Merge pull request #7199 from maxaudron/feature/configurable-data-dir
Add flag to store user data sepperate from source code
This commit is contained in:
commit
ce72af87d3
@ -8,7 +8,7 @@ import torch
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import modules.face_restoration
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import modules.shared
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from modules import shared, devices, modelloader
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from modules.paths import script_path, models_path
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from modules.paths import models_path
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# codeformer people made a choice to include modified basicsr library to their project which makes
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# it utterly impossible to use it alongside with other libraries that also use basicsr, like GFPGAN.
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@ -7,9 +7,11 @@ import git
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from modules import paths, shared
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extensions = []
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extensions_dir = os.path.join(paths.script_path, "extensions")
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extensions_dir = os.path.join(paths.data_path, "extensions")
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extensions_builtin_dir = os.path.join(paths.script_path, "extensions-builtin")
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if not os.path.exists(extensions_dir):
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os.makedirs(extensions_dir)
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def active():
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return [x for x in extensions if x.enabled]
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@ -6,7 +6,7 @@ import re
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from pathlib import Path
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import gradio as gr
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from modules.shared import script_path
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from modules.paths import data_path
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from modules import shared, ui_tempdir, script_callbacks
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import tempfile
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from PIL import Image
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@ -289,7 +289,7 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model
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def connect_paste(button, paste_fields, input_comp, jsfunc=None):
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def paste_func(prompt):
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if not prompt and not shared.cmd_opts.hide_ui_dir_config:
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filename = os.path.join(script_path, "params.txt")
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filename = os.path.join(data_path, "params.txt")
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if os.path.exists(filename):
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with open(filename, "r", encoding="utf8") as file:
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prompt = file.read()
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@ -6,12 +6,11 @@ import facexlib
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import gfpgan
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import modules.face_restoration
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from modules import shared, devices, modelloader
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from modules.paths import models_path
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from modules import paths, shared, devices, modelloader
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model_dir = "GFPGAN"
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user_path = None
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model_path = os.path.join(models_path, model_dir)
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model_path = os.path.join(paths.models_path, model_dir)
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model_url = "https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.4.pth"
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have_gfpgan = False
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loaded_gfpgan_model = None
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@ -4,8 +4,10 @@ import os.path
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import filelock
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from modules.paths import data_path
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cache_filename = "cache.json"
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cache_filename = os.path.join(data_path, "cache.json")
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cache_data = None
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@ -12,7 +12,7 @@ from torchvision import transforms
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from torchvision.transforms.functional import InterpolationMode
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import modules.shared as shared
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from modules import devices, paths, lowvram, modelloader, errors
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from modules import devices, paths, shared, lowvram, modelloader, errors
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blip_image_eval_size = 384
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clip_model_name = 'ViT-L/14'
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@ -4,7 +4,15 @@ import sys
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import modules.safe
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script_path = os.path.dirname(os.path.dirname(os.path.realpath(__file__)))
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models_path = os.path.join(script_path, "models")
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# Parse the --data-dir flag first so we can use it as a base for our other argument default values
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parser = argparse.ArgumentParser()
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parser.add_argument("--data-dir", type=str, default=os.path.dirname(os.path.dirname(os.path.realpath(__file__))), help="base path where all user data is stored",)
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cmd_opts_pre = parser.parse_known_args()[0]
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data_path = cmd_opts_pre.data_dir
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models_path = os.path.join(data_path, "models")
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# data_path = cmd_opts_pre.data
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sys.path.insert(0, script_path)
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# search for directory of stable diffusion in following places
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@ -17,6 +17,7 @@ from modules import devices, prompt_parser, masking, sd_samplers, lowvram, gener
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from modules.sd_hijack import model_hijack
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from modules.shared import opts, cmd_opts, state
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import modules.shared as shared
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import modules.paths as paths
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import modules.face_restoration
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import modules.images as images
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import modules.styles
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@ -584,7 +585,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
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if not p.disable_extra_networks:
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extra_networks.activate(p, extra_network_data)
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with open(os.path.join(shared.script_path, "params.txt"), "w", encoding="utf8") as file:
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with open(os.path.join(paths.data_path, "params.txt"), "w", encoding="utf8") as file:
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processed = Processed(p, [], p.seed, "")
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file.write(processed.infotext(p, 0))
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@ -1,16 +1,14 @@
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import os
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import sys
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import traceback
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import importlib.util
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from types import ModuleType
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def load_module(path):
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with open(path, "r", encoding="utf8") as file:
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text = file.read()
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compiled = compile(text, path, 'exec')
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module = ModuleType(os.path.basename(path))
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exec(compiled, module.__dict__)
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module_spec = importlib.util.spec_from_file_location(os.path.basename(path), path)
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module = importlib.util.module_from_spec(module_spec)
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module_spec.loader.exec_module(module)
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return module
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@ -12,13 +12,13 @@ import ldm.modules.midas as midas
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from ldm.util import instantiate_from_config
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from modules import shared, modelloader, devices, script_callbacks, sd_vae, sd_disable_initialization, errors, hashes, sd_models_config
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from modules import paths, shared, modelloader, devices, script_callbacks, sd_vae, sd_disable_initialization, errors, hashes, sd_models_config
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from modules.paths import models_path
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from modules.sd_hijack_inpainting import do_inpainting_hijack
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from modules.timer import Timer
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model_dir = "Stable-diffusion"
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model_path = os.path.abspath(os.path.join(models_path, model_dir))
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model_path = os.path.abspath(os.path.join(paths.models_path, model_dir))
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checkpoints_list = {}
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checkpoint_alisases = {}
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@ -307,7 +307,7 @@ def enable_midas_autodownload():
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location automatically.
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"""
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midas_path = os.path.join(models_path, 'midas')
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midas_path = os.path.join(paths.models_path, 'midas')
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# stable-diffusion-stability-ai hard-codes the midas model path to
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# a location that differs from where other scripts using this model look.
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@ -3,13 +3,12 @@ import safetensors.torch
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import os
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import collections
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from collections import namedtuple
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from modules import shared, devices, script_callbacks, sd_models
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from modules.paths import models_path
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from modules import paths, shared, devices, script_callbacks, sd_models
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import glob
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from copy import deepcopy
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vae_path = os.path.abspath(os.path.join(models_path, "VAE"))
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vae_path = os.path.abspath(os.path.join(paths.models_path, "VAE"))
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vae_ignore_keys = {"model_ema.decay", "model_ema.num_updates"}
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vae_dict = {}
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@ -14,7 +14,7 @@ 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, extensions, script_loading, errors, ui_components, shared_items
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from modules.paths import models_path, script_path
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from modules.paths import models_path, script_path, data_path
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demo = None
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@ -25,6 +25,7 @@ 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()
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parser.add_argument("--data-dir", type=str, default=os.path.dirname(os.path.dirname(os.path.realpath(__file__))), help="base path where all user data is stored",)
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parser.add_argument("--config", type=str, default=sd_default_config, 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; if specified, this checkpoint will be added to the list of checkpoints and loaded",)
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parser.add_argument("--ckpt-dir", type=str, default=None, help="Path to directory with stable diffusion checkpoints")
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@ -35,7 +36,7 @@ parser.add_argument("--no-half", action='store_true', help="do not switch the mo
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parser.add_argument("--no-half-vae", action='store_true', help="do not switch the VAE 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("--embeddings-dir", type=str, default=os.path.join(data_path, 'embeddings'), help="embeddings directory for textual inversion (default: embeddings)")
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parser.add_argument("--textual-inversion-templates-dir", type=str, default=os.path.join(script_path, 'textual_inversion_templates'), help="directory with textual inversion templates")
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parser.add_argument("--hypernetwork-dir", type=str, default=os.path.join(models_path, 'hypernetworks'), help="hypernetwork directory")
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parser.add_argument("--localizations-dir", type=str, default=os.path.join(script_path, 'localizations'), help="localizations directory")
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@ -74,16 +75,16 @@ parser.add_argument("--use-cpu", nargs='+', help="use CPU as torch device for sp
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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("--ui-config-file", type=str, help="filename to use for ui configuration", default=os.path.join(data_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("--freeze-settings", action='store_true', help="disable editing settings", 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("--ui-settings-file", type=str, help="filename to use for ui settings", default=os.path.join(data_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("--gradio-img2img-tool", type=str, help='does not do anything')
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parser.add_argument("--gradio-inpaint-tool", type=str, help="does not do anything")
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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("--styles-file", type=str, help="filename to use for styles", default=os.path.join(data_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("--theme", type=str, help="launches the UI with light or dark theme", default=None)
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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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@ -6,8 +6,7 @@ import sys
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import tqdm
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import time
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from modules import shared, images, deepbooru
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from modules.paths import models_path
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from modules import paths, shared, images, deepbooru
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from modules.shared import opts, cmd_opts
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from modules.textual_inversion import autocrop
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@ -199,7 +198,7 @@ def preprocess_work(process_src, process_dst, process_width, process_height, pre
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dnn_model_path = None
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try:
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dnn_model_path = autocrop.download_and_cache_models(os.path.join(models_path, "opencv"))
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dnn_model_path = autocrop.download_and_cache_models(os.path.join(paths.models_path, "opencv"))
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except Exception as e:
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print("Unable to load face detection model for auto crop selection. Falling back to lower quality haar method.", e)
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@ -21,7 +21,7 @@ from modules.call_queue import wrap_gradio_gpu_call, wrap_queued_call, wrap_grad
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from modules import sd_hijack, sd_models, localization, script_callbacks, ui_extensions, deepbooru, sd_vae, extra_networks, postprocessing, ui_components, ui_common, ui_postprocessing
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from modules.ui_components import FormRow, FormGroup, ToolButton, FormHTML
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from modules.paths import script_path
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from modules.paths import script_path, data_path
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from modules.shared import opts, cmd_opts, restricted_opts
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@ -1510,8 +1510,8 @@ def create_ui():
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with open(cssfile, "r", encoding="utf8") as file:
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css += file.read() + "\n"
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if os.path.exists(os.path.join(script_path, "user.css")):
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with open(os.path.join(script_path, "user.css"), "r", encoding="utf8") as file:
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if os.path.exists(os.path.join(data_path, "user.css")):
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with open(os.path.join(data_path, "user.css"), "r", encoding="utf8") as file:
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css += file.read() + "\n"
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if not cmd_opts.no_progressbar_hiding:
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@ -132,7 +132,7 @@ def install_extension_from_url(dirname, url):
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normalized_url = normalize_git_url(url)
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assert len([x for x in extensions.extensions if normalize_git_url(x.remote) == normalized_url]) == 0, 'Extension with this URL is already installed'
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tmpdir = os.path.join(paths.script_path, "tmp", dirname)
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tmpdir = os.path.join(paths.data_path, "tmp", dirname)
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try:
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shutil.rmtree(tmpdir, True)
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@ -11,7 +11,6 @@ from modules import modelloader, shared
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LANCZOS = (Image.Resampling.LANCZOS if hasattr(Image, 'Resampling') else Image.LANCZOS)
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NEAREST = (Image.Resampling.NEAREST if hasattr(Image, 'Resampling') else Image.NEAREST)
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from modules.paths import models_path
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class Upscaler:
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@ -39,7 +38,7 @@ class Upscaler:
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self.mod_scale = None
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if self.model_path is None and self.name:
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self.model_path = os.path.join(models_path, self.name)
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self.model_path = os.path.join(shared.models_path, self.name)
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if self.model_path and create_dirs:
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os.makedirs(self.model_path, exist_ok=True)
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@ -143,4 +142,4 @@ class UpscalerNearest(Upscaler):
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def __init__(self, dirname=None):
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super().__init__(False)
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self.name = "Nearest"
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self.scalers = [UpscalerData("Nearest", None, self)]
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self.scalers = [UpscalerData("Nearest", None, self)]
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1
webui.py
1
webui.py
@ -15,7 +15,6 @@ logging.getLogger("xformers").addFilter(lambda record: 'A matching Triton is not
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from modules import import_hook, errors, extra_networks
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from modules import extra_networks_hypernet, ui_extra_networks_hypernets, ui_extra_networks_textual_inversion
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from modules.call_queue import wrap_queued_call, queue_lock, wrap_gradio_gpu_call
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from modules.paths import script_path
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import torch
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