernetworks():
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from modules.hypernetworks import hypernetwork
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global hypernetworks
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hypernetworks = hypernetwork.list_hypernetworks(cmd_opts.hypernetwork_dir)
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global hypernetworks # pylint: disable=W0603
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hypernetworks = hypernetwork.list_hypernetworks(opts.hypernetwork_dir)
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class State:
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@@ -177,7 +169,7 @@ class State:
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if self.current_latent is None:
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return
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import modules.sd_samplers
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import modules.sd_samplers # pylint: disable=W0621
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if opts.show_progress_grid:
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self.assign_current_image(modules.sd_samplers.samples_to_image_grid(self.current_latent))
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else:
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@@ -193,8 +185,7 @@ class State:
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state = State()
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state.server_start = time.time()
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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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prompt_styles = modules.styles.StyleDatabase('styles.csv')
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interrogator = modules.interrogate.InterrogateModels("interrogate")
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@@ -212,24 +203,24 @@ class OptionInfo:
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def options_section(section_identifier, options_dict):
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for k, v in options_dict.items():
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for _k, v in options_dict.items():
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v.section = section_identifier
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return options_dict
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def list_checkpoint_tiles():
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import modules.sd_models
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import modules.sd_models # pylint: disable=W0621
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return modules.sd_models.checkpoint_tiles()
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def refresh_checkpoints():
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import modules.sd_models
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import modules.sd_models # pylint: disable=W0621
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return modules.sd_models.list_models()
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def list_samplers():
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import modules.sd_samplers
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import modules.sd_samplers # pylint: disable=W0621
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return modules.sd_samplers.all_samplers
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@@ -237,101 +228,10 @@ hide_dirs = {"visible": not cmd_opts.hide_ui_dir_config}
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tab_names = []
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options_templates = {}
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options_templates.update(options_section(('saving-images', "Saving images/grids"), {
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"samples_save": OptionInfo(True, "Always save all generated images"),
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"samples_format": OptionInfo('png', 'File format for images'),
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"samples_filename_pattern": OptionInfo("", "Images filename pattern", component_args=hide_dirs),
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"save_images_add_number": OptionInfo(True, "Add number to filename when saving", component_args=hide_dirs),
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"grid_save": OptionInfo(True, "Always save all generated image grids"),
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"grid_format": OptionInfo('png', 'File format for grids'),
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"grid_extended_filename": OptionInfo(False, "Add extended info (seed, prompt) to filename when saving grid"),
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"grid_only_if_multiple": OptionInfo(True, "Do not save grids consisting of one picture"),
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"grid_prevent_empty_spots": OptionInfo(False, "Prevent empty spots in grid (when set to autodetect)"),
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"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"),
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"save_txt": OptionInfo(False, "Create a text file next to every image with generation parameters."),
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"save_images_before_face_restoration": OptionInfo(False, "Save a copy of image before doing face restoration."),
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"save_images_before_highres_fix": OptionInfo(False, "Save a copy of image before applying highres fix."),
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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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"save_mask": OptionInfo(False, "For inpainting, save a copy of the greyscale mask"),
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"save_mask_composite": OptionInfo(False, "For inpainting, save a masked composite"),
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"jpeg_quality": OptionInfo(80, "Quality for saved jpeg images", gr.Slider, {"minimum": 1, "maximum": 100, "step": 1}),
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"webp_lossless": OptionInfo(False, "Use lossless compression for webp images"),
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"export_for_4chan": OptionInfo(True, "If the saved image file size is above the limit, or its either width or height are above the limit, save a downscaled copy as JPG"),
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"img_downscale_threshold": OptionInfo(4.0, "File size limit for the above option, MB", gr.Number),
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"target_side_length": OptionInfo(4000, "Width/height limit for the above option, in pixels", gr.Number),
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"img_max_size_mp": OptionInfo(200, "Maximum image size, in megapixels", gr.Number),
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"use_original_name_batch": OptionInfo(True, "Use original name for output filename during batch process in extras tab"),
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"use_upscaler_name_as_suffix": OptionInfo(False, "Use upscaler name as filename suffix in the extras tab"),
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"save_selected_only": OptionInfo(True, "When using 'Save' button, only save a single selected image"),
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"do_not_add_watermark": OptionInfo(False, "Do not add watermark to images"),
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"temp_dir": OptionInfo("", "Directory for temporary images; leave empty for default"),
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"clean_temp_dir_at_start": OptionInfo(False, "Cleanup non-default temporary directory when starting webui"),
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}))
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options_templates.update(options_section(('saving-paths', "Paths for saving"), {
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"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),
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"outdir_img2img_samples": OptionInfo("outputs/img2img-images", 'Output directory for img2img images', component_args=hide_dirs),
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"outdir_extras_samples": OptionInfo("outputs/extras-images", 'Output directory for images from extras tab', component_args=hide_dirs),
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"outdir_grids": OptionInfo("", "Output directory for grids; if empty, defaults to two directories below", component_args=hide_dirs),
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"outdir_txt2img_grids": OptionInfo("outputs/txt2img-grids", 'Output directory for txt2img grids', component_args=hide_dirs),
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"outdir_img2img_grids": OptionInfo("outputs/img2img-grids", 'Output directory for img2img grids', component_args=hide_dirs),
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"outdir_save": OptionInfo("log/images", "Directory for saving images using the Save button", component_args=hide_dirs),
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}))
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options_templates.update(options_section(('saving-to-dirs', "Saving to a directory"), {
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"save_to_dirs": OptionInfo(True, "Save images to a subdirectory"),
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"grid_save_to_dirs": OptionInfo(True, "Save grids to a subdirectory"),
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"use_save_to_dirs_for_ui": OptionInfo(False, "When using \"Save\" button, save images to a subdirectory"),
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"directories_filename_pattern": OptionInfo("[date]", "Directory name pattern", component_args=hide_dirs),
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"directories_max_prompt_words": OptionInfo(8, "Max prompt words for [prompt_words] pattern", gr.Slider, {"minimum": 1, "maximum": 20, "step": 1, **hide_dirs}),
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}))
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options_templates.update(options_section(('upscaling', "Upscaling"), {
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"ESRGAN_tile": OptionInfo(192, "Tile size for ESRGAN upscalers. 0 = no tiling.", gr.Slider, {"minimum": 0, "maximum": 512, "step": 16}),
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"ESRGAN_tile_overlap": OptionInfo(8, "Tile overlap, in pixels for ESRGAN upscalers. Low values = visible seam.", gr.Slider, {"minimum": 0, "maximum": 48, "step": 1}),
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"realesrgan_enabled_models": OptionInfo(["R-ESRGAN 4x+", "R-ESRGAN 4x+ Anime6B"], "Select which Real-ESRGAN models to show in the web UI. (Requires restart)", gr.CheckboxGroup, lambda: {"choices": shared_items.realesrgan_models_names()}),
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"upscaler_for_img2img": OptionInfo(None, "Upscaler for img2img", gr.Dropdown, lambda: {"choices": [x.name for x in sd_upscalers]}),
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}))
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options_templates.update(options_section(('face-restoration', "Face restoration"), {
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"face_restoration_model": OptionInfo("CodeFormer", "Face restoration model", gr.Radio, lambda: {"choices": [x.name() for x in face_restorers]}),
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"code_former_weight": OptionInfo(0.5, "CodeFormer weight parameter; 0 = maximum effect; 1 = minimum effect", gr.Slider, {"minimum": 0, "maximum": 1, "step": 0.01}),
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"face_restoration_unload": OptionInfo(False, "Move face restoration model from VRAM into RAM after processing"),
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}))
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options_templates.update(options_section(('system', "System"), {
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"show_warnings": OptionInfo(False, "Show warnings in console."),
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"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}),
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"samples_log_stdout": OptionInfo(False, "Always print all generation info to standard output"),
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"multiple_tqdm": OptionInfo(True, "Add a second progress bar to the console that shows progress for an entire job."),
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"print_hypernet_extra": OptionInfo(False, "Print extra hypernetwork information to console."),
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}))
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options_templates.update(options_section(('training', "Training"), {
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"unload_models_when_training": OptionInfo(False, "Move VAE and CLIP to RAM when training if possible. Saves VRAM."),
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"pin_memory": OptionInfo(False, "Turn on pin_memory for DataLoader. Makes training slightly faster but can increase memory usage."),
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"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."),
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"save_training_settings_to_txt": OptionInfo(True, "Save textual inversion and hypernet settings to a text file whenever training starts."),
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"dataset_filename_word_regex": OptionInfo("", "Filename word regex"),
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"dataset_filename_join_string": OptionInfo(" ", "Filename join string"),
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"training_image_repeats_per_epoch": OptionInfo(1, "Number of repeats for a single input image per epoch; used only for displaying epoch number", gr.Number, {"precision": 0}),
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"training_write_csv_every": OptionInfo(500, "Save an csv containing the loss to log directory every N steps, 0 to disable"),
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"training_xattention_optimizations": OptionInfo(False, "Use cross attention optimizations while training"),
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"training_enable_tensorboard": OptionInfo(False, "Enable tensorboard logging."),
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"training_tensorboard_save_images": OptionInfo(False, "Save generated images within tensorboard."),
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"training_tensorboard_flush_every": OptionInfo(120, "How often, in seconds, to flush the pending tensorboard events and summaries to disk."),
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}))
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default_checkpoint = list_checkpoint_tiles()[0] if len(list_checkpoint_tiles()) > 0 else "model.ckpt"
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options_templates.update(options_section(('sd', "Stable Diffusion"), {
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"sd_model_checkpoint": OptionInfo(None, "Stable Diffusion checkpoint", gr.Dropdown, lambda: {"choices": list_checkpoint_tiles()}, refresh=refresh_checkpoints),
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"sd_model_checkpoint": OptionInfo(default_checkpoint, "Stable Diffusion checkpoint", gr.Dropdown, lambda: {"choices": list_checkpoint_tiles()}, refresh=refresh_checkpoints),
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"sd_checkpoint_cache": OptionInfo(0, "Checkpoints to cache in RAM", gr.Slider, {"minimum": 0, "maximum": 10, "step": 1}),
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"sd_vae_checkpoint_cache": OptionInfo(0, "VAE Checkpoints to cache in RAM", gr.Slider, {"minimum": 0, "maximum": 10, "step": 1}),
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"sd_vae": OptionInfo("Automatic", "SD VAE", gr.Dropdown, lambda: {"choices": shared_items.sd_vae_items()}, refresh=shared_items.refresh_vae_list),
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@@ -341,31 +241,129 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), {
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"img2img_color_correction": OptionInfo(False, "Apply color correction to img2img results to match original colors."),
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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)."),
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"img2img_background_color": OptionInfo("#ffffff", "With img2img, fill image's transparent parts with this color.", ui_components.FormColorPicker, {}),
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"enable_quantization": OptionInfo(False, "Enable quantization in K samplers for sharper and cleaner results. This may change existing seeds. Requires restart to apply."),
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"enable_quantization": OptionInfo(True, "Enable quantization in K samplers for sharper and cleaner results. This may change existing seeds. Requires restart to apply."),
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"enable_emphasis": OptionInfo(True, "Emphasis: use (text) to make model pay more attention to text and [text] to make it pay less attention"),
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"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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"comma_padding_backtrack": OptionInfo(20, "Increase coherency by padding from the last comma within n tokens when using more than 75 tokens", gr.Slider, {"minimum": 0, "maximum": 74, "step": 1 }),
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"CLIP_stop_at_last_layers": OptionInfo(1, "Clip skip", gr.Slider, {"minimum": 1, "maximum": 12, "step": 1}),
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"upcast_attn": OptionInfo(False, "Upcast cross attention layer to float32"),
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"cross_attention_optimization": OptionInfo("Scaled-Dot-Product", "Cross-attention optimization method", gr.Radio, lambda: {"choices": shared_items.list_crossattention() }),
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"cross_attention_options": OptionInfo([], "Cross-attention advanced options", gr.CheckboxGroup, lambda: {"choices": ['xFormers enable flash Attention', 'SDP disable memory attention']}),
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"disable_nan_check": OptionInfo(False, "Do not check if produced images/latent spaces have NaN values"),
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"opt_channelslast": OptionInfo(False, "Use channels last as torch memory format "),
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"cudnn_benchmark": OptionInfo(False, "Enable CUDA cuDNN benchmark feature"),
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"sub_quad_q_chunk_size": OptionInfo(512, "Sub-quadratic cross-attention query chunk size for the layer optimization to use", gr.Slider, {"minimum": 16, "maximum": 8192, "step": 8}),
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"sub_quad_kv_chunk_size": OptionInfo(512, "Sub-quadratic cross-attentionkv chunk size for the sub-quadratic cross-attention layer optimization to use", gr.Slider, {"minimum": 0, "maximum": 8192, "step": 8}),
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"sub_quad_chunk_threshold": OptionInfo(80, "Sub-quadratic cross-attention percentage of VRAM chunking threshold", gr.Slider, {"minimum": 0, "maximum": 100, "step": 1}),
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"always_batch_cond_uncond": OptionInfo(False, "Disables cond/uncond batching that is enabled to save memory with --medvram or --lowvram"),
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"upcast_sampling": OptionInfo(False, "Enable upcast sampling. Usually produces similar results to --no-half with better performance while using less memory"),
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}))
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options_templates.update(options_section(('compatibility', "Compatibility"), {
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"use_old_emphasis_implementation": OptionInfo(False, "Use old emphasis implementation. Can be useful to reproduce old seeds."),
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"use_old_karras_scheduler_sigmas": OptionInfo(False, "Use old karras scheduler sigmas (0.1 to 10)."),
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"no_dpmpp_sde_batch_determinism": OptionInfo(False, "Do not make DPM++ SDE deterministic across different batch sizes."),
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options_templates.update(options_section(('system-paths', "System Paths"), {
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"ckpt_dir": OptionInfo(os.path.join(paths.models_path, 'Stable-diffusion'), "Path to directory with stable diffusion checkpoints"),
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"vae_dir": OptionInfo(os.path.join(paths.models_path, 'VAE'), "Path to directory with VAE files"),
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"embeddings_dir": OptionInfo(os.path.join(paths.models_path, 'embeddings'), "Embeddings directory for textual inversion"),
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"embeddings_templates_dir": OptionInfo(os.path.join(paths.script_path, 'train/templates'), "Embeddings train templates directory"),
|
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"hypernetwork_dir": OptionInfo(os.path.join(paths.models_path, 'hypernetworks'), "Hypernetwork directory"),
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"codeformer_models_path": OptionInfo(os.path.join(paths.models_path, 'Codeformer'), "Path to directory with codeformer model file(s)."),
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"gfpgan_models_path": OptionInfo(os.path.join(paths.models_path, 'GFPGAN'), "Path to directory with GFPGAN model file(s)"),
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"esrgan_models_path": OptionInfo(os.path.join(paths.models_path, 'ESRGAN'), "Path to directory with ESRGAN model file(s)"),
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"bsrgan_models_path": OptionInfo(os.path.join(paths.models_path, 'BSRGAN'), "Path to directory with BSRGAN model file(s)"),
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"realesrgan_models_path": OptionInfo(os.path.join(paths.models_path, 'RealESRGAN'), "Path to directory with RealESRGAN model file(s)"),
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"clip_models_path": OptionInfo(os.path.join(paths.models_path, 'CLIP'), "Path to directory with CLIP model file(s)"),
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"lora_dir": OptionInfo(os.path.join(paths.models_path, 'Lora'), "Path to directory with Lora network(s)"),
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"lyco_dir": OptionInfo(os.path.join(paths.models_path, 'LyCORIS'), "Path to directory with LyCORIS network(s)"),
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# "gfpgan_model": OptionInfo("", "GFPGAN model file name"),
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}))
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options_templates.update(options_section(('saving-images', "Image options"), {
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"samples_save": OptionInfo(True, "Always save all generated images"),
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"samples_format": OptionInfo('jpg', 'File format for images'),
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"samples_filename_pattern": OptionInfo("", "Images filename pattern", component_args=hide_dirs),
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"save_images_add_number": OptionInfo(True, "Add number to filename when saving", component_args=hide_dirs),
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"grid_save": OptionInfo(True, "Always save all generated image grids"),
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"grid_format": OptionInfo('jpg', 'File format for grids'),
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"grid_extended_filename": OptionInfo(True, "Add extended info (seed, prompt) to filename when saving grid"),
|
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"grid_only_if_multiple": OptionInfo(True, "Do not save grids consisting of one picture"),
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"grid_prevent_empty_spots": OptionInfo(True, "Prevent empty spots in grid (when set to autodetect)"),
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"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}),
|
||||
"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(True, "Save a copy of image before doing face restoration."),
|
||||
"save_images_before_highres_fix": OptionInfo(True, "Save a copy of image before applying highres fix."),
|
||||
"save_images_before_color_correction": OptionInfo(True, "Save a copy of image before applying color correction to img2img results"),
|
||||
"save_mask": OptionInfo(False, "For inpainting, save a copy of the greyscale mask"),
|
||||
"save_mask_composite": OptionInfo(False, "For inpainting, save a masked composite"),
|
||||
"jpeg_quality": OptionInfo(85, "Quality for saved jpeg images", gr.Slider, {"minimum": 1, "maximum": 100, "step": 1}),
|
||||
"webp_lossless": OptionInfo(False, "Use lossless compression for webp images"),
|
||||
"img_max_size_mp": OptionInfo(200, "Maximum image size, in megapixels", gr.Number),
|
||||
"use_original_name_batch": OptionInfo(True, "Use original name for output filename during batch process in extras tab"),
|
||||
"use_upscaler_name_as_suffix": OptionInfo(True, "Use upscaler name as filename suffix in the extras tab"),
|
||||
"save_selected_only": OptionInfo(True, "When using 'Save' button, only save a single selected image"),
|
||||
"save_to_dirs": OptionInfo(False, "Save images to a subdirectory"),
|
||||
"grid_save_to_dirs": OptionInfo(False, "Save grids to a subdirectory"),
|
||||
"use_save_to_dirs_for_ui": OptionInfo(False, "When using \"Save\" button, save images to a subdirectory"),
|
||||
"directories_filename_pattern": OptionInfo("[date]", "Directory name pattern", component_args=hide_dirs),
|
||||
"directories_max_prompt_words": OptionInfo(8, "Max prompt words for [prompt_words] pattern", gr.Slider, {"minimum": 1, "maximum": 20, "step": 1, **hide_dirs}),
|
||||
"temp_dir": OptionInfo("", "Directory for temporary images; leave empty for default"),
|
||||
"clean_temp_dir_at_start": OptionInfo(True, "Cleanup non-default temporary directory when starting webui"),
|
||||
}))
|
||||
|
||||
options_templates.update(options_section(('saving-paths', "Image Paths"), {
|
||||
"outdir_samples": OptionInfo("", "Output directory for images; if empty, defaults to three directories below", component_args=hide_dirs),
|
||||
"outdir_txt2img_samples": OptionInfo("outputs/text", 'Output directory for txt2img images', component_args=hide_dirs),
|
||||
"outdir_img2img_samples": OptionInfo("outputs/image", 'Output directory for img2img images', component_args=hide_dirs),
|
||||
"outdir_extras_samples": OptionInfo("outputs/extras", '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/grids", 'Output directory for txt2img grids', component_args=hide_dirs),
|
||||
"outdir_img2img_grids": OptionInfo("outputs/grids", 'Output directory for img2img grids', component_args=hide_dirs),
|
||||
"outdir_save": OptionInfo("outputs/save", "Directory for saving images using the Save button", component_args=hide_dirs),
|
||||
}))
|
||||
|
||||
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(["R-ESRGAN 4x+", "R-ESRGAN 4x+ Anime6B"], "Select which Real-ESRGAN models to show in the web UI. (Requires restart)", gr.CheckboxGroup, lambda: {"choices": shared_items.realesrgan_models_names()}),
|
||||
"upscaler_for_img2img": OptionInfo("SwinIR_4x", "Upscaler for img2img", gr.Dropdown, lambda: {"choices": [x.name for x in sd_upscalers]}),
|
||||
"use_old_hires_fix_width_height": OptionInfo(False, "For hires fix, use width/height sliders to set final resolution rather than first pass (disables Upscale by, Resize width/height to)."),
|
||||
}))
|
||||
|
||||
options_templates.update(options_section(('face-restoration', "Face restoration"), {
|
||||
"face_restoration_model": OptionInfo("CodeFormer", "Face restoration model", gr.Radio, lambda: {"choices": [x.name() for x in face_restorers]}),
|
||||
"code_former_weight": OptionInfo(0.2, "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"),
|
||||
}))
|
||||
|
||||
options_templates.update(options_section(('system', "System"), {
|
||||
"memmon_poll_rate": OptionInfo(2, "VRAM usage polls per second during generation. Set to 0 to disable.", gr.Slider, {"minimum": 0, "maximum": 40, "step": 1}),
|
||||
"multiple_tqdm": OptionInfo(False, "Add a second progress bar to the console that shows progress for an entire job."),
|
||||
"print_hypernet_extra": OptionInfo(False, "Print extra hypernetwork information to console."),
|
||||
}))
|
||||
|
||||
options_templates.update(options_section(('training', "Training"), {
|
||||
"unload_models_when_training": OptionInfo(False, "Move VAE and CLIP to RAM when training if possible. Saves VRAM."),
|
||||
"pin_memory": OptionInfo(True, "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_training_settings_to_txt": OptionInfo(True, "Save textual inversion and hypernet settings to a text file whenever training starts."),
|
||||
"dataset_filename_word_regex": OptionInfo("", "Filename word regex"),
|
||||
"dataset_filename_join_string": OptionInfo(" ", "Filename join string"),
|
||||
"training_image_repeats_per_epoch": OptionInfo(1, "Number of repeats for a single input image per epoch; used only for displaying epoch number", gr.Number, {"precision": 0}),
|
||||
"training_write_csv_every": OptionInfo(0, "Save an csv containing the loss to log directory every N steps, 0 to disable"),
|
||||
"training_enable_tensorboard": OptionInfo(False, "Enable tensorboard logging."),
|
||||
"training_tensorboard_save_images": OptionInfo(False, "Save generated images within tensorboard."),
|
||||
"training_tensorboard_flush_every": OptionInfo(120, "How often, in seconds, to flush the pending tensorboard events and summaries to disk."),
|
||||
}))
|
||||
|
||||
options_templates.update(options_section(('interrogate', "Interrogate Options"), {
|
||||
"interrogate_keep_models_in_memory": OptionInfo(False, "Interrogate: keep models in VRAM"),
|
||||
"interrogate_return_ranks": OptionInfo(False, "Interrogate: include ranks of model tags matches in results (Has no effect on caption-based interrogators)."),
|
||||
"interrogate_return_ranks": OptionInfo(True, "Interrogate: include ranks of model tags matches in results (Has no effect on caption-based interrogators)."),
|
||||
"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, "CLIP: maximum number of lines in text file (0 = No limit)"),
|
||||
"interrogate_clip_skip_categories": OptionInfo([], "CLIP: skip inquire categories", gr.CheckboxGroup, lambda: {"choices": modules.interrogate.category_types()}, refresh=modules.interrogate.category_types),
|
||||
"interrogate_deepbooru_score_threshold": OptionInfo(0.5, "Interrogate: deepbooru score threshold", gr.Slider, {"minimum": 0, "maximum": 1, "step": 0.01}),
|
||||
"deepbooru_sort_alpha": OptionInfo(True, "Interrogate: deepbooru sort alphabetically"),
|
||||
"interrogate_clip_min_length": OptionInfo(32, "Interrogate: minimum description length (excluding artists, etc..)", gr.Slider, {"minimum": 1, "maximum": 128, "step": 1}),
|
||||
"interrogate_clip_max_length": OptionInfo(192, "Interrogate: maximum description length", gr.Slider, {"minimum": 1, "maximum": 256, "step": 1}),
|
||||
"interrogate_clip_dict_limit": OptionInfo(2048, "CLIP: maximum number of lines in text file (0 = No limit)"),
|
||||
"interrogate_clip_skip_categories": OptionInfo(["artists", "movements", "flavors"], "CLIP: skip inquire categories", gr.CheckboxGroup, lambda: {"choices": modules.interrogate.category_types()}, refresh=modules.interrogate.category_types),
|
||||
"interrogate_deepbooru_score_threshold": OptionInfo(0.65, "Interrogate: deepbooru score threshold", gr.Slider, {"minimum": 0, "maximum": 1, "step": 0.01}),
|
||||
"deepbooru_sort_alpha": OptionInfo(False, "Interrogate: deepbooru sort alphabetically"),
|
||||
"deepbooru_use_spaces": OptionInfo(False, "use spaces for tags in deepbooru"),
|
||||
"deepbooru_escape": OptionInfo(True, "escape (\\) brackets in deepbooru (so they are used as literal brackets and not for emphasis)"),
|
||||
"deepbooru_filter_tags": OptionInfo("", "filter out those tags from deepbooru output (separated by comma)"),
|
||||
@@ -393,31 +391,28 @@ options_templates.update(options_section(('ui', "User interface"), {
|
||||
"font": OptionInfo("", "Font for image grids that have text"),
|
||||
"js_modal_lightbox": OptionInfo(True, "Enable full page image viewer"),
|
||||
"js_modal_lightbox_initially_zoomed": OptionInfo(True, "Show images zoomed in by default in full page image viewer"),
|
||||
"show_progress_in_title": OptionInfo(True, "Show generation progress in window title."),
|
||||
"samplers_in_dropdown": OptionInfo(True, "Use dropdown for sampler selection instead of radio group"),
|
||||
"dimensions_and_batch_together": OptionInfo(True, "Show Width/Height and Batch sliders in same row"),
|
||||
"show_progress_in_title": OptionInfo(False, "Show generation progress in window title."),
|
||||
"keyedit_precision_attention": OptionInfo(0.1, "Ctrl+up/down precision when editing (attention:1.1)", gr.Slider, {"minimum": 0.01, "maximum": 0.2, "step": 0.001}),
|
||||
"keyedit_precision_extra": OptionInfo(0.05, "Ctrl+up/down precision when editing <extra networks:0.9>", gr.Slider, {"minimum": 0.01, "maximum": 0.2, "step": 0.001}),
|
||||
"quicksettings": OptionInfo("sd_model_checkpoint", "Quicksettings list"),
|
||||
"hidden_tabs": OptionInfo([], "Hidden UI tabs (requires restart)", ui_components.DropdownMulti, lambda: {"choices": [x for x in tab_names]}),
|
||||
"ui_reorder": OptionInfo(", ".join(ui_reorder_categories), "txt2img/img2img UI item order"),
|
||||
"ui_extra_networks_tab_reorder": OptionInfo("", "Extra networks tab order"),
|
||||
"localization": OptionInfo("None", "Localization (requires restart)", gr.Dropdown, lambda: {"choices": ["None"] + list(localization.localizations.keys())}, refresh=lambda: localization.list_localizations(cmd_opts.localizations_dir)),
|
||||
"gradio_theme": OptionInfo("Default", "Gradio theme (requires restart)", gr.Dropdown, lambda: {"choices": ["Default"] + gradio_hf_hub_themes})
|
||||
"gradio_theme": OptionInfo("Default", "Gradio theme (requires restart)", gr.Dropdown, lambda: {"choices": ["Default"] + gradio_hf_hub_themes}),
|
||||
}))
|
||||
|
||||
options_templates.update(options_section(('ui', "Live previews"), {
|
||||
"show_progressbar": OptionInfo(True, "Show progressbar"),
|
||||
"live_previews_enable": OptionInfo(True, "Show live previews of the created image"),
|
||||
"show_progress_grid": OptionInfo(True, "Show previews of all images generated in a batch as a grid"),
|
||||
"show_progress_every_n_steps": OptionInfo(10, "Show new live preview image every N sampling steps. Set to -1 to show after completion of batch.", gr.Slider, {"minimum": -1, "maximum": 32, "step": 1}),
|
||||
"show_progress_type": OptionInfo("Approx NN", "Image creation progress preview mode", gr.Radio, {"choices": ["Full", "Approx NN", "Approx cheap"]}),
|
||||
"live_preview_content": OptionInfo("Prompt", "Live preview subject", gr.Radio, {"choices": ["Combined", "Prompt", "Negative prompt"]}),
|
||||
"show_progress_every_n_steps": OptionInfo(-1, "Show new live preview image every N sampling steps. Set to -1 to show after completion of batch.", gr.Slider, {"minimum": -1, "maximum": 32, "step": 1}),
|
||||
"show_progress_type": OptionInfo("Full", "Image creation progress preview mode", gr.Radio, {"choices": ["Full", "Approx NN", "Approx cheap"]}),
|
||||
"live_preview_content": OptionInfo("Combined", "Live preview subject", gr.Radio, {"choices": ["Combined", "Prompt", "Negative prompt"]}),
|
||||
"live_preview_refresh_period": OptionInfo(1000, "Progressbar/preview update period, in milliseconds")
|
||||
}))
|
||||
|
||||
options_templates.update(options_section(('sampler-params', "Sampler parameters"), {
|
||||
"hide_samplers": OptionInfo([], "Hide samplers in user interface (requires restart)", gr.CheckboxGroup, lambda: {"choices": [x.name for x in list_samplers()]}),
|
||||
"hide_samplers": OptionInfo(["Euler", "LMS", "Heun", "DPM2", "DPM2 a", "DPM++ 2M", "DPM fast", "DPM adaptive", "DPM++ 2S a Karras", "DPM++ 2S a", "DPM++ SDE Karras", "DPM2 a Karras", "LMS Karras"], "Hide samplers in user interface (requires restart)", gr.CheckboxGroup, lambda: {"choices": [x.name for x in list_samplers()]}),
|
||||
"eta_ddim": OptionInfo(0.0, "eta (noise multiplier) for DDIM", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),
|
||||
"eta_ancestral": OptionInfo(1.0, "eta (noise multiplier) for ancestral samplers", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),
|
||||
"ddim_discretize": OptionInfo('uniform', "img2img DDIM discretize", gr.Radio, {"choices": ['uniform', 'quad']}),
|
||||
@@ -439,7 +434,8 @@ options_templates.update(options_section(('postprocessing', "Postprocessing"), {
|
||||
}))
|
||||
|
||||
options_templates.update(options_section((None, "Hidden options"), {
|
||||
"disabled_extensions": OptionInfo([], "Disable those extensions"),
|
||||
"disabled_extensions": OptionInfo([], "Disable these extensions"),
|
||||
"disable_all_extensions": OptionInfo("none", "Disable all extensions (preserves the list of disabled extensions)", gr.Radio, {"choices": ["none", "extra", "all"]}),
|
||||
"sd_checkpoint_hash": OptionInfo("", "SHA256 hash of the current checkpoint"),
|
||||
}))
|
||||
|
||||
@@ -536,11 +532,11 @@ class Options:
|
||||
for k, v in self.data.items():
|
||||
info = self.data_labels.get(k, None)
|
||||
if info is not None and not self.same_type(info.default, v):
|
||||
print(f"Warning: bad setting value: {k}: {v} ({type(v).__name__}; expected {type(info.default).__name__})", file=sys.stderr)
|
||||
log.error(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.\nSettings file: {filename}\nEither fix the file, or delete it and restart.", file=sys.stderr)
|
||||
log.error(f"The program is likely to not work with bad settings.\nSettings file: {filename}\nEither fix the file, or delete it and restart.", file=sys.stderr)
|
||||
|
||||
def onchange(self, key, func, call=True):
|
||||
item = self.data_labels.get(key)
|
||||
@@ -592,9 +588,21 @@ class Options:
|
||||
|
||||
|
||||
opts = Options()
|
||||
|
||||
batch_cond_uncond = opts.always_batch_cond_uncond or not (cmd_opts.lowvram or cmd_opts.medvram)
|
||||
parallel_processing_allowed = not cmd_opts.lowvram and not cmd_opts.medvram
|
||||
xformers_available = False
|
||||
config_filename = cmd_opts.ui_settings_file
|
||||
|
||||
os.makedirs(opts.hypernetwork_dir, exist_ok=True)
|
||||
hypernetworks = {}
|
||||
loaded_hypernetworks = []
|
||||
|
||||
if os.path.exists(config_filename):
|
||||
opts.load(config_filename)
|
||||
|
||||
cmd_opts = cmd_args.compatibility_args(opts, cmd_opts)
|
||||
|
||||
settings_components = None
|
||||
"""assinged from ui.py, a mapping on setting anmes to gradio components repsponsible for those settings"""
|
||||
|
||||
@@ -608,12 +616,6 @@ latent_upscale_modes = {
|
||||
"Latent (nearest-exact)": {"mode": "nearest-exact", "antialias": False},
|
||||
}
|
||||
|
||||
sd_upscalers = []
|
||||
|
||||
sd_model = None
|
||||
|
||||
clip_model = None
|
||||
|
||||
progress_print_out = sys.stdout
|
||||
|
||||
gradio_theme = gr.themes.Base()
|
||||
@@ -641,7 +643,7 @@ class TotalTQDM:
|
||||
|
||||
def reset(self):
|
||||
self._tqdm = tqdm.tqdm(
|
||||
desc="Total progress",
|
||||
desc="Total",
|
||||
total=state.job_count * state.sampling_steps,
|
||||
position=1,
|
||||
file=progress_print_out
|
||||
@@ -675,12 +677,12 @@ mem_mon.start()
|
||||
|
||||
|
||||
def listfiles(dirname):
|
||||
filenames = [os.path.join(dirname, x) for x in sorted(os.listdir(dirname)) if not x.startswith(".")]
|
||||
filenames = [os.path.join(dirname, x) for x in sorted(os.listdir(dirname), key=str.lower) if not x.startswith(".")]
|
||||
return [file for file in filenames if os.path.isfile(file)]
|
||||
|
||||
|
||||
def html_path(filename):
|
||||
return os.path.join(script_path, "html", filename)
|
||||
return os.path.join(paths.script_path, "html", filename)
|
||||
|
||||
|
||||
def html(filename):
|
||||
|
||||
Reference in New Issue
Block a user