add data-dir flag and set all user data directories based on it

modules/extensions.py

@@ -7,7 +7,7 @@ import git
 from modules import paths, shared
 
 extensions = []
-extensions_dir = os.path.join(paths.script_path, "extensions")
+extensions_dir = os.path.join(paths.data_path, "extensions")
 extensions_builtin_dir = os.path.join(paths.script_path, "extensions-builtin")
 
 

modules/generation_parameters_copypaste.py

@@ -6,7 +6,7 @@ import re
 from pathlib import Path
 
 import gradio as gr
-from modules.shared import script_path
+from modules.paths import data_path, script_path
 from modules import shared, ui_tempdir, script_callbacks
 import tempfile
 from PIL import Image
@@ -289,7 +289,7 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model
 def connect_paste(button, paste_fields, input_comp, jsfunc=None):
     def paste_func(prompt):
         if not prompt and not shared.cmd_opts.hide_ui_dir_config:
-            filename = os.path.join(script_path, "params.txt")
+            filename = os.path.join(data_path, "params.txt")
             if os.path.exists(filename):
                 with open(filename, "r", encoding="utf8") as file:
                     prompt = file.read()

modules/gfpgan_model.py

@@ -6,12 +6,11 @@ import facexlib
 import gfpgan
 
 import modules.face_restoration
-from modules import shared, devices, modelloader
-from modules.paths import models_path
+from modules import paths, shared, devices, modelloader
 
 model_dir = "GFPGAN"
 user_path = None
-model_path = os.path.join(models_path, model_dir)
+model_path = os.path.join(paths.models_path, model_dir)
 model_url = "https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.4.pth"
 have_gfpgan = False
 loaded_gfpgan_model = None

modules/hashes.py

@@ -4,8 +4,10 @@ import os.path
 
 import filelock
 
+from modules.paths import data_path
 
-cache_filename = "cache.json"
+
+cache_filename = os.path.join(data_path, "cache.json")
 cache_data = None
 
 

modules/interrogate.py

@@ -12,7 +12,7 @@ from torchvision import transforms
 from torchvision.transforms.functional import InterpolationMode
 
 import modules.shared as shared
-from modules import devices, paths, lowvram, modelloader, errors
+from modules import devices, paths, shared, lowvram, modelloader, errors
 
 blip_image_eval_size = 384
 clip_model_name = 'ViT-L/14'

modules/paths.py

@@ -4,7 +4,15 @@ import sys
 import modules.safe
 
 script_path = os.path.dirname(os.path.dirname(os.path.realpath(__file__)))
-models_path = os.path.join(script_path, "models")
+
+# Parse the --data-dir flag first so we can use it as a base for our other argument default values
+parser = argparse.ArgumentParser()
+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",)
+cmd_opts_pre = parser.parse_known_args()[0]
+data_path = cmd_opts_pre.data_dir
+models_path = os.path.join(data_path, "models")
+
+# data_path = cmd_opts_pre.data
 sys.path.insert(0, script_path)
 
 # search for directory of stable diffusion in following places

modules/processing.py

@@ -17,6 +17,7 @@ from modules import devices, prompt_parser, masking, sd_samplers, lowvram, gener
 from modules.sd_hijack import model_hijack
 from modules.shared import opts, cmd_opts, state
 import modules.shared as shared
+import modules.paths as paths
 import modules.face_restoration
 import modules.images as images
 import modules.styles
@@ -584,7 +585,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
             if not p.disable_extra_networks:
                 extra_networks.activate(p, extra_network_data)
 
-        with open(os.path.join(shared.script_path, "params.txt"), "w", encoding="utf8") as file:
+        with open(os.path.join(paths.data_path, "params.txt"), "w", encoding="utf8") as file:
             processed = Processed(p, [], p.seed, "")
             file.write(processed.infotext(p, 0))
 

modules/sd_models.py

@@ -12,13 +12,13 @@ import ldm.modules.midas as midas
 
 from ldm.util import instantiate_from_config
 
-from modules import shared, modelloader, devices, script_callbacks, sd_vae, sd_disable_initialization, errors, hashes, sd_models_config
+from modules import paths, shared, modelloader, devices, script_callbacks, sd_vae, sd_disable_initialization, errors, hashes, sd_models_config
 from modules.paths import models_path
 from modules.sd_hijack_inpainting import do_inpainting_hijack
 from modules.timer import Timer
 
 model_dir = "Stable-diffusion"
-model_path = os.path.abspath(os.path.join(models_path, model_dir))
+model_path = os.path.abspath(os.path.join(paths.models_path, model_dir))
 
 checkpoints_list = {}
 checkpoint_alisases = {}
@@ -307,7 +307,7 @@ def enable_midas_autodownload():
     location automatically.
     """
 
-    midas_path = os.path.join(models_path, 'midas')
+    midas_path = os.path.join(paths.models_path, 'midas')
 
     # stable-diffusion-stability-ai hard-codes the midas model path to
     # a location that differs from where other scripts using this model look.

modules/sd_vae.py

@@ -3,13 +3,12 @@ import safetensors.torch
 import os
 import collections
 from collections import namedtuple
-from modules import shared, devices, script_callbacks, sd_models
-from modules.paths import models_path
+from modules import paths, shared, devices, script_callbacks, sd_models
 import glob
 from copy import deepcopy
 
 
-vae_path = os.path.abspath(os.path.join(models_path, "VAE"))
+vae_path = os.path.abspath(os.path.join(paths.models_path, "VAE"))
 vae_ignore_keys = {"model_ema.decay", "model_ema.num_updates"}
 vae_dict = {}
 

modules/shared.py

@@ -14,7 +14,7 @@ import modules.memmon
 import modules.styles
 import modules.devices as devices
 from modules import localization, extensions, script_loading, errors, ui_components, shared_items
-from modules.paths import models_path, script_path
+from modules.paths import models_path, script_path, data_path
 
 
 demo = None
@@ -25,6 +25,7 @@ sd_model_file = os.path.join(script_path, 'model.ckpt')
 default_sd_model_file = sd_model_file
 
 parser = argparse.ArgumentParser()
+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",)
 parser.add_argument("--config", type=str, default=sd_default_config, 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")
@@ -35,7 +36,7 @@ parser.add_argument("--no-half", action='store_true', help="do not switch the mo
 parser.add_argument("--no-half-vae", action='store_true', help="do not switch the VAE 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("--embeddings-dir", type=str, default=os.path.join(data_path, 'embeddings'), help="embeddings directory for textual inversion (default: embeddings)")
 parser.add_argument("--textual-inversion-templates-dir", type=str, default=os.path.join(script_path, 'textual_inversion_templates'), help="directory with textual inversion templates")
 parser.add_argument("--hypernetwork-dir", type=str, default=os.path.join(models_path, 'hypernetworks'), help="hypernetwork directory")
 parser.add_argument("--localizations-dir", type=str, default=os.path.join(script_path, 'localizations'), help="localizations directory")
@@ -74,16 +75,16 @@ parser.add_argument("--use-cpu", nargs='+', help="use CPU as torch device for sp
 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("--ui-config-file", type=str, help="filename to use for ui configuration", default=os.path.join(data_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("--freeze-settings", action='store_true', help="disable editing settings", 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("--ui-settings-file", type=str, help="filename to use for ui settings", default=os.path.join(data_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='does not do anything')
 parser.add_argument("--gradio-inpaint-tool", type=str, help="does not do anything")
 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("--styles-file", type=str, help="filename to use for styles", default=os.path.join(data_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("--theme", type=str, help="launches the UI with light or dark theme", default=None)
 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)

modules/textual_inversion/preprocess.py

@@ -6,8 +6,7 @@ import sys
 import tqdm
 import time
 
-from modules import shared, images, deepbooru
-from modules.paths import models_path
+from modules import paths, shared, images, deepbooru
 from modules.shared import opts, cmd_opts
 from modules.textual_inversion import autocrop
 
@@ -199,7 +198,7 @@ def preprocess_work(process_src, process_dst, process_width, process_height, pre
 
             dnn_model_path = None
             try:
-                dnn_model_path = autocrop.download_and_cache_models(os.path.join(models_path, "opencv"))
+                dnn_model_path = autocrop.download_and_cache_models(os.path.join(paths.models_path, "opencv"))
             except Exception as e:
                 print("Unable to load face detection model for auto crop selection. Falling back to lower quality haar method.", e)
 

modules/ui.py

@@ -21,7 +21,7 @@ from modules.call_queue import wrap_gradio_gpu_call, wrap_queued_call, wrap_grad
 
 from modules import sd_hijack, sd_models, localization, script_callbacks, ui_extensions, deepbooru, sd_vae, extra_networks, postprocessing, ui_components, ui_common, ui_postprocessing
 from modules.ui_components import FormRow, FormGroup, ToolButton, FormHTML
-from modules.paths import script_path
+from modules.paths import script_path, data_path
 
 from modules.shared import opts, cmd_opts, restricted_opts
 
@@ -1497,8 +1497,8 @@ def create_ui():
         with open(cssfile, "r", encoding="utf8") as file:
             css += file.read() + "\n"
 
-    if os.path.exists(os.path.join(script_path, "user.css")):
-        with open(os.path.join(script_path, "user.css"), "r", encoding="utf8") as file:
+    if os.path.exists(os.path.join(data_path, "user.css")):
+        with open(os.path.join(data_path, "user.css"), "r", encoding="utf8") as file:
             css += file.read() + "\n"
 
     if not cmd_opts.no_progressbar_hiding:

modules/ui_extensions.py

@@ -132,7 +132,7 @@ def install_extension_from_url(dirname, url):
     normalized_url = normalize_git_url(url)
     assert len([x for x in extensions.extensions if normalize_git_url(x.remote) == normalized_url]) == 0, 'Extension with this URL is already installed'
 
-    tmpdir = os.path.join(paths.script_path, "tmp", dirname)
+    tmpdir = os.path.join(paths.data_path, "tmp", dirname)
 
     try:
         shutil.rmtree(tmpdir, True)

modules/upscaler.py

@@ -11,7 +11,6 @@ from modules import modelloader, shared
 
 LANCZOS = (Image.Resampling.LANCZOS if hasattr(Image, 'Resampling') else Image.LANCZOS)
 NEAREST = (Image.Resampling.NEAREST if hasattr(Image, 'Resampling') else Image.NEAREST)
-from modules.paths import models_path
 
 
 class Upscaler:
@@ -39,7 +38,7 @@ class Upscaler:
         self.mod_scale = None
 
         if self.model_path is None and self.name:
-            self.model_path = os.path.join(models_path, self.name)
+            self.model_path = os.path.join(shared.models_path, self.name)
         if self.model_path and create_dirs:
             os.makedirs(self.model_path, exist_ok=True)
 
@@ -143,4 +142,4 @@ class UpscalerNearest(Upscaler):
     def __init__(self, dirname=None):
         super().__init__(False)
         self.name = "Nearest"
-        self.scalers = [UpscalerData("Nearest", None, self)]
+        self.scalers = [UpscalerData("Nearest", None, self)]