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import argparse | |
import datetime | |
import json | |
import os | |
import sys | |
import gradio as gr | |
import tqdm | |
import modules.artists | |
import modules.interrogate | |
import modules.memmon | |
import modules.sd_models | |
import modules.styles | |
import modules.devices as devices | |
from modules import sd_samplers, hypernetwork | |
from modules.paths import models_path, script_path, sd_path | |
sd_model_file = os.path.join(script_path, 'model.ckpt') | |
default_sd_model_file = sd_model_file | |
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",) | |
parser.add_argument("--ckpt", type=str, default=sd_model_file, help="path to checkpoint of stable diffusion model; if specified, this checkpoint will be added to the list of checkpoints and loaded",) | |
parser.add_argument("--ckpt-dir", type=str, default=None, help="Path to directory with stable diffusion checkpoints") | |
parser.add_argument("--gfpgan-dir", type=str, help="GFPGAN directory", default=('./src/gfpgan' if os.path.exists('./src/gfpgan') else './GFPGAN')) | |
parser.add_argument("--gfpgan-model", type=str, help="GFPGAN model file name", default=None) | |
parser.add_argument("--no-half", action='store_true', help="do not switch the model to 16-bit floats") | |
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)") | |
parser.add_argument("--max-batch-count", type=int, default=16, help="maximum batch count value for the UI") | |
parser.add_argument("--embeddings-dir", type=str, default=os.path.join(script_path, 'embeddings'), help="embeddings directory for textual inversion (default: embeddings)") | |
parser.add_argument("--allow-code", action='store_true', help="allow custom script execution from webui") | |
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") | |
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") | |
parser.add_argument("--unload-gfpgan", action='store_true', help="does not do anything.") | |
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)") | |
parser.add_argument("--codeformer-models-path", type=str, help="Path to directory with codeformer model file(s).", default=os.path.join(models_path, 'Codeformer')) | |
parser.add_argument("--gfpgan-models-path", type=str, help="Path to directory with GFPGAN model file(s).", default=os.path.join(models_path, 'GFPGAN')) | |
parser.add_argument("--esrgan-models-path", type=str, help="Path to directory with ESRGAN model file(s).", default=os.path.join(models_path, 'ESRGAN')) | |
parser.add_argument("--bsrgan-models-path", type=str, help="Path to directory with BSRGAN model file(s).", default=os.path.join(models_path, 'BSRGAN')) | |
parser.add_argument("--realesrgan-models-path", type=str, help="Path to directory with RealESRGAN model file(s).", default=os.path.join(models_path, 'RealESRGAN')) | |
parser.add_argument("--scunet-models-path", type=str, help="Path to directory with ScuNET model file(s).", default=os.path.join(models_path, 'ScuNET')) | |
parser.add_argument("--swinir-models-path", type=str, help="Path to directory with SwinIR model file(s).", default=os.path.join(models_path, 'SwinIR')) | |
parser.add_argument("--ldsr-models-path", type=str, help="Path to directory with LDSR model file(s).", default=os.path.join(models_path, 'LDSR')) | |
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") | |
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") | |
parser.add_argument("--use-cpu", nargs='+',choices=['SD', 'GFPGAN', 'BSRGAN', 'ESRGAN', 'SCUNet', 'CodeFormer'], help="use CPU as torch device for specified modules", default=[]) | |
parser.add_argument("--listen", action='store_true', help="launch gradio with 0.0.0.0 as server name, allowing to respond to network requests") | |
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) | |
parser.add_argument("--show-negative-prompt", action='store_true', help="does not do anything", default=False) | |
parser.add_argument("--ui-config-file", type=str, help="filename to use for ui configuration", default=os.path.join(script_path, 'ui-config.json')) | |
parser.add_argument("--hide-ui-dir-config", action='store_true', help="hide directory configuration from webui", default=False) | |
parser.add_argument("--ui-settings-file", type=str, help="filename to use for ui settings", default=os.path.join(script_path, 'config.json')) | |
parser.add_argument("--gradio-debug", action='store_true', help="launch gradio with --debug option") | |
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) | |
parser.add_argument("--gradio-img2img-tool", type=str, help='gradio image uploader tool: can be either editor for ctopping, or color-sketch for drawing', choices=["color-sketch", "editor"], default="editor") | |
parser.add_argument("--opt-channelslast", action='store_true', help="change memory type for stable diffusion to channels last") | |
parser.add_argument("--styles-file", type=str, help="filename to use for styles", default=os.path.join(script_path, 'styles.csv')) | |
parser.add_argument("--autolaunch", action='store_true', help="open the webui URL in the system's default browser upon launch", default=False) | |
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) | |
parser.add_argument("--disable-console-progressbars", action='store_true', help="do not output progressbars to console", default=False) | |
parser.add_argument("--enable-console-prompts", action='store_true', help="print prompts to console when generating with txt2img and img2img", default=False) | |
cmd_opts = parser.parse_args() | |
devices.device, devices.device_gfpgan, devices.device_bsrgan, devices.device_esrgan, devices.device_scunet, devices.device_codeformer = \ | |
(devices.cpu if x in cmd_opts.use_cpu else devices.get_optimal_device() for x in ['SD', 'GFPGAN', 'BSRGAN', 'ESRGAN', 'SCUNet', 'CodeFormer']) | |
device = devices.device | |
batch_cond_uncond = cmd_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 | |
config_filename = cmd_opts.ui_settings_file | |
hypernetworks = hypernetwork.load_hypernetworks(os.path.join(models_path, 'hypernetworks')) | |
def selected_hypernetwork(): | |
return hypernetworks.get(opts.sd_hypernetwork, None) | |
class State: | |
interrupted = False | |
job = "" | |
job_no = 0 | |
job_count = 0 | |
job_timestamp = '0' | |
sampling_step = 0 | |
sampling_steps = 0 | |
current_latent = None | |
current_image = None | |
current_image_sampling_step = 0 | |
textinfo = None | |
def interrupt(self): | |
self.interrupted = True | |
def nextjob(self): | |
self.job_no += 1 | |
self.sampling_step = 0 | |
self.current_image_sampling_step = 0 | |
def get_job_timestamp(self): | |
return datetime.datetime.now().strftime("%Y%m%d%H%M%S") # shouldn't this return job_timestamp? | |
state = State() | |
artist_db = modules.artists.ArtistsDatabase(os.path.join(script_path, 'artists.csv')) | |
styles_filename = cmd_opts.styles_file | |
prompt_styles = modules.styles.StyleDatabase(styles_filename) | |
interrogator = modules.interrogate.InterrogateModels("interrogate") | |
face_restorers = [] | |
# This was moved to webui.py with the other model "setup" calls. | |
# modules.sd_models.list_models() | |
def realesrgan_models_names(): | |
import modules.realesrgan_model | |
return [x.name for x in modules.realesrgan_model.get_realesrgan_models(None)] | |
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 | |
self.section = None | |
def options_section(section_identifer, options_dict): | |
for k, v in options_dict.items(): | |
v.section = section_identifer | |
return options_dict | |
hide_dirs = {"visible": not cmd_opts.hide_ui_dir_config} | |
options_templates = {} | |
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}), | |
"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."), | |
"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"), | |
"save_selected_only": OptionInfo(True, "When using 'Save' button, only save a single selected image"), | |
})) | |
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), | |
"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), | |
})) | |
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 a subdirectory"), | |
"use_save_to_dirs_for_ui": OptionInfo(False, "When using \"Save\" button, save images to a subdirectory"), | |
"directories_filename_pattern": OptionInfo("", "Directory name pattern"), | |
"directories_max_prompt_words": OptionInfo(8, "Max prompt words for [prompt_words] pattern", 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(["R-ESRGAN x4+", "R-ESRGAN x4+ Anime6B"], "Select which Real-ESRGAN 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}), | |
"upscaler_for_img2img": OptionInfo(None, "Upscaler for img2img", gr.Dropdown, lambda: {"choices": [x.name for x in sd_upscalers]}), | |
})) | |
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"), | |
})) | |
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."), | |
})) | |
options_templates.update(options_section(('sd', "Stable Diffusion"), { | |
"sd_model_checkpoint": OptionInfo(None, "Stable Diffusion checkpoint", gr.Dropdown, lambda: {"choices": modules.sd_models.checkpoint_tiles()}), | |
"sd_hypernetwork": OptionInfo("None", "Stable Diffusion finetune hypernetwork", gr.Dropdown, lambda: {"choices": ["None"] + [x for x in hypernetworks.keys()]}), | |
"img2img_color_correction": OptionInfo(False, "Apply color correction to img2img results to match original colors."), | |
"save_images_before_color_correction": OptionInfo(False, "Save a copy of image before applying color correction to img2img results"), | |
"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, "Emphasis: use (text) to make model pay more attention to text and [text] to make it pay less attention"), | |
"use_old_emphasis_implementation": OptionInfo(False, "Use old emphasis implementation. Can be useful to reproduce old seeds."), | |
"enable_batch_seeds": OptionInfo(True, "Make K-diffusion samplers produce same images in a batch as when making a single image"), | |
"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()}), | |
})) | |
options_templates.update(options_section(('interrogate', "Interrogate Options"), { | |
"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)"), | |
})) | |
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"), | |
"do_not_show_images": OptionInfo(False, "Do not show any images 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"), | |
"show_progress_in_title": OptionInfo(True, "Show generation progress in window title."), | |
})) | |
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 sd_samplers.all_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']}), | |
'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}), | |
})) | |
class Options: | |
data = None | |
data_labels = options_templates | |
typemap = {int: float} | |
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) | |
def same_type(self, x, y): | |
if x is None or y is None: | |
return True | |
type_x = self.typemap.get(type(x), type(x)) | |
type_y = self.typemap.get(type(y), type(y)) | |
return type_x == type_y | |
def load(self, filename): | |
with open(filename, "r", encoding="utf8") as file: | |
self.data = json.load(file) | |
bad_settings = 0 | |
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) | |
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) | |
def onchange(self, key, func): | |
item = self.data_labels.get(key) | |
item.onchange = func | |
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) | |
opts = Options() | |
if os.path.exists(config_filename): | |
opts.load(config_filename) | |
sd_upscalers = [] | |
sd_model = None | |
progress_print_out = sys.stdout | |
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 or cmd_opts.disable_console_progressbars: | |
return | |
if self._tqdm is None: | |
self.reset() | |
self._tqdm.update() | |
def updateTotal(self, new_total): | |
if not opts.multiple_tqdm or cmd_opts.disable_console_progressbars: | |
return | |
if self._tqdm is None: | |
self.reset() | |
self._tqdm.total=new_total | |
def clear(self): | |
if self._tqdm is not None: | |
self._tqdm.close() | |
self._tqdm = None | |
total_tqdm = TotalTQDM() | |
mem_mon = modules.memmon.MemUsageMonitor("MemMon", device, opts) | |
mem_mon.start() | |