Merge branch 'dev' into master

modules/api/api.py

@@ -6,7 +6,6 @@ import uvicorn
 import gradio as gr
 from threading import Lock
 from io import BytesIO
-from gradio_client.utils import decode_base64_to_file
 from fastapi import APIRouter, Depends, FastAPI, Request, Response
 from fastapi.security import HTTPBasic, HTTPBasicCredentials
 from fastapi.exceptions import HTTPException
@@ -131,8 +130,8 @@ def api_middleware(app: FastAPI):
             "body": vars(e).get('body', ''),
             "errors": str(e),
         }
-        print(f"API error: {request.method}: {request.url} {err}")
         if not isinstance(e, HTTPException): # do not print backtrace on known httpexceptions
+            print(f"API error: {request.method}: {request.url} {err}")
             if rich_available:
                 console.print_exception(show_locals=True, max_frames=2, extra_lines=1, suppress=[anyio, starlette], word_wrap=False, width=min([console.width, 200]))
             else:
@@ -272,7 +271,9 @@ class Api:
                     raise HTTPException(status_code=422, detail=f"Cannot have a selectable script in the always on scripts params")
                 # always on script with no arg should always run so you don't really need to add them to the requests
                 if "args" in request.alwayson_scripts[alwayson_script_name]:
-                    script_args[alwayson_script.args_from:alwayson_script.args_to] = request.alwayson_scripts[alwayson_script_name]["args"]
+                    # min between arg length in scriptrunner and arg length in the request
+                    for idx in range(0, min((alwayson_script.args_to - alwayson_script.args_from), len(request.alwayson_scripts[alwayson_script_name]["args"]))):
+                        script_args[alwayson_script.args_from + idx] = request.alwayson_scripts[alwayson_script_name]["args"][idx]
         return script_args
 
     def text2imgapi(self, txt2imgreq: StableDiffusionTxt2ImgProcessingAPI):
@@ -395,16 +396,11 @@ class Api:
     def extras_batch_images_api(self, req: ExtrasBatchImagesRequest):
         reqDict = setUpscalers(req)
 
-        def prepareFiles(file):
-            file = decode_base64_to_file(file.data, file_path=file.name)
-            file.orig_name = file.name
-            return file
-
-        reqDict['image_folder'] = list(map(prepareFiles, reqDict['imageList']))
-        reqDict.pop('imageList')
+        image_list = reqDict.pop('imageList', [])
+        image_folder = [decode_base64_to_image(x.data) for x in image_list]
 
         with self.queue_lock:
-            result = postprocessing.run_extras(extras_mode=1, image="", input_dir="", output_dir="", save_output=False, **reqDict)
+            result = postprocessing.run_extras(extras_mode=1, image_folder=image_folder, image="", input_dir="", output_dir="", save_output=False, **reqDict)
 
         return ExtrasBatchImagesResponse(images=list(map(encode_pil_to_base64, result[0])), html_info=result[1])
 

modules/config_states.py

@@ -0,0 +1,200 @@
+"""
+Supports saving and restoring webui and extensions from a known working set of commits
+"""
+
+import os
+import sys
+import traceback
+import json
+import time
+import tqdm
+
+from datetime import datetime
+from collections import OrderedDict
+import git
+
+from modules import shared, extensions
+from modules.paths_internal import extensions_dir, extensions_builtin_dir, script_path, config_states_dir
+
+
+all_config_states = OrderedDict()
+
+
+def list_config_states():
+    global all_config_states
+
+    all_config_states.clear()
+    os.makedirs(config_states_dir, exist_ok=True)
+
+    config_states = []
+    for filename in os.listdir(config_states_dir):
+        if filename.endswith(".json"):
+            path = os.path.join(config_states_dir, filename)
+            with open(path, "r", encoding="utf-8") as f:
+                j = json.load(f)
+                j["filepath"] = path
+                config_states.append(j)
+
+    config_states = list(sorted(config_states, key=lambda cs: cs["created_at"], reverse=True))
+
+    for cs in config_states:
+        timestamp = time.asctime(time.gmtime(cs["created_at"]))
+        name = cs.get("name", "Config")
+        full_name = f"{name}: {timestamp}"
+        all_config_states[full_name] = cs
+
+    return all_config_states
+
+
+def get_webui_config():
+    webui_repo = None
+
+    try:
+        if os.path.exists(os.path.join(script_path, ".git")):
+            webui_repo = git.Repo(script_path)
+    except Exception:
+        print(f"Error reading webui git info from {script_path}:", file=sys.stderr)
+        print(traceback.format_exc(), file=sys.stderr)
+
+    webui_remote = None
+    webui_commit_hash = None
+    webui_commit_date = None
+    webui_branch = None
+    if webui_repo and not webui_repo.bare:
+        try:
+            webui_remote = next(webui_repo.remote().urls, None)
+            head = webui_repo.head.commit
+            webui_commit_date = webui_repo.head.commit.committed_date
+            webui_commit_hash = head.hexsha
+            webui_branch = webui_repo.active_branch.name
+
+        except Exception:
+            webui_remote = None
+
+    return {
+        "remote": webui_remote,
+        "commit_hash": webui_commit_hash,
+        "commit_date": webui_commit_date,
+        "branch": webui_branch,
+    }
+
+
+def get_extension_config():
+    ext_config = {}
+
+    for ext in extensions.extensions:
+        entry = {
+            "name": ext.name,
+            "path": ext.path,
+            "enabled": ext.enabled,
+            "is_builtin": ext.is_builtin,
+            "remote": ext.remote,
+            "commit_hash": ext.commit_hash,
+            "commit_date": ext.commit_date,
+            "branch": ext.branch,
+            "have_info_from_repo": ext.have_info_from_repo
+        }
+
+        ext_config[ext.name] = entry
+
+    return ext_config
+
+
+def get_config():
+    creation_time = datetime.now().timestamp()
+    webui_config = get_webui_config()
+    ext_config = get_extension_config()
+
+    return {
+        "created_at": creation_time,
+        "webui": webui_config,
+        "extensions": ext_config
+    }
+
+
+def restore_webui_config(config):
+    print("* Restoring webui state...")
+
+    if "webui" not in config:
+        print("Error: No webui data saved to config")
+        return
+
+    webui_config = config["webui"]
+
+    if "commit_hash" not in webui_config:
+        print("Error: No commit saved to webui config")
+        return
+
+    webui_commit_hash = webui_config.get("commit_hash", None)
+    webui_repo = None
+
+    try:
+        if os.path.exists(os.path.join(script_path, ".git")):
+            webui_repo = git.Repo(script_path)
+    except Exception:
+        print(f"Error reading webui git info from {script_path}:", file=sys.stderr)
+        print(traceback.format_exc(), file=sys.stderr)
+        return
+
+    try:
+        webui_repo.git.fetch(all=True)
+        webui_repo.git.reset(webui_commit_hash, hard=True)
+        print(f"* Restored webui to commit {webui_commit_hash}.")
+    except Exception:
+        print(f"Error restoring webui to commit {webui_commit_hash}:", file=sys.stderr)
+        print(traceback.format_exc(), file=sys.stderr)
+
+
+def restore_extension_config(config):
+    print("* Restoring extension state...")
+
+    if "extensions" not in config:
+        print("Error: No extension data saved to config")
+        return
+
+    ext_config = config["extensions"]
+
+    results = []
+    disabled = []
+
+    for ext in tqdm.tqdm(extensions.extensions):
+        if ext.is_builtin:
+            continue
+
+        ext.read_info_from_repo()
+        current_commit = ext.commit_hash
+
+        if ext.name not in ext_config:
+            ext.disabled = True
+            disabled.append(ext.name)
+            results.append((ext, current_commit[:8], False, "Saved extension state not found in config, marking as disabled"))
+            continue
+
+        entry = ext_config[ext.name]
+
+        if "commit_hash" in entry and entry["commit_hash"]:
+            try:
+                ext.fetch_and_reset_hard(entry["commit_hash"])
+                ext.read_info_from_repo()
+                if current_commit != entry["commit_hash"]:
+                    results.append((ext, current_commit[:8], True, entry["commit_hash"][:8]))
+            except Exception as ex:
+                results.append((ext, current_commit[:8], False, ex))
+        else:
+            results.append((ext, current_commit[:8], False, "No commit hash found in config"))
+
+        if not entry.get("enabled", False):
+            ext.disabled = True
+            disabled.append(ext.name)
+        else:
+            ext.disabled = False
+
+    shared.opts.disabled_extensions = disabled
+    shared.opts.save(shared.config_filename)
+
+    print("* Finished restoring extensions. Results:")
+    for ext, prev_commit, success, result in results:
+        if success:
+            print(f"  + {ext.name}: {prev_commit} -> {result}")
+        else:
+            print(f"  ! {ext.name}: FAILURE ({result})")

modules/devices.py

@@ -92,14 +92,18 @@ def cond_cast_float(input):
 
 
 def randn(seed, shape):
+    from modules.shared import opts
+
     torch.manual_seed(seed)
-    if device.type == 'mps':
+    if opts.randn_source == "CPU" or device.type == 'mps':
         return torch.randn(shape, device=cpu).to(device)
     return torch.randn(shape, device=device)
 
 
 def randn_without_seed(shape):
-    if device.type == 'mps':
+    from modules.shared import opts
+
+    if opts.randn_source == "CPU" or device.type == 'mps':
         return torch.randn(shape, device=cpu).to(device)
     return torch.randn(shape, device=device)
 

modules/extensions.py

@@ -3,10 +3,11 @@ import sys
 import traceback
 
 import time
+from datetime import datetime
 import git
 
 from modules import shared
-from modules.paths_internal import extensions_dir, extensions_builtin_dir
+from modules.paths_internal import extensions_dir, extensions_builtin_dir, script_path
 
 extensions = []
 
@@ -31,12 +32,15 @@ class Extension:
         self.status = ''
         self.can_update = False
         self.is_builtin = is_builtin
+        self.commit_hash = ''
+        self.commit_date = None
         self.version = ''
+        self.branch = None
         self.remote = None
         self.have_info_from_repo = False
 
     def read_info_from_repo(self):
-        if self.have_info_from_repo:
+        if self.is_builtin or self.have_info_from_repo:
             return
 
         self.have_info_from_repo = True
@@ -56,10 +60,15 @@ class Extension:
                 self.status = 'unknown'
                 self.remote = next(repo.remote().urls, None)
                 head = repo.head.commit
-                ts = time.asctime(time.gmtime(repo.head.commit.committed_date))
-                self.version = f'{head.hexsha[:8]} ({ts})'
+                self.commit_date = repo.head.commit.committed_date
+                ts = time.asctime(time.gmtime(self.commit_date))
+                if repo.active_branch:
+                    self.branch = repo.active_branch.name
+                self.commit_hash = head.hexsha
+                self.version = f'{self.commit_hash[:8]} ({ts})'
 
-            except Exception:
+            except Exception as ex:
+                print(f"Failed reading extension data from Git repository ({self.name}): {ex}", file=sys.stderr)
                 self.remote = None
 
     def list_files(self, subdir, extension):
@@ -82,18 +91,30 @@ class Extension:
         for fetch in repo.remote().fetch(dry_run=True):
             if fetch.flags != fetch.HEAD_UPTODATE:
                 self.can_update = True
-                self.status = "behind"
+                self.status = "new commits"
                 return
 
+        try:
+            origin = repo.rev_parse('origin')
+            if repo.head.commit != origin:
+                self.can_update = True
+                self.status = "behind HEAD"
+                return
+        except Exception:
+            self.can_update = False
+            self.status = "unknown (remote error)"
+            return
+
         self.can_update = False
         self.status = "latest"
 
-    def fetch_and_reset_hard(self):
+    def fetch_and_reset_hard(self, commit='origin'):
         repo = git.Repo(self.path)
         # Fix: `error: Your local changes to the following files would be overwritten by merge`,
         # because WSL2 Docker set 755 file permissions instead of 644, this results to the error.
         repo.git.fetch(all=True)
-        repo.git.reset('origin', hard=True)
+        repo.git.reset(commit, hard=True)
+        self.have_info_from_repo = False
 
 
 def list_extensions():

modules/extra_networks_hypernet.py

@@ -9,7 +9,7 @@ class ExtraNetworkHypernet(extra_networks.ExtraNetwork):
     def activate(self, p, params_list):
         additional = shared.opts.sd_hypernetwork
 
-        if additional != "" and additional in shared.hypernetworks and len([x for x in params_list if x.items[0] == additional]) == 0:
+        if additional != "None" and additional in shared.hypernetworks and len([x for x in params_list if x.items[0] == additional]) == 0:
             p.all_prompts = [x + f"<hypernet:{additional}:{shared.opts.extra_networks_default_multiplier}>" for x in p.all_prompts]
             params_list.append(extra_networks.ExtraNetworkParams(items=[additional, shared.opts.extra_networks_default_multiplier]))
 

modules/extras.py

@@ -1,6 +1,7 @@
 import os
 import re
 import shutil
+import json
 
 
 import torch
@@ -71,7 +72,7 @@ def to_half(tensor, enable):
     return tensor
 
 
-def run_modelmerger(id_task, primary_model_name, secondary_model_name, tertiary_model_name, interp_method, multiplier, save_as_half, custom_name, checkpoint_format, config_source, bake_in_vae, discard_weights):
+def run_modelmerger(id_task, primary_model_name, secondary_model_name, tertiary_model_name, interp_method, multiplier, save_as_half, custom_name, checkpoint_format, config_source, bake_in_vae, discard_weights, save_metadata):
     shared.state.begin()
     shared.state.job = 'model-merge'
 
@@ -241,13 +242,54 @@ def run_modelmerger(id_task, primary_model_name, secondary_model_name, tertiary_
     shared.state.textinfo = "Saving"
     print(f"Saving to {output_modelname}...")
 
+    metadata = {"format": "pt", "sd_merge_models": {}, "sd_merge_recipe": None}
+
+    if save_metadata:
+        merge_recipe = {
+            "type": "webui", # indicate this model was merged with webui's built-in merger
+            "primary_model_hash": primary_model_info.sha256,
+            "secondary_model_hash": secondary_model_info.sha256 if secondary_model_info else None,
+            "tertiary_model_hash": tertiary_model_info.sha256 if tertiary_model_info else None,
+            "interp_method": interp_method,
+            "multiplier": multiplier,
+            "save_as_half": save_as_half,
+            "custom_name": custom_name,
+            "config_source": config_source,
+            "bake_in_vae": bake_in_vae,
+            "discard_weights": discard_weights,
+            "is_inpainting": result_is_inpainting_model,
+            "is_instruct_pix2pix": result_is_instruct_pix2pix_model
+        }
+        metadata["sd_merge_recipe"] = json.dumps(merge_recipe)
+
+        def add_model_metadata(checkpoint_info):
+            checkpoint_info.calculate_shorthash()
+            metadata["sd_merge_models"][checkpoint_info.sha256] = {
+                "name": checkpoint_info.name,
+                "legacy_hash": checkpoint_info.hash,
+                "sd_merge_recipe": checkpoint_info.metadata.get("sd_merge_recipe", None)
+            }
+
+            metadata["sd_merge_models"].update(checkpoint_info.metadata.get("sd_merge_models", {}))
+
+        add_model_metadata(primary_model_info)
+        if secondary_model_info:
+            add_model_metadata(secondary_model_info)
+        if tertiary_model_info:
+            add_model_metadata(tertiary_model_info)
+
+        metadata["sd_merge_models"] = json.dumps(metadata["sd_merge_models"])
+
     _, extension = os.path.splitext(output_modelname)
     if extension.lower() == ".safetensors":
-        safetensors.torch.save_file(theta_0, output_modelname, metadata={"format": "pt"})
+        safetensors.torch.save_file(theta_0, output_modelname, metadata=metadata)
     else:
         torch.save(theta_0, output_modelname)
 
     sd_models.list_models()
+    created_model = next((ckpt for ckpt in sd_models.checkpoints_list.values() if ckpt.name == filename), None)
+    if created_model:
+        created_model.calculate_shorthash()
 
     create_config(output_modelname, config_source, primary_model_info, secondary_model_info, tertiary_model_info)
 

modules/generation_parameters_copypaste.py

@@ -284,6 +284,10 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model
 
     restore_old_hires_fix_params(res)
 
+    # Missing RNG means the default was set, which is GPU RNG
+    if "RNG" not in res:
+        res["RNG"] = "GPU"
+
     return res
 
 
@@ -304,6 +308,8 @@ infotext_to_setting_name_mapping = [
     ('UniPC skip type', 'uni_pc_skip_type'),
     ('UniPC order', 'uni_pc_order'),
     ('UniPC lower order final', 'uni_pc_lower_order_final'),
+    ('RNG', 'randn_source'),
+    ('NGMS', 's_min_uncond'),
 ]
 
 

modules/images.py

@@ -318,6 +318,7 @@ re_nonletters = re.compile(r'[\s' + string.punctuation + ']+')
 re_pattern = re.compile(r"(.*?)(?:\[([^\[\]]+)\]|$)")
 re_pattern_arg = re.compile(r"(.*)<([^>]*)>$")
 max_filename_part_length = 128
+NOTHING_AND_SKIP_PREVIOUS_TEXT = object()
 
 
 def sanitize_filename_part(text, replace_spaces=True):
@@ -352,6 +353,10 @@ class FilenameGenerator:
         'prompt_no_styles': lambda self: self.prompt_no_style(),
         'prompt_spaces': lambda self: sanitize_filename_part(self.prompt, replace_spaces=False),
         'prompt_words': lambda self: self.prompt_words(),
+        'batch_number': lambda self: NOTHING_AND_SKIP_PREVIOUS_TEXT if self.p.batch_size == 1 else self.p.batch_index + 1,
+        'generation_number': lambda self: NOTHING_AND_SKIP_PREVIOUS_TEXT if self.p.n_iter == 1 and self.p.batch_size == 1 else self.p.iteration * self.p.batch_size + self.p.batch_index + 1,
+        'hasprompt': lambda self, *args: self.hasprompt(*args),  # accepts formats:[hasprompt<prompt1|default><prompt2>..]
+        'clip_skip': lambda self: opts.data["CLIP_stop_at_last_layers"],
     }
     default_time_format = '%Y%m%d%H%M%S'
 
@@ -360,6 +365,22 @@ class FilenameGenerator:
         self.seed = seed
         self.prompt = prompt
         self.image = image
+        
+    def hasprompt(self, *args):
+        lower = self.prompt.lower()
+        if self.p is None or self.prompt is None:
+            return None
+        outres = ""
+        for arg in args:
+            if arg != "":
+                division = arg.split("|")
+                expected = division[0].lower()
+                default = division[1] if len(division) > 1 else ""
+                if lower.find(expected) >= 0:
+                    outres = f'{outres}{expected}'
+                else:
+                    outres = outres if default == "" else f'{outres}{default}'
+        return sanitize_filename_part(outres)
 
     def prompt_no_style(self):
         if self.p is None or self.prompt is None:
@@ -403,9 +424,9 @@ class FilenameGenerator:
 
         for m in re_pattern.finditer(x):
             text, pattern = m.groups()
-            res += text
 
             if pattern is None:
+                res += text
                 continue
 
             pattern_args = []
@@ -426,11 +447,13 @@ class FilenameGenerator:
                     print(f"Error adding [{pattern}] to filename", file=sys.stderr)
                     print(traceback.format_exc(), file=sys.stderr)
 
-                if replacement is not None:
-                    res += str(replacement)
+                if replacement == NOTHING_AND_SKIP_PREVIOUS_TEXT:
+                    continue
+                elif replacement is not None:
+                    res += text + str(replacement)
                     continue
 
-            res += f'[{pattern}]'
+            res += f'{text}[{pattern}]'
 
         return res
 

modules/img2img.py

@@ -4,7 +4,7 @@ import sys
 import traceback
 
 import numpy as np
-from PIL import Image, ImageOps, ImageFilter, ImageEnhance, ImageChops
+from PIL import Image, ImageOps, ImageFilter, ImageEnhance, ImageChops, UnidentifiedImageError
 
 from modules import devices, sd_samplers
 from modules.generation_parameters_copypaste import create_override_settings_dict
@@ -46,7 +46,10 @@ def process_batch(p, input_dir, output_dir, inpaint_mask_dir, args):
         if state.interrupted:
             break
 
-        img = Image.open(image)
+        try:
+            img = Image.open(image)
+        except UnidentifiedImageError:
+            continue
         # Use the EXIF orientation of photos taken by smartphones.
         img = ImageOps.exif_transpose(img)
         p.init_images = [img] * p.batch_size
@@ -78,7 +81,7 @@ def process_batch(p, input_dir, output_dir, inpaint_mask_dir, args):
                 processed_image.save(os.path.join(output_dir, filename))
 
 
-def img2img(id_task: str, mode: int, prompt: str, negative_prompt: str, prompt_styles, init_img, sketch, init_img_with_mask, inpaint_color_sketch, inpaint_color_sketch_orig, init_img_inpaint, init_mask_inpaint, steps: int, sampler_index: int, mask_blur: int, mask_alpha: float, inpainting_fill: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, image_cfg_scale: float, denoising_strength: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, resize_mode: int, inpaint_full_res: bool, inpaint_full_res_padding: int, inpainting_mask_invert: int, img2img_batch_input_dir: str, img2img_batch_output_dir: str, img2img_batch_inpaint_mask_dir: str, override_settings_texts, *args):
+def img2img(id_task: str, mode: int, prompt: str, negative_prompt: str, prompt_styles, init_img, sketch, init_img_with_mask, inpaint_color_sketch, inpaint_color_sketch_orig, init_img_inpaint, init_mask_inpaint, steps: int, sampler_index: int, mask_blur: int, mask_alpha: float, inpainting_fill: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, image_cfg_scale: float, denoising_strength: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, selected_scale_tab: int, height: int, width: int, scale_by: float, resize_mode: int, inpaint_full_res: bool, inpaint_full_res_padding: int, inpainting_mask_invert: int, img2img_batch_input_dir: str, img2img_batch_output_dir: str, img2img_batch_inpaint_mask_dir: str, override_settings_texts, *args):
     override_settings = create_override_settings_dict(override_settings_texts)
 
     is_batch = mode == 5
@@ -114,6 +117,12 @@ def img2img(id_task: str, mode: int, prompt: str, negative_prompt: str, prompt_s
     if image is not None:
         image = ImageOps.exif_transpose(image)
 
+    if selected_scale_tab == 1:
+        assert image, "Can't scale by because no image is selected"
+
+        width = int(image.width * scale_by)
+        height = int(image.height * scale_by)
+
     assert 0. <= denoising_strength <= 1., 'can only work with strength in [0.0, 1.0]'
 
     p = StableDiffusionProcessingImg2Img(
@@ -151,7 +160,7 @@ def img2img(id_task: str, mode: int, prompt: str, negative_prompt: str, prompt_s
         override_settings=override_settings,
     )
 
-    p.scripts = modules.scripts.scripts_txt2img
+    p.scripts = modules.scripts.scripts_img2img
     p.script_args = args
 
     if shared.cmd_opts.enable_console_prompts:

modules/interrogate.py

@@ -32,7 +32,7 @@ def download_default_clip_interrogate_categories(content_dir):
     category_types = ["artists", "flavors", "mediums", "movements"]
 
     try:
-        os.makedirs(tmpdir)
+        os.makedirs(tmpdir, exist_ok=True)
         for category_type in category_types:
             torch.hub.download_url_to_file(f"https://raw.githubusercontent.com/pharmapsychotic/clip-interrogator/main/clip_interrogator/data/{category_type}.txt", os.path.join(tmpdir, f"{category_type}.txt"))
         os.rename(tmpdir, content_dir)
@@ -41,7 +41,7 @@ def download_default_clip_interrogate_categories(content_dir):
         errors.display(e, "downloading default CLIP interrogate categories")
     finally:
         if os.path.exists(tmpdir):
-            os.remove(tmpdir)
+            os.removedirs(tmpdir)
 
 
 class InterrogateModels:

modules/ngrok.py

@@ -13,6 +13,18 @@ def connect(token, port, region):
     config = conf.PyngrokConfig(
         auth_token=token, region=region
     )
+    
+    # Guard for existing tunnels
+    existing = ngrok.get_tunnels(pyngrok_config=config)
+    if existing:
+        for established in existing:
+            # Extra configuration in the case that the user is also using ngrok for other tunnels
+            if established.config['addr'][-4:] == str(port):
+                public_url = existing[0].public_url
+                print(f'ngrok has already been connected to localhost:{port}! URL: {public_url}\n'
+                    'You can use this link after the launch is complete.')
+                return
+    
     try:
         if account is None:
             public_url = ngrok.connect(port, pyngrok_config=config, bind_tls=True).public_url

modules/paths_internal.py

@@ -20,3 +20,4 @@ data_path = cmd_opts_pre.data_dir
 models_path = os.path.join(data_path, "models")
 extensions_dir = os.path.join(data_path, "extensions")
 extensions_builtin_dir = os.path.join(script_path, "extensions-builtin")
+config_states_dir = os.path.join(script_path, "config_states")

modules/postprocessing.py

@@ -18,9 +18,14 @@ def run_postprocessing(extras_mode, image, image_folder, input_dir, output_dir,
 
     if extras_mode == 1:
         for img in image_folder:
-            image = Image.open(img)
+            if isinstance(img, Image.Image):
+                image = img
+                fn = ''
+            else:
+                image = Image.open(os.path.abspath(img.name))
+                fn = os.path.splitext(img.orig_name)[0]
             image_data.append(image)
-            image_names.append(os.path.splitext(img.orig_name)[0])
+            image_names.append(fn)
     elif extras_mode == 2:
         assert not shared.cmd_opts.hide_ui_dir_config, '--hide-ui-dir-config option must be disabled'
         assert input_dir, 'input directory not selected'

modules/processing.py

@@ -3,6 +3,7 @@ import math
 import os
 import sys
 import warnings
+import hashlib
 
 import torch
 import numpy as np
@@ -105,7 +106,7 @@ class StableDiffusionProcessing:
     """
     The first set of paramaters: sd_models -> do_not_reload_embeddings represent the minimum required to create a StableDiffusionProcessing
     """
-    def __init__(self, sd_model=None, outpath_samples=None, outpath_grids=None, prompt: str = "", styles: List[str] = None, seed: int = -1, subseed: int = -1, subseed_strength: float = 0, seed_resize_from_h: int = -1, seed_resize_from_w: int = -1, seed_enable_extras: bool = True, sampler_name: str = None, batch_size: int = 1, n_iter: int = 1, steps: int = 50, cfg_scale: float = 7.0, width: int = 512, height: int = 512, restore_faces: bool = False, tiling: bool = False, do_not_save_samples: bool = False, do_not_save_grid: bool = False, extra_generation_params: Dict[Any, Any] = None, overlay_images: Any = None, negative_prompt: str = None, eta: float = None, do_not_reload_embeddings: bool = False, denoising_strength: float = 0, ddim_discretize: str = None, s_churn: float = 0.0, s_tmax: float = None, s_tmin: float = 0.0, s_noise: float = 1.0, override_settings: Dict[str, Any] = None, override_settings_restore_afterwards: bool = True, sampler_index: int = None, script_args: list = None):
+    def __init__(self, sd_model=None, outpath_samples=None, outpath_grids=None, prompt: str = "", styles: List[str] = None, seed: int = -1, subseed: int = -1, subseed_strength: float = 0, seed_resize_from_h: int = -1, seed_resize_from_w: int = -1, seed_enable_extras: bool = True, sampler_name: str = None, batch_size: int = 1, n_iter: int = 1, steps: int = 50, cfg_scale: float = 7.0, width: int = 512, height: int = 512, restore_faces: bool = False, tiling: bool = False, do_not_save_samples: bool = False, do_not_save_grid: bool = False, extra_generation_params: Dict[Any, Any] = None, overlay_images: Any = None, negative_prompt: str = None, eta: float = None, do_not_reload_embeddings: bool = False, denoising_strength: float = 0, ddim_discretize: str = None, s_min_uncond: float = 0.0, s_churn: float = 0.0, s_tmax: float = None, s_tmin: float = 0.0, s_noise: float = 1.0, override_settings: Dict[str, Any] = None, override_settings_restore_afterwards: bool = True, sampler_index: int = None, script_args: list = None):
         if sampler_index is not None:
             print("sampler_index argument for StableDiffusionProcessing does not do anything; use sampler_name", file=sys.stderr)
 
@@ -140,6 +141,7 @@ class StableDiffusionProcessing:
         self.denoising_strength: float = denoising_strength
         self.sampler_noise_scheduler_override = None
         self.ddim_discretize = ddim_discretize or opts.ddim_discretize
+        self.s_min_uncond = s_min_uncond or opts.s_min_uncond
         self.s_churn = s_churn or opts.s_churn
         self.s_tmin = s_tmin or opts.s_tmin
         self.s_tmax = s_tmax or float('inf')  # not representable as a standard ui option
@@ -162,6 +164,8 @@ class StableDiffusionProcessing:
         self.all_seeds = None
         self.all_subseeds = None
         self.iteration = 0
+        self.is_hr_pass = False
+        
 
     @property
     def sd_model(self):
@@ -476,6 +480,9 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter
         "Conditional mask weight": getattr(p, "inpainting_mask_weight", shared.opts.inpainting_mask_weight) if p.is_using_inpainting_conditioning else None,
         "Clip skip": None if clip_skip <= 1 else clip_skip,
         "ENSD": None if opts.eta_noise_seed_delta == 0 else opts.eta_noise_seed_delta,
+        "Init image hash": getattr(p, 'init_img_hash', None),
+        "RNG": opts.randn_source if opts.randn_source != "GPU" else None,
+        "NGMS": None if p.s_min_uncond == 0 else p.s_min_uncond,
     }
 
     generation_params.update(p.extra_generation_params)
@@ -639,8 +646,14 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
                     processed = Processed(p, [], p.seed, "")
                     file.write(processed.infotext(p, 0))
 
-            uc = get_conds_with_caching(prompt_parser.get_learned_conditioning, negative_prompts, p.steps, cached_uc)
-            c = get_conds_with_caching(prompt_parser.get_multicond_learned_conditioning, prompts, p.steps, cached_c)
+            step_multiplier = 1
+            if not shared.opts.dont_fix_second_order_samplers_schedule:
+                try:
+                    step_multiplier = 2 if sd_samplers.all_samplers_map.get(p.sampler_name).aliases[0] in ['k_dpmpp_2s_a', 'k_dpmpp_2s_a_ka', 'k_dpmpp_sde', 'k_dpmpp_sde_ka', 'k_dpm_2', 'k_dpm_2_a', 'k_heun'] else 1
+                except:
+                    pass
+            uc = get_conds_with_caching(prompt_parser.get_learned_conditioning, negative_prompts, p.steps * step_multiplier, cached_uc)
+            c = get_conds_with_caching(prompt_parser.get_multicond_learned_conditioning, prompts, p.steps * step_multiplier, cached_c)
 
             if len(model_hijack.comments) > 0:
                 for comment in model_hijack.comments:
@@ -670,6 +683,8 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
                 p.scripts.postprocess_batch(p, x_samples_ddim, batch_number=n)
 
             for i, x_sample in enumerate(x_samples_ddim):
+                p.batch_index = i
+
                 x_sample = 255. * np.moveaxis(x_sample.cpu().numpy(), 0, 2)
                 x_sample = x_sample.astype(np.uint8)
 
@@ -706,9 +721,9 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
                     image.info["parameters"] = text
                 output_images.append(image)
 
-                if hasattr(p, 'mask_for_overlay') and p.mask_for_overlay:
+                if hasattr(p, 'mask_for_overlay') and p.mask_for_overlay and any([opts.save_mask, opts.save_mask_composite, opts.return_mask, opts.return_mask_composite]):
                     image_mask = p.mask_for_overlay.convert('RGB')
-                    image_mask_composite = Image.composite(image.convert('RGBA').convert('RGBa'), Image.new('RGBa', image.size), p.mask_for_overlay.convert('L')).convert('RGBA')
+                    image_mask_composite = Image.composite(image.convert('RGBA').convert('RGBa'), Image.new('RGBa', image.size), images.resize_image(2, p.mask_for_overlay, image.width, image.height).convert('L')).convert('RGBA')
 
                     if opts.save_mask:
                         images.save_image(image_mask, p.outpath_samples, "", seeds[i], prompts[i], opts.samples_format, info=infotext(n, i), p=p, suffix="-mask")
@@ -718,7 +733,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
 
                     if opts.return_mask:
                         output_images.append(image_mask)
-                    
+
                     if opts.return_mask_composite:
                         output_images.append(image_mask_composite)
 
@@ -871,6 +886,8 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
         if not self.enable_hr:
             return samples
 
+        self.is_hr_pass = True
+
         target_width = self.hr_upscale_to_x
         target_height = self.hr_upscale_to_y
 
@@ -940,6 +957,8 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
 
         samples = self.sampler.sample_img2img(self, samples, noise, conditioning, unconditional_conditioning, steps=self.hr_second_pass_steps or self.steps, image_conditioning=image_conditioning)
 
+        self.is_hr_pass = False
+
         return samples
 
 
@@ -1007,6 +1026,12 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing):
             self.color_corrections = []
         imgs = []
         for img in self.init_images:
+
+            # Save init image
+            if opts.save_init_img:
+                self.init_img_hash = hashlib.md5(img.tobytes()).hexdigest()
+                images.save_image(img, path=opts.outdir_init_images, basename=None, forced_filename=self.init_img_hash, save_to_dirs=False)
+
             image = images.flatten(img, opts.img2img_background_color)
 
             if crop_region is None and self.resize_mode != 3:

modules/realesrgan_model.py

@@ -9,7 +9,7 @@ from realesrgan import RealESRGANer
 
 from modules.upscaler import Upscaler, UpscalerData
 from modules.shared import cmd_opts, opts
-
+from modules import modelloader
 
 class UpscalerRealESRGAN(Upscaler):
     def __init__(self, path):
@@ -23,7 +23,15 @@ class UpscalerRealESRGAN(Upscaler):
             self.enable = True
             self.scalers = []
             scalers = self.load_models(path)
+
+            local_model_paths = self.find_models(ext_filter=[".pth"])
             for scaler in scalers:
+                if scaler.local_data_path.startswith("http"):
+                    filename = modelloader.friendly_name(scaler.local_data_path)
+                    local = next(iter([local_model for local_model in local_model_paths if local_model.endswith(filename + '.pth')]), None)
+                    if local:
+                        scaler.local_data_path = local
+
                 if scaler.name in opts.realesrgan_enabled_models:
                     self.scalers.append(scaler)
 
@@ -64,7 +72,9 @@ class UpscalerRealESRGAN(Upscaler):
                 print(f"Unable to find model info: {path}")
                 return None
 
-            info.local_data_path = load_file_from_url(url=info.data_path, model_dir=self.model_path, progress=True)
+            if info.local_data_path.startswith("http"):
+                info.local_data_path = load_file_from_url(url=info.data_path, model_dir=self.model_path, progress=True)
+
             return info
         except Exception as e:
             print(f"Error making Real-ESRGAN models list: {e}", file=sys.stderr)

modules/safe.py

@@ -1,6 +1,5 @@
 # this code is adapted from the script contributed by anon from /h/
 
-import io
 import pickle
 import collections
 import sys
@@ -12,11 +11,9 @@ import _codecs
 import zipfile
 import re
 
-
 # PyTorch 1.13 and later have _TypedStorage renamed to TypedStorage
 TypedStorage = torch.storage.TypedStorage if hasattr(torch.storage, 'TypedStorage') else torch.storage._TypedStorage
 
-
 def encode(*args):
     out = _codecs.encode(*args)
     return out
@@ -27,7 +24,7 @@ class RestrictedUnpickler(pickle.Unpickler):
 
     def persistent_load(self, saved_id):
         assert saved_id[0] == 'storage'
-        return TypedStorage()
+        return TypedStorage(_internal=True)
 
     def find_class(self, module, name):
         if self.extra_handler is not None:

modules/script_callbacks.py

@@ -93,6 +93,7 @@ callback_map = dict(
     callbacks_infotext_pasted=[],
     callbacks_script_unloaded=[],
     callbacks_before_ui=[],
+    callbacks_on_reload=[],
 )
 
 
@@ -109,6 +110,14 @@ def app_started_callback(demo: Optional[Blocks], app: FastAPI):
             report_exception(c, 'app_started_callback')
 
 
+def app_reload_callback():
+    for c in callback_map['callbacks_on_reload']:
+        try:
+            c.callback()
+        except Exception:
+            report_exception(c, 'callbacks_on_reload')
+
+
 def model_loaded_callback(sd_model):
     for c in callback_map['callbacks_model_loaded']:
         try:
@@ -254,6 +263,11 @@ def on_app_started(callback):
     add_callback(callback_map['callbacks_app_started'], callback)
 
 
+def on_before_reload(callback):
+    """register a function to be called just before the server reloads."""
+    add_callback(callback_map['callbacks_on_reload'], callback)
+
+
 def on_model_loaded(callback):
     """register a function to be called when the stable diffusion model is created; the model is
     passed as an argument; this function is also called when the script is reloaded. """

modules/sd_models.py

@@ -52,6 +52,15 @@ class CheckpointInfo:
 
         self.ids = [self.hash, self.model_name, self.title, name, f'{name} [{self.hash}]'] + ([self.shorthash, self.sha256, f'{self.name} [{self.shorthash}]'] if self.shorthash else [])
 
+        self.metadata = {}
+
+        _, ext = os.path.splitext(self.filename)
+        if ext.lower() == ".safetensors":
+            try:
+                self.metadata = read_metadata_from_safetensors(filename)
+            except Exception as e:
+                errors.display(e, f"reading checkpoint metadata: {filename}")
+
     def register(self):
         checkpoints_list[self.title] = self
         for id in self.ids:
@@ -544,4 +553,4 @@ def unload_model_weights(sd_model=None, info=None):
 
     print(f"Unloaded weights {timer.summary()}.")
 
-    return sd_model
+    return sd_model

modules/sd_samplers_common.py

@@ -60,3 +60,13 @@ def store_latent(decoded):
 
 class InterruptedException(BaseException):
     pass
+
+
+if opts.randn_source == "CPU":
+    import torchsde._brownian.brownian_interval
+
+    def torchsde_randn(size, dtype, device, seed):
+        generator = torch.Generator(devices.cpu).manual_seed(int(seed))
+        return torch.randn(size, dtype=dtype, device=devices.cpu, generator=generator).to(device)
+
+    torchsde._brownian.brownian_interval._randn = torchsde_randn

modules/sd_samplers_kdiffusion.py

@@ -76,7 +76,7 @@ class CFGDenoiser(torch.nn.Module):
 
         return denoised
 
-    def forward(self, x, sigma, uncond, cond, cond_scale, image_cond):
+    def forward(self, x, sigma, uncond, cond, cond_scale, s_min_uncond, image_cond):
         if state.interrupted or state.skipped:
             raise sd_samplers_common.InterruptedException
 
@@ -115,12 +115,21 @@ class CFGDenoiser(torch.nn.Module):
         sigma_in = denoiser_params.sigma
         tensor = denoiser_params.text_cond
         uncond = denoiser_params.text_uncond
+        skip_uncond = False
 
-        if tensor.shape[1] == uncond.shape[1]:
-            if not is_edit_model:
-                cond_in = torch.cat([tensor, uncond])
-            else:
+        # alternating uncond allows for higher thresholds without the quality loss normally expected from raising it
+        if self.step % 2 and s_min_uncond > 0 and sigma[0] < s_min_uncond and not is_edit_model:
+            skip_uncond = True
+            x_in = x_in[:-batch_size]
+            sigma_in = sigma_in[:-batch_size]
+
+        if tensor.shape[1] == uncond.shape[1] or skip_uncond:
+            if is_edit_model:
                 cond_in = torch.cat([tensor, uncond, uncond])
+            elif skip_uncond:
+                cond_in = tensor
+            else:
+                cond_in = torch.cat([tensor, uncond])
 
             if shared.batch_cond_uncond:
                 x_out = self.inner_model(x_in, sigma_in, cond=make_condition_dict([cond_in], image_cond_in))
@@ -144,7 +153,13 @@ class CFGDenoiser(torch.nn.Module):
 
                 x_out[a:b] = self.inner_model(x_in[a:b], sigma_in[a:b], cond=make_condition_dict(c_crossattn, image_cond_in[a:b]))
 
-            x_out[-uncond.shape[0]:] = self.inner_model(x_in[-uncond.shape[0]:], sigma_in[-uncond.shape[0]:], cond=make_condition_dict([uncond], image_cond_in[-uncond.shape[0]:]))
+            if not skip_uncond:
+                x_out[-uncond.shape[0]:] = self.inner_model(x_in[-uncond.shape[0]:], sigma_in[-uncond.shape[0]:], cond=make_condition_dict([uncond], image_cond_in[-uncond.shape[0]:]))
+
+        denoised_image_indexes = [x[0][0] for x in conds_list]
+        if skip_uncond:
+            fake_uncond = torch.cat([x_out[i:i+1] for i in denoised_image_indexes])
+            x_out = torch.cat([x_out, fake_uncond])  # we skipped uncond denoising, so we put cond-denoised image to where the uncond-denoised image should be
 
         denoised_params = CFGDenoisedParams(x_out, state.sampling_step, state.sampling_steps)
         cfg_denoised_callback(denoised_params)
@@ -152,20 +167,21 @@ class CFGDenoiser(torch.nn.Module):
         devices.test_for_nans(x_out, "unet")
 
         if opts.live_preview_content == "Prompt":
-            sd_samplers_common.store_latent(x_out[0:uncond.shape[0]])
+            sd_samplers_common.store_latent(torch.cat([x_out[i:i+1] for i in denoised_image_indexes]))
         elif opts.live_preview_content == "Negative prompt":
             sd_samplers_common.store_latent(x_out[-uncond.shape[0]:])
 
-        if not is_edit_model:
-            denoised = self.combine_denoised(x_out, conds_list, uncond, cond_scale)
-        else:
+        if is_edit_model:
             denoised = self.combine_denoised_for_edit_model(x_out, cond_scale)
+        elif skip_uncond:
+            denoised = self.combine_denoised(x_out, conds_list, uncond, 1.0)
+        else:
+            denoised = self.combine_denoised(x_out, conds_list, uncond, cond_scale)
 
         if self.mask is not None:
             denoised = self.init_latent * self.mask + self.nmask * denoised
 
         self.step += 1
-
         return denoised
 
 
@@ -190,7 +206,7 @@ class TorchHijack:
             if noise.shape == x.shape:
                 return noise
 
-        if x.device.type == 'mps':
+        if opts.randn_source == "CPU" or x.device.type == 'mps':
             return torch.randn_like(x, device=devices.cpu).to(x.device)
         else:
             return torch.randn_like(x)
@@ -210,6 +226,7 @@ class KDiffusionSampler:
         self.eta = None
         self.config = None
         self.last_latent = None
+        self.s_min_uncond = None
 
         self.conditioning_key = sd_model.model.conditioning_key
 
@@ -244,6 +261,7 @@ class KDiffusionSampler:
         self.model_wrap_cfg.step = 0
         self.model_wrap_cfg.image_cfg_scale = getattr(p, 'image_cfg_scale', None)
         self.eta = p.eta if p.eta is not None else opts.eta_ancestral
+        self.s_min_uncond = getattr(p, 's_min_uncond', 0.0)
 
         k_diffusion.sampling.torch = TorchHijack(self.sampler_noises if self.sampler_noises is not None else [])
 
@@ -326,6 +344,7 @@ class KDiffusionSampler:
             'image_cond': image_conditioning, 
             'uncond': unconditional_conditioning, 
             'cond_scale': p.cfg_scale,
+            's_min_uncond': self.s_min_uncond
         }
 
         samples = self.launch_sampling(t_enc + 1, lambda: self.func(self.model_wrap_cfg, xi, extra_args=extra_args, disable=False, callback=self.callback_state, **extra_params_kwargs))
@@ -359,7 +378,8 @@ class KDiffusionSampler:
             'cond': conditioning, 
             'image_cond': image_conditioning, 
             'uncond': unconditional_conditioning, 
-            'cond_scale': p.cfg_scale
+            'cond_scale': p.cfg_scale,
+            's_min_uncond': self.s_min_uncond
         }, disable=False, callback=self.callback_state, **extra_params_kwargs))
 
         return samples

modules/shared.py

@@ -4,6 +4,7 @@ import json
 import os
 import sys
 import time
+import requests
 
 from PIL import Image
 import gradio as gr
@@ -39,6 +40,7 @@ restricted_opts = {
     "outdir_grids",
     "outdir_txt2img_grids",
     "outdir_save",
+    "outdir_init_images"
 }
 
 ui_reorder_categories = [
@@ -54,6 +56,21 @@ ui_reorder_categories = [
     "scripts",
 ]
 
+# https://huggingface.co/datasets/freddyaboulton/gradio-theme-subdomains/resolve/main/subdomains.json
+gradio_hf_hub_themes = [
+    "gradio/glass",
+    "gradio/monochrome",
+    "gradio/seafoam",
+    "gradio/soft",
+    "freddyaboulton/dracula_revamped",
+    "gradio/dracula_test",
+    "abidlabs/dracula_test",
+    "abidlabs/pakistan",
+    "dawood/microsoft_windows",
+    "ysharma/steampunk"
+]
+
+
 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
 
 devices.device, devices.device_interrogate, devices.device_gfpgan, devices.device_esrgan, devices.device_codeformer = \
@@ -252,7 +269,7 @@ options_templates.update(options_section(('saving-images', "Saving images/grids"
     "use_original_name_batch": OptionInfo(True, "Use original name for output filename during batch process in extras tab"),
     "use_upscaler_name_as_suffix": OptionInfo(False, "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"),
-    "do_not_add_watermark": OptionInfo(False, "Do not add watermark to images"),
+    "save_init_img": OptionInfo(False, "Save init images when using img2img"),
 
     "temp_dir":  OptionInfo("", "Directory for temporary images; leave empty for default"),
     "clean_temp_dir_at_start": OptionInfo(False, "Cleanup non-default temporary directory when starting webui"),
@@ -268,6 +285,7 @@ options_templates.update(options_section(('saving-paths', "Paths for saving"), {
     "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),
+    "outdir_init_images": OptionInfo("outputs/init-images", "Directory for saving init images when using img2img", component_args=hide_dirs),
 }))
 
 options_templates.update(options_section(('saving-to-dirs', "Saving to a directory"), {
@@ -283,6 +301,8 @@ options_templates.update(options_section(('upscaling', "Upscaling"), {
     "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(None, "Upscaler for img2img", gr.Dropdown, lambda: {"choices": [x.name for x in sd_upscalers]}),
+    "SCUNET_tile": OptionInfo(256, "Tile size for SCUNET upscalers. 0 = no tiling.", gr.Slider, {"minimum": 0, "maximum": 512, "step": 16}),
+    "SCUNET_tile_overlap": OptionInfo(8, "Tile overlap, in pixels for SCUNET upscalers. Low values = visible seam.", gr.Slider, {"minimum": 0, "maximum": 64, "step": 1}),
 }))
 
 options_templates.update(options_section(('face-restoration', "Face restoration"), {
@@ -331,6 +351,7 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), {
     "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 }),
     "CLIP_stop_at_last_layers": OptionInfo(1, "Clip skip", gr.Slider, {"minimum": 1, "maximum": 12, "step": 1}),
     "upcast_attn": OptionInfo(False, "Upcast cross attention layer to float32"),
+    "randn_source": OptionInfo("GPU", "Random number generator source. Changes seeds drastically. Use CPU to produce the same picture across different vidocard vendors.", gr.Radio, {"choices": ["GPU", "CPU"]}),
 }))
 
 options_templates.update(options_section(('compatibility', "Compatibility"), {
@@ -338,6 +359,7 @@ options_templates.update(options_section(('compatibility', "Compatibility"), {
     "use_old_karras_scheduler_sigmas": OptionInfo(False, "Use old karras scheduler sigmas (0.1 to 10)."),
     "no_dpmpp_sde_batch_determinism": OptionInfo(False, "Do not make DPM++ SDE deterministic across different batch sizes."),
     "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)."),
+    "dont_fix_second_order_samplers_schedule": OptionInfo(False, "Do not fix prompt schedule for second order samplers."),
 }))
 
 options_templates.update(options_section(('interrogate', "Interrogate Options"), {
@@ -361,7 +383,7 @@ options_templates.update(options_section(('extra_networks', "Extra Networks"), {
     "extra_networks_card_width": OptionInfo(0, "Card width for Extra Networks (px)"),
     "extra_networks_card_height": OptionInfo(0, "Card height for Extra Networks (px)"),
     "extra_networks_add_text_separator": OptionInfo(" ", "Extra text to add before <...> when adding extra network to prompt"),
-    "sd_hypernetwork": OptionInfo("None", "Add hypernetwork to prompt", gr.Dropdown, lambda: {"choices": [""] + [x for x in hypernetworks.keys()]}, refresh=reload_hypernetworks),
+    "sd_hypernetwork": OptionInfo("None", "Add hypernetwork to prompt", gr.Dropdown, lambda: {"choices": ["None"] + [x for x in hypernetworks.keys()]}, refresh=reload_hypernetworks),
 }))
 
 options_templates.update(options_section(('ui', "User interface"), {
@@ -382,11 +404,13 @@ options_templates.update(options_section(('ui', "User interface"), {
     "dimensions_and_batch_together": OptionInfo(True, "Show Width/Height and Batch sliders in same row"),
     "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}),
+    "keyedit_delimiters": OptionInfo(".,\/!?%^*;:{}=`~()", "Ctrl+up/down word delimiters"),
     "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)", ui_components.DropdownEditable, lambda: {"choices": ["Default"] + gradio_hf_hub_themes})
 }))
 
 options_templates.update(options_section(('ui', "Live previews"), {
@@ -405,6 +429,7 @@ options_templates.update(options_section(('sampler-params', "Sampler parameters"
     "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_min_uncond': OptionInfo(0, "Negative Guidance minimum sigma", gr.Slider, {"minimum": 0.0, "maximum": 4.0, "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}),
     'eta_noise_seed_delta': OptionInfo(0, "Eta noise seed delta", gr.Number, {"precision": 0}),
@@ -424,6 +449,7 @@ options_templates.update(options_section(('postprocessing', "Postprocessing"), {
 options_templates.update(options_section((None, "Hidden options"), {
     "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"]}),
+    "restore_config_state_file": OptionInfo("", "Config state file to restore from, under 'config-states/' folder"),
     "sd_checkpoint_hash": OptionInfo("", "SHA256 hash of the current checkpoint"),
 }))
 
@@ -600,6 +626,24 @@ clip_model = None
 
 progress_print_out = sys.stdout
 
+gradio_theme = gr.themes.Base()
+
+
+def reload_gradio_theme(theme_name=None):
+    global gradio_theme
+    if not theme_name:
+        theme_name = opts.gradio_theme
+
+    if theme_name == "Default":
+        gradio_theme = gr.themes.Default()
+    else:
+        try:
+            gradio_theme = gr.themes.ThemeClass.from_hub(theme_name)
+        except requests.exceptions.ConnectionError:
+            print("Can't access HuggingFace Hub, falling back to default Gradio theme")
+            gradio_theme = gr.themes.Default()
+
+
 
 class TotalTQDM:
     def __init__(self):

modules/styles.py

@@ -72,16 +72,14 @@ class StyleDatabase:
         return apply_styles_to_prompt(prompt, [self.styles.get(x, self.no_style).negative_prompt for x in styles])
 
     def save_styles(self, path: str) -> None:
-        # Write to temporary file first, so we don't nuke the file if something goes wrong
-        fd, temp_path = tempfile.mkstemp(".csv")
+        # Always keep a backup file around
+        if os.path.exists(path):
+            shutil.copy(path, path + ".bak")
+
+        fd = os.open(path, os.O_RDWR|os.O_CREAT)
         with os.fdopen(fd, "w", encoding="utf-8-sig", newline='') as file:
             # _fields is actually part of the public API: typing.NamedTuple is a replacement for collections.NamedTuple,
             # and collections.NamedTuple has explicit documentation for accessing _fields. Same goes for _asdict()
             writer = csv.DictWriter(file, fieldnames=PromptStyle._fields)
             writer.writeheader()
             writer.writerows(style._asdict() for k,     style in self.styles.items())
-
-        # Always keep a backup file around
-        if os.path.exists(path):
-            shutil.move(path, path + ".bak")
-        shutil.move(temp_path, path)

modules/textual_inversion/preprocess.py

@@ -11,7 +11,7 @@ from modules.shared import opts, cmd_opts
 from modules.textual_inversion import autocrop
 
 
-def preprocess(id_task, process_src, process_dst, process_width, process_height, preprocess_txt_action, process_flip, process_split, process_caption, process_caption_deepbooru=False, split_threshold=0.5, overlap_ratio=0.2, process_focal_crop=False, process_focal_crop_face_weight=0.9, process_focal_crop_entropy_weight=0.3, process_focal_crop_edges_weight=0.5, process_focal_crop_debug=False, process_multicrop=None, process_multicrop_mindim=None, process_multicrop_maxdim=None, process_multicrop_minarea=None, process_multicrop_maxarea=None, process_multicrop_objective=None, process_multicrop_threshold=None):
+def preprocess(id_task, process_src, process_dst, process_width, process_height, preprocess_txt_action, process_keep_original_size, process_flip, process_split, process_caption, process_caption_deepbooru=False, split_threshold=0.5, overlap_ratio=0.2, process_focal_crop=False, process_focal_crop_face_weight=0.9, process_focal_crop_entropy_weight=0.3, process_focal_crop_edges_weight=0.5, process_focal_crop_debug=False, process_multicrop=None, process_multicrop_mindim=None, process_multicrop_maxdim=None, process_multicrop_minarea=None, process_multicrop_maxarea=None, process_multicrop_objective=None, process_multicrop_threshold=None):
     try:
         if process_caption:
             shared.interrogator.load()
@@ -19,7 +19,7 @@ def preprocess(id_task, process_src, process_dst, process_width, process_height,
         if process_caption_deepbooru:
             deepbooru.model.start()
 
-        preprocess_work(process_src, process_dst, process_width, process_height, preprocess_txt_action, process_flip, process_split, process_caption, process_caption_deepbooru, split_threshold, overlap_ratio, process_focal_crop, process_focal_crop_face_weight, process_focal_crop_entropy_weight, process_focal_crop_edges_weight, process_focal_crop_debug, process_multicrop, process_multicrop_mindim, process_multicrop_maxdim, process_multicrop_minarea, process_multicrop_maxarea, process_multicrop_objective, process_multicrop_threshold)
+        preprocess_work(process_src, process_dst, process_width, process_height, preprocess_txt_action, process_keep_original_size, process_flip, process_split, process_caption, process_caption_deepbooru, split_threshold, overlap_ratio, process_focal_crop, process_focal_crop_face_weight, process_focal_crop_entropy_weight, process_focal_crop_edges_weight, process_focal_crop_debug, process_multicrop, process_multicrop_mindim, process_multicrop_maxdim, process_multicrop_minarea, process_multicrop_maxarea, process_multicrop_objective, process_multicrop_threshold)
 
     finally:
 
@@ -131,7 +131,7 @@ def multicrop_pic(image: Image, mindim, maxdim, minarea, maxarea, objective, thr
     return wh and center_crop(image, *wh)
     
 
-def preprocess_work(process_src, process_dst, process_width, process_height, preprocess_txt_action, process_flip, process_split, process_caption, process_caption_deepbooru=False, split_threshold=0.5, overlap_ratio=0.2, process_focal_crop=False, process_focal_crop_face_weight=0.9, process_focal_crop_entropy_weight=0.3, process_focal_crop_edges_weight=0.5, process_focal_crop_debug=False, process_multicrop=None, process_multicrop_mindim=None, process_multicrop_maxdim=None, process_multicrop_minarea=None, process_multicrop_maxarea=None, process_multicrop_objective=None, process_multicrop_threshold=None):
+def preprocess_work(process_src, process_dst, process_width, process_height, preprocess_txt_action, process_keep_original_size, process_flip, process_split, process_caption, process_caption_deepbooru=False, split_threshold=0.5, overlap_ratio=0.2, process_focal_crop=False, process_focal_crop_face_weight=0.9, process_focal_crop_entropy_weight=0.3, process_focal_crop_edges_weight=0.5, process_focal_crop_debug=False, process_multicrop=None, process_multicrop_mindim=None, process_multicrop_maxdim=None, process_multicrop_minarea=None, process_multicrop_maxarea=None, process_multicrop_objective=None, process_multicrop_threshold=None):
     width = process_width
     height = process_height
     src = os.path.abspath(process_src)
@@ -161,7 +161,9 @@ def preprocess_work(process_src, process_dst, process_width, process_height, pre
         params.subindex = 0
         filename = os.path.join(src, imagefile)
         try:
-            img = Image.open(filename).convert("RGB")
+            img = Image.open(filename)
+            img = ImageOps.exif_transpose(img)
+            img = img.convert("RGB")
         except Exception:
             continue
 
@@ -223,6 +225,10 @@ def preprocess_work(process_src, process_dst, process_width, process_height, pre
                 print(f"skipped {img.width}x{img.height} image {filename} (can't find suitable size within error threshold)")
             process_default_resize = False
 
+        if process_keep_original_size:
+            save_pic(img, index, params, existing_caption=existing_caption)
+            process_default_resize = False
+
         if process_default_resize:
             img = images.resize_image(1, img, width, height)
             save_pic(img, index, params, existing_caption=existing_caption)

modules/textual_inversion/textual_inversion.py

@@ -233,6 +233,12 @@ class EmbeddingDatabase:
             self.load_from_dir(embdir)
             embdir.update()
 
+        # re-sort word_embeddings because load_from_dir may not load in alphabetic order.
+        # using a temporary copy so we don't reinitialize self.word_embeddings in case other objects have a reference to it.
+        sorted_word_embeddings = {e.name: e for e in sorted(self.word_embeddings.values(), key=lambda e: e.name.lower())}
+        self.word_embeddings.clear()
+        self.word_embeddings.update(sorted_word_embeddings)
+
         displayed_embeddings = (tuple(self.word_embeddings.keys()), tuple(self.skipped_embeddings.keys()))
         if self.previously_displayed_embeddings != displayed_embeddings:
             self.previously_displayed_embeddings = displayed_embeddings

modules/ui.py

@@ -94,6 +94,9 @@ def send_gradio_gallery_to_image(x):
 
 def visit(x, func, path=""):
     if hasattr(x, 'children'):
+        if isinstance(x, gr.Tabs) and x.elem_id is not None:
+            # Tabs element can't have a label, have to use elem_id instead
+            func(f"{path}/Tabs@{x.elem_id}", x)
         for c in x.children:
             visit(c, func, path)
     elif x.label is not None:
@@ -127,6 +130,16 @@ def calc_resolution_hires(enable, width, height, hr_scale, hr_resize_x, hr_resiz
     return f"resize: from <span class='resolution'>{p.width}x{p.height}</span> to <span class='resolution'>{p.hr_resize_x or p.hr_upscale_to_x}x{p.hr_resize_y or p.hr_upscale_to_y}</span>"
 
 
+def resize_from_to_html(width, height, scale_by):
+    target_width = int(width * scale_by)
+    target_height = int(height * scale_by)
+
+    if not target_width or not target_height:
+        return "no image selected"
+
+    return f"resize: from <span class='resolution'>{width}x{height}</span> to <span class='resolution'>{target_width}x{target_height}</span>"
+
+
 def apply_styles(prompt, prompt_neg, styles):
     prompt = shared.prompt_styles.apply_styles_to_prompt(prompt, styles)
     prompt_neg = shared.prompt_styles.apply_negative_styles_to_prompt(prompt_neg, styles)
@@ -171,8 +184,8 @@ def create_seed_inputs(target_interface):
     with FormRow(elem_id=target_interface + '_seed_row', variant="compact"):
         seed = (gr.Textbox if cmd_opts.use_textbox_seed else gr.Number)(label='Seed', value=-1, elem_id=target_interface + '_seed')
         seed.style(container=False)
-        random_seed = ToolButton(random_symbol, elem_id=target_interface + '_random_seed')
-        reuse_seed = ToolButton(reuse_symbol, elem_id=target_interface + '_reuse_seed')
+        random_seed = ToolButton(random_symbol, elem_id=target_interface + '_random_seed', label='Random seed')
+        reuse_seed = ToolButton(reuse_symbol, elem_id=target_interface + '_reuse_seed', label='Reuse seed')
 
         seed_checkbox = gr.Checkbox(label='Extra', elem_id=target_interface + '_subseed_show', value=False)
 
@@ -468,7 +481,7 @@ def create_ui():
                                 height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="txt2img_height")
 
                             with gr.Column(elem_id="txt2img_dimensions_row", scale=1, elem_classes="dimensions-tools"):
-                                res_switch_btn = ToolButton(value=switch_values_symbol, elem_id="txt2img_res_switch_btn")
+                                res_switch_btn = ToolButton(value=switch_values_symbol, elem_id="txt2img_res_switch_btn", label="Switch dims")
 
                             if opts.dimensions_and_batch_together:
                                 with gr.Column(elem_id="txt2img_column_batch"):
@@ -673,6 +686,8 @@ def create_ui():
                             copy_image_buttons.append((button, name, elem))
 
                 with gr.Tabs(elem_id="mode_img2img"):
+                    img2img_selected_tab = gr.State(0)
+
                     with gr.TabItem('img2img', id='img2img', elem_id="img2img_img2img_tab") as tab_img2img:
                         init_img = gr.Image(label="Image for img2img", elem_id="img2img_image", show_label=False, source="upload", interactive=True, type="pil", tool="editor", image_mode="RGBA").style(height=480)
                         add_copy_image_controls('img2img', init_img)
@@ -715,6 +730,12 @@ def create_ui():
                         img2img_batch_output_dir = gr.Textbox(label="Output directory", **shared.hide_dirs, elem_id="img2img_batch_output_dir")
                         img2img_batch_inpaint_mask_dir = gr.Textbox(label="Inpaint batch mask directory (required for inpaint batch processing only)", **shared.hide_dirs, elem_id="img2img_batch_inpaint_mask_dir")
 
+                    img2img_tabs = [tab_img2img, tab_sketch, tab_inpaint, tab_inpaint_color, tab_inpaint_upload, tab_batch]
+                    img2img_image_inputs = [init_img, sketch, init_img_with_mask, inpaint_color_sketch]
+
+                    for i, tab in enumerate(img2img_tabs):
+                        tab.select(fn=lambda tabnum=i: tabnum, inputs=[], outputs=[img2img_selected_tab])
+
                 def copy_image(img):
                     if isinstance(img, dict) and 'image' in img:
                         return img['image']
@@ -744,11 +765,41 @@ def create_ui():
                     elif category == "dimensions":
                         with FormRow():
                             with gr.Column(elem_id="img2img_column_size", scale=4):
-                                width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="img2img_width")
-                                height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="img2img_height")
+                                selected_scale_tab = gr.State(value=0)
 
-                            with gr.Column(elem_id="img2img_dimensions_row", scale=1, elem_classes="dimensions-tools"):
-                                res_switch_btn = ToolButton(value=switch_values_symbol, elem_id="img2img_res_switch_btn")
+                                with gr.Tabs():
+                                    with gr.Tab(label="Resize to") as tab_scale_to:
+                                        with FormRow():
+                                            with gr.Column(elem_id="img2img_column_size", scale=4):
+                                                width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="img2img_width")
+                                                height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="img2img_height")
+                                            with gr.Column(elem_id="img2img_dimensions_row", scale=1, elem_classes="dimensions-tools"):
+                                                res_switch_btn = ToolButton(value=switch_values_symbol, elem_id="img2img_res_switch_btn")
+
+                                    with gr.Tab(label="Resize by") as tab_scale_by:
+                                        scale_by = gr.Slider(minimum=0.05, maximum=4.0, step=0.05, label="Scale", value=1.0, elem_id="img2img_scale")
+
+                                        with FormRow():
+                                            scale_by_html = FormHTML(resize_from_to_html(0, 0, 0.0), elem_id="img2img_scale_resolution_preview")
+                                            gr.Slider(label="Unused", elem_id="img2img_unused_scale_by_slider")
+                                            button_update_resize_to = gr.Button(visible=False, elem_id="img2img_update_resize_to")
+
+                                    on_change_args = dict(
+                                        fn=resize_from_to_html,
+                                        _js="currentImg2imgSourceResolution",
+                                        inputs=[dummy_component, dummy_component, scale_by],
+                                        outputs=scale_by_html,
+                                        show_progress=False,
+                                    )
+
+                                    scale_by.release(**on_change_args)
+                                    button_update_resize_to.click(**on_change_args)
+
+                                    for component in img2img_image_inputs:
+                                        component.change(fn=lambda: None, _js="updateImg2imgResizeToTextAfterChangingImage", inputs=[], outputs=[], show_progress=False)
+
+                            tab_scale_to.select(fn=lambda: 0, inputs=[], outputs=[selected_scale_tab])
+                            tab_scale_by.select(fn=lambda: 1, inputs=[], outputs=[selected_scale_tab])
 
                             if opts.dimensions_and_batch_together:
                                 with gr.Column(elem_id="img2img_column_batch"):
@@ -806,7 +857,7 @@ def create_ui():
                             def select_img2img_tab(tab):
                                 return gr.update(visible=tab in [2, 3, 4]), gr.update(visible=tab == 3),
 
-                            for i, elem in enumerate([tab_img2img, tab_sketch, tab_inpaint, tab_inpaint_color, tab_inpaint_upload, tab_batch]):
+                            for i, elem in enumerate(img2img_tabs):
                                 elem.select(
                                     fn=lambda tab=i: select_img2img_tab(tab),
                                     inputs=[],
@@ -859,8 +910,10 @@ def create_ui():
                     denoising_strength,
                     seed,
                     subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox,
+                    selected_scale_tab,
                     height,
                     width,
+                    scale_by,
                     resize_mode,
                     inpaint_full_res,
                     inpaint_full_res_padding,
@@ -1019,8 +1072,9 @@ def create_ui():
                 interp_method.change(fn=update_interp_description, inputs=[interp_method], outputs=[interp_description])
 
                 with FormRow():
-                    checkpoint_format = gr.Radio(choices=["ckpt", "safetensors"], value="ckpt", label="Checkpoint format", elem_id="modelmerger_checkpoint_format")
+                    checkpoint_format = gr.Radio(choices=["ckpt", "safetensors"], value="safetensors", label="Checkpoint format", elem_id="modelmerger_checkpoint_format")
                     save_as_half = gr.Checkbox(value=False, label="Save as float16", elem_id="modelmerger_save_as_half")
+                    save_metadata = gr.Checkbox(value=True, label="Save metadata (.safetensors only)", elem_id="modelmerger_save_metadata")
 
                 with FormRow():
                     with gr.Column():
@@ -1048,7 +1102,7 @@ def create_ui():
         with gr.Row(variant="compact").style(equal_height=False):
             with gr.Tabs(elem_id="train_tabs"):
 
-                with gr.Tab(label="Create embedding"):
+                with gr.Tab(label="Create embedding", id="create_embedding"):
                     new_embedding_name = gr.Textbox(label="Name", elem_id="train_new_embedding_name")
                     initialization_text = gr.Textbox(label="Initialization text", value="*", elem_id="train_initialization_text")
                     nvpt = gr.Slider(label="Number of vectors per token", minimum=1, maximum=75, step=1, value=1, elem_id="train_nvpt")
@@ -1061,7 +1115,7 @@ def create_ui():
                         with gr.Column():
                             create_embedding = gr.Button(value="Create embedding", variant='primary', elem_id="train_create_embedding")
 
-                with gr.Tab(label="Create hypernetwork"):
+                with gr.Tab(label="Create hypernetwork", id="create_hypernetwork"):
                     new_hypernetwork_name = gr.Textbox(label="Name", elem_id="train_new_hypernetwork_name")
                     new_hypernetwork_sizes = gr.CheckboxGroup(label="Modules", value=["768", "320", "640", "1280"], choices=["768", "1024", "320", "640", "1280"], elem_id="train_new_hypernetwork_sizes")
                     new_hypernetwork_layer_structure = gr.Textbox("1, 2, 1", label="Enter hypernetwork layer structure", placeholder="1st and last digit must be 1. ex:'1, 2, 1'", elem_id="train_new_hypernetwork_layer_structure")
@@ -1079,7 +1133,7 @@ def create_ui():
                         with gr.Column():
                             create_hypernetwork = gr.Button(value="Create hypernetwork", variant='primary', elem_id="train_create_hypernetwork")
 
-                with gr.Tab(label="Preprocess images"):
+                with gr.Tab(label="Preprocess images", id="preprocess_images"):
                     process_src = gr.Textbox(label='Source directory', elem_id="train_process_src")
                     process_dst = gr.Textbox(label='Destination directory', elem_id="train_process_dst")
                     process_width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="train_process_width")
@@ -1087,6 +1141,7 @@ def create_ui():
                     preprocess_txt_action = gr.Dropdown(label='Existing Caption txt Action', value="ignore", choices=["ignore", "copy", "prepend", "append"], elem_id="train_preprocess_txt_action")
 
                     with gr.Row():
+                        process_keep_original_size = gr.Checkbox(label='Keep original size', elem_id="train_process_keep_original_size")
                         process_flip = gr.Checkbox(label='Create flipped copies', elem_id="train_process_flip")
                         process_split = gr.Checkbox(label='Split oversized images', elem_id="train_process_split")
                         process_focal_crop = gr.Checkbox(label='Auto focal point crop', elem_id="train_process_focal_crop")
@@ -1146,7 +1201,7 @@ def create_ui():
                 def get_textual_inversion_template_names():
                     return sorted([x for x in textual_inversion.textual_inversion_templates])
 
-                with gr.Tab(label="Train"):
+                with gr.Tab(label="Train", id="train"):
                     gr.HTML(value="<p style='margin-bottom: 0.7em'>Train an embedding or Hypernetwork; you must specify a directory with a set of 1:1 ratio images <a href=\"https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Textual-Inversion\" style=\"font-weight:bold;\">[wiki]</a></p>")
                     with FormRow():
                         train_embedding_name = gr.Dropdown(label='Embedding', elem_id="train_embedding", choices=sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys()))
@@ -1204,7 +1259,7 @@ def create_ui():
 
             with gr.Column(elem_id='ti_gallery_container'):
                 ti_output = gr.Text(elem_id="ti_output", value="", show_label=False)
-                ti_gallery = gr.Gallery(label='Output', show_label=False, elem_id='ti_gallery').style(grid=4)
+                ti_gallery = gr.Gallery(label='Output', show_label=False, elem_id='ti_gallery').style(columns=4)
                 ti_progress = gr.HTML(elem_id="ti_progress", value="")
                 ti_outcome = gr.HTML(elem_id="ti_error", value="")
 
@@ -1253,6 +1308,7 @@ def create_ui():
                 process_width,
                 process_height,
                 preprocess_txt_action,
+                process_keep_original_size,
                 process_flip,
                 process_split,
                 process_caption,
@@ -1479,7 +1535,7 @@ def create_ui():
                 current_row.__exit__()
                 current_tab.__exit__()
 
-            with gr.TabItem("Actions"):
+            with gr.TabItem("Actions", id="actions"):
                 request_notifications = gr.Button(value='Request browser notifications', elem_id="request_notifications")
                 download_localization = gr.Button(value='Download localization template', elem_id="download_localization")
                 reload_script_bodies = gr.Button(value='Reload custom script bodies (No ui updates, No restart)', variant='secondary', elem_id="settings_reload_script_bodies")
@@ -1487,7 +1543,7 @@ def create_ui():
                     unload_sd_model = gr.Button(value='Unload SD checkpoint to free VRAM', elem_id="sett_unload_sd_model")
                     reload_sd_model = gr.Button(value='Reload the last SD checkpoint back into VRAM', elem_id="sett_reload_sd_model")
 
-            with gr.TabItem("Licenses"):
+            with gr.TabItem("Licenses", id="licenses"):
                 gr.HTML(shared.html("licenses.html"), elem_id="licenses")
 
             gr.Button(value="Show all pages", elem_id="settings_show_all_pages")
@@ -1565,7 +1621,7 @@ def create_ui():
     for _interface, label, _ifid in interfaces:
         shared.tab_names.append(label)
 
-    with gr.Blocks(analytics_enabled=False, title="Stable Diffusion") as demo:
+    with gr.Blocks(theme=shared.gradio_theme, analytics_enabled=False, title="Stable Diffusion") as demo:
         with gr.Row(elem_id="quicksettings", variant="compact"):
             for i, k, item in sorted(quicksettings_list, key=lambda x: quicksettings_names.get(x[1], x[0])):
                 component = create_setting_component(k, is_quicksettings=True)
@@ -1598,7 +1654,8 @@ def create_ui():
             component = component_dict[k]
             info = opts.data_labels[k]
 
-            component.change(
+            change_handler = component.release if hasattr(component, 'release') else component.change
+            change_handler(
                 fn=lambda value, k=k: run_settings_single(value, key=k),
                 inputs=[component],
                 outputs=[component, text_settings],
@@ -1658,6 +1715,7 @@ def create_ui():
                 config_source,
                 bake_in_vae,
                 discard_weights,
+                save_metadata,
             ],
             outputs=[
                 primary_model_name,
@@ -1705,7 +1763,7 @@ def create_ui():
                 if init_field is not None:
                     init_field(saved_value)
 
-        if type(x) in [gr.Slider, gr.Radio, gr.Checkbox, gr.Textbox, gr.Number, gr.Dropdown] and x.visible:
+        if type(x) in [gr.Slider, gr.Radio, gr.Checkbox, gr.Textbox, gr.Number, gr.Dropdown, ToolButton] and x.visible:
             apply_field(x, 'visible')
 
         if type(x) == gr.Slider:
@@ -1735,12 +1793,27 @@ def create_ui():
 
             apply_field(x, 'value', check_dropdown, getattr(x, 'init_field', None))
 
+        def check_tab_id(tab_id):
+            tab_items = list(filter(lambda e: isinstance(e, gr.TabItem), x.children))
+            if type(tab_id) == str:
+                tab_ids = [t.id for t in tab_items]
+                return tab_id in tab_ids
+            elif type(tab_id) == int:
+                return tab_id >= 0 and tab_id < len(tab_items)
+            else:
+                return False
+
+        if type(x) == gr.Tabs:
+            apply_field(x, 'selected', check_tab_id)
+
     visit(txt2img_interface, loadsave, "txt2img")
     visit(img2img_interface, loadsave, "img2img")
     visit(extras_interface, loadsave, "extras")
     visit(modelmerger_interface, loadsave, "modelmerger")
     visit(train_interface, loadsave, "train")
 
+    loadsave(f"webui/Tabs@{tabs.elem_id}", tabs)
+
     if not error_loading and (not os.path.exists(ui_config_file) or settings_count != len(ui_settings)):
         with open(ui_config_file, "w", encoding="utf8") as file:
             json.dump(ui_settings, file, indent=4)

modules/ui_common.py

@@ -125,7 +125,7 @@ Requested path was: {f}
 
     with gr.Column(variant='panel', elem_id=f"{tabname}_results"):
         with gr.Group(elem_id=f"{tabname}_gallery_container"):
-            result_gallery = gr.Gallery(label='Output', show_label=False, elem_id=f"{tabname}_gallery").style(grid=4)
+            result_gallery = gr.Gallery(label='Output', show_label=False, elem_id=f"{tabname}_gallery").style(columns=4)
 
         generation_info = None
         with gr.Column():

modules/ui_components.py

@@ -62,3 +62,13 @@ class DropdownMulti(FormComponent, gr.Dropdown):
 
     def get_block_name(self):
         return "dropdown"
+
+
+class DropdownEditable(FormComponent, gr.Dropdown):
+    """Same as gr.Dropdown but allows editing value"""
+    def __init__(self, **kwargs):
+        super().__init__(allow_custom_value=True, **kwargs)
+
+    def get_block_name(self):
+        return "dropdown"
+

modules/ui_extensions.py

@@ -2,6 +2,7 @@ import json
 import os.path
 import sys
 import time
+from datetime import datetime
 import traceback
 
 import git
@@ -11,10 +12,12 @@ import html
 import shutil
 import errno
 
-from modules import extensions, shared, paths
+from modules import extensions, shared, paths, config_states
+from modules.paths_internal import config_states_dir
 from modules.call_queue import wrap_gradio_gpu_call
 
 available_extensions = {"extensions": []}
+STYLE_PRIMARY = ' style="color: var(--primary-400)"'
 
 
 def check_access():
@@ -30,6 +33,9 @@ def apply_and_restart(disable_list, update_list, disable_all):
     update = json.loads(update_list)
     assert type(update) == list, f"wrong update_list data for apply_and_restart: {update_list}"
 
+    if update:
+        save_config_state("Backup (pre-update)")
+
     update = set(update)
 
     for ext in extensions.extensions:
@@ -50,6 +56,46 @@ def apply_and_restart(disable_list, update_list, disable_all):
     shared.state.need_restart = True
 
 
+def save_config_state(name):
+    current_config_state = config_states.get_config()
+    if not name:
+        name = "Config"
+    current_config_state["name"] = name
+    filename = os.path.join(config_states_dir, datetime.now().strftime("%Y_%m_%d-%H_%M_%S") + "_" + name + ".json")
+    print(f"Saving backup of webui/extension state to {filename}.")
+    with open(filename, "w", encoding="utf-8") as f:
+        json.dump(current_config_state, f)
+    config_states.list_config_states()
+    new_value = next(iter(config_states.all_config_states.keys()), "Current")
+    new_choices = ["Current"] + list(config_states.all_config_states.keys())
+    return gr.Dropdown.update(value=new_value, choices=new_choices), f"<span>Saved current webui/extension state to \"{filename}\"</span>"
+
+
+def restore_config_state(confirmed, config_state_name, restore_type):
+    if config_state_name == "Current":
+        return "<span>Select a config to restore from.</span>"
+    if not confirmed:
+        return "<span>Cancelled.</span>"
+
+    check_access()
+
+    config_state = config_states.all_config_states[config_state_name]
+
+    print(f"*** Restoring webui state from backup: {restore_type} ***")
+
+    if restore_type == "extensions" or restore_type == "both":
+        shared.opts.restore_config_state_file = config_state["filepath"]
+        shared.opts.save(shared.config_filename)
+
+    if restore_type == "webui" or restore_type == "both":
+        config_states.restore_webui_config(config_state)
+
+    shared.state.interrupt()
+    shared.state.need_restart = True
+
+    return ""
+
+
 def check_updates(id_task, disable_list):
     check_access()
 
@@ -76,6 +122,16 @@ def check_updates(id_task, disable_list):
     return extension_table(), ""
 
 
+def make_commit_link(commit_hash, remote, text=None):
+    if text is None:
+        text = commit_hash[:8]
+    if remote.startswith("https://github.com/"):
+        href = os.path.join(remote, "commit", commit_hash)
+        return f'<a href="{href}" target="_blank">{text}</a>'
+    else:
+        return text
+
+
 def extension_table():
     code = f"""<!-- {time.time()} -->
     <table id="extensions">
@@ -102,13 +158,17 @@ def extension_table():
 
         style = ""
         if shared.opts.disable_all_extensions == "extra" and not ext.is_builtin or shared.opts.disable_all_extensions == "all":
-            style = ' style="color: var(--primary-400)"'
+            style = STYLE_PRIMARY
+
+        version_link = ext.version
+        if ext.commit_hash and ext.remote:
+            version_link = make_commit_link(ext.commit_hash, ext.remote, ext.version)
 
         code += f"""
             <tr>
                 <td><label{style}><input class="gr-check-radio gr-checkbox" name="enable_{html.escape(ext.name)}" type="checkbox" {'checked="checked"' if ext.enabled else ''}>{html.escape(ext.name)}</label></td>
                 <td>{remote}</td>
-                <td>{ext.version}</td>
+                <td>{version_link}</td>
                 <td{' class="extension_status"' if ext.remote is not None else ''}>{ext_status}</td>
             </tr>
     """
@@ -121,6 +181,133 @@ def extension_table():
     return code
 
 
+def update_config_states_table(state_name):
+    if state_name == "Current":
+        config_state = config_states.get_config()
+    else:
+        config_state = config_states.all_config_states[state_name]
+
+    config_name = config_state.get("name", "Config")
+    created_date = time.asctime(time.gmtime(config_state["created_at"]))
+    filepath = config_state.get("filepath", "<unknown>")
+
+    code = f"""<!-- {time.time()} -->"""
+
+    webui_remote = config_state["webui"]["remote"] or ""
+    webui_branch = config_state["webui"]["branch"]
+    webui_commit_hash = config_state["webui"]["commit_hash"] or "<unknown>"
+    webui_commit_date = config_state["webui"]["commit_date"]
+    if webui_commit_date:
+        webui_commit_date = time.asctime(time.gmtime(webui_commit_date))
+    else:
+        webui_commit_date = "<unknown>"
+
+    remote = f"""<a href="{html.escape(webui_remote)}" target="_blank">{html.escape(webui_remote or '')}</a>"""
+    commit_link = make_commit_link(webui_commit_hash, webui_remote)
+    date_link = make_commit_link(webui_commit_hash, webui_remote, webui_commit_date)
+
+    current_webui = config_states.get_webui_config()
+
+    style_remote = ""
+    style_branch = ""
+    style_commit = ""
+    if current_webui["remote"] != webui_remote:
+        style_remote = STYLE_PRIMARY
+    if current_webui["branch"] != webui_branch:
+        style_branch = STYLE_PRIMARY
+    if current_webui["commit_hash"] != webui_commit_hash:
+        style_commit = STYLE_PRIMARY
+
+    code += f"""<h2>Config Backup: {config_name}</h2>
+      <div><b>Filepath:</b> {filepath}</div>
+      <div><b>Created at:</b> {created_date}</div>"""
+
+    code += f"""<h2>WebUI State</h2>
+      <table id="config_state_webui">
+        <thead>
+            <tr>
+                <th>URL</th>
+                <th>Branch</th>
+                <th>Commit</th>
+                <th>Date</th>
+            </tr>
+        </thead>
+        <tbody>
+            <tr>
+                <td><label{style_remote}>{remote}</label></td>
+                <td><label{style_branch}>{webui_branch}</label></td>
+                <td><label{style_commit}>{commit_link}</label></td>
+                <td><label{style_commit}>{date_link}</label></td>
+            </tr>
+        </tbody>
+      </table>
+    """
+
+    code += """<h2>Extension State</h2>
+      <table id="config_state_extensions">
+        <thead>
+            <tr>
+                <th>Extension</th>
+                <th>URL</th>
+                <th>Branch</th>
+                <th>Commit</th>
+                <th>Date</th>
+            </tr>
+        </thead>
+        <tbody>
+    """
+
+    ext_map = {ext.name: ext for ext in extensions.extensions}
+
+    for ext_name, ext_conf in config_state["extensions"].items():
+        ext_remote = ext_conf["remote"] or ""
+        ext_branch = ext_conf["branch"] or "<unknown>"
+        ext_enabled = ext_conf["enabled"]
+        ext_commit_hash = ext_conf["commit_hash"] or "<unknown>"
+        ext_commit_date = ext_conf["commit_date"]
+        if ext_commit_date:
+            ext_commit_date = time.asctime(time.gmtime(ext_commit_date))
+        else:
+            ext_commit_date = "<unknown>"
+
+        remote = f"""<a href="{html.escape(ext_remote)}" target="_blank">{html.escape(ext_remote or '')}</a>"""
+        commit_link = make_commit_link(ext_commit_hash, ext_remote)
+        date_link = make_commit_link(ext_commit_hash, ext_remote, ext_commit_date)
+
+        style_enabled = ""
+        style_remote = ""
+        style_branch = ""
+        style_commit = ""
+        if ext_name in ext_map:
+            current_ext = ext_map[ext_name]
+            current_ext.read_info_from_repo()
+            if current_ext.enabled != ext_enabled:
+                style_enabled = STYLE_PRIMARY
+            if current_ext.remote != ext_remote:
+                style_remote = STYLE_PRIMARY
+            if current_ext.branch != ext_branch:
+                style_branch = STYLE_PRIMARY
+            if current_ext.commit_hash != ext_commit_hash:
+                style_commit = STYLE_PRIMARY
+
+        code += f"""
+            <tr>
+                <td><label{style_enabled}><input class="gr-check-radio gr-checkbox" type="checkbox" disabled="true" {'checked="checked"' if ext_enabled else ''}>{html.escape(ext_name)}</label></td>
+                <td><label{style_remote}>{remote}</label></td>
+                <td><label{style_branch}>{ext_branch}</label></td>
+                <td><label{style_commit}>{commit_link}</label></td>
+                <td><label{style_commit}>{date_link}</label></td>
+            </tr>
+    """
+
+    code += """
+        </tbody>
+    </table>
+    """
+
+    return code
+
+
 def normalize_git_url(url):
     if url is None:
         return ""
@@ -129,7 +316,7 @@ def normalize_git_url(url):
     return url
 
 
-def install_extension_from_url(dirname, url):
+def install_extension_from_url(dirname, url, branch_name=None):
     check_access()
 
     assert url, 'No URL specified'
@@ -150,10 +337,17 @@ def install_extension_from_url(dirname, url):
 
     try:
         shutil.rmtree(tmpdir, True)
-        with git.Repo.clone_from(url, tmpdir) as repo:
-            repo.remote().fetch()
-            for submodule in repo.submodules:
-                submodule.update()
+        if not branch_name:
+            # if no branch is specified, use the default branch
+            with git.Repo.clone_from(url, tmpdir) as repo:
+                repo.remote().fetch()
+                for submodule in repo.submodules:
+                    submodule.update()
+        else:
+            with git.Repo.clone_from(url, tmpdir, branch=branch_name) as repo:
+                repo.remote().fetch()
+                for submodule in repo.submodules:
+                    submodule.update()
         try:
             os.rename(tmpdir, target_dir)
         except OSError as err:
@@ -292,9 +486,11 @@ def refresh_available_extensions_from_data(hide_tags, sort_column, filter_text="
 def create_ui():
     import modules.ui
 
+    config_states.list_config_states()
+
     with gr.Blocks(analytics_enabled=False) as ui:
         with gr.Tabs(elem_id="tabs_extensions") as tabs:
-            with gr.TabItem("Installed"):
+            with gr.TabItem("Installed", id="installed"):
 
                 with gr.Row(elem_id="extensions_installed_top"):
                     apply = gr.Button(value="Apply and restart UI", variant="primary")
@@ -327,7 +523,7 @@ def create_ui():
                     outputs=[extensions_table, info],
                 )
 
-            with gr.TabItem("Available"):
+            with gr.TabItem("Available", id="available"):
                 with gr.Row():
                     refresh_available_extensions_button = gr.Button(value="Load from:", variant="primary")
                     available_extensions_index = gr.Text(value="https://raw.githubusercontent.com/AUTOMATIC1111/stable-diffusion-webui-extensions/master/index.json", label="Extension index URL").style(container=False)
@@ -374,16 +570,41 @@ def create_ui():
                     outputs=[available_extensions_table, install_result]
                 )
 
-            with gr.TabItem("Install from URL"):
+            with gr.TabItem("Install from URL", id="install_from_url"):
                 install_url = gr.Text(label="URL for extension's git repository")
+                install_branch = gr.Text(label="Specific branch name", placeholder="Leave empty for default main branch")
                 install_dirname = gr.Text(label="Local directory name", placeholder="Leave empty for auto")
                 install_button = gr.Button(value="Install", variant="primary")
                 install_result = gr.HTML(elem_id="extension_install_result")
 
                 install_button.click(
                     fn=modules.ui.wrap_gradio_call(install_extension_from_url, extra_outputs=[gr.update()]),
-                    inputs=[install_dirname, install_url],
+                    inputs=[install_dirname, install_url, install_branch],
                     outputs=[extensions_table, install_result],
                 )
 
+            with gr.TabItem("Backup/Restore"):
+                with gr.Row(elem_id="extensions_backup_top_row"):
+                    config_states_list = gr.Dropdown(label="Saved Configs", elem_id="extension_backup_saved_configs", value="Current", choices=["Current"] + list(config_states.all_config_states.keys()))
+                    modules.ui.create_refresh_button(config_states_list, config_states.list_config_states, lambda: {"choices": ["Current"] + list(config_states.all_config_states.keys())}, "refresh_config_states")
+                    config_restore_type = gr.Radio(label="State to restore", choices=["extensions", "webui", "both"], value="extensions", elem_id="extension_backup_restore_type")
+                    config_restore_button = gr.Button(value="Restore Selected Config", variant="primary", elem_id="extension_backup_restore")
+                with gr.Row(elem_id="extensions_backup_top_row2"):
+                    config_save_name = gr.Textbox("", placeholder="Config Name", show_label=False)
+                    config_save_button = gr.Button(value="Save Current Config")
+
+                config_states_info = gr.HTML("")
+                config_states_table = gr.HTML(lambda: update_config_states_table("Current"))
+
+                config_save_button.click(fn=save_config_state, inputs=[config_save_name], outputs=[config_states_list, config_states_info])
+
+                dummy_component = gr.Label(visible=False)
+                config_restore_button.click(fn=restore_config_state, _js="config_state_confirm_restore", inputs=[dummy_component, config_states_list, config_restore_type], outputs=[config_states_info])
+
+                config_states_list.change(
+                    fn=update_config_states_table,
+                    inputs=[config_states_list],
+                    outputs=[config_states_table],
+                )
+
     return ui

modules/ui_extra_networks.py

@@ -241,7 +241,7 @@ def create_ui(container, button, tabname):
 
     with gr.Tabs(elem_id=tabname+"_extra_tabs") as tabs:
         for page in ui.stored_extra_pages:
-            with gr.Tab(page.title):
+            with gr.Tab(page.title, id=page.title.lower().replace(" ", "_")):
 
                 page_elem = gr.HTML(page.create_html(ui.tabname))
                 ui.pages.append(page_elem)

modules/ui_postprocessing.py

@@ -9,13 +9,13 @@ def create_ui():
     with gr.Row().style(equal_height=False, variant='compact'):
         with gr.Column(variant='compact'):
             with gr.Tabs(elem_id="mode_extras"):
-                with gr.TabItem('Single Image', elem_id="extras_single_tab") as tab_single:
+                with gr.TabItem('Single Image', id="single_image", elem_id="extras_single_tab") as tab_single:
                     extras_image = gr.Image(label="Source", source="upload", interactive=True, type="pil", elem_id="extras_image")
 
-                with gr.TabItem('Batch Process', elem_id="extras_batch_process_tab") as tab_batch:
-                    image_batch = gr.File(label="Batch Process", file_count="multiple", interactive=True, type="file", elem_id="extras_image_batch")
+                with gr.TabItem('Batch Process', id="batch_process", elem_id="extras_batch_process_tab") as tab_batch:
+                    image_batch = gr.Files(label="Batch Process", interactive=True, elem_id="extras_image_batch")
 
-                with gr.TabItem('Batch from Directory', elem_id="extras_batch_directory_tab") as tab_batch_dir:
+                with gr.TabItem('Batch from Directory', id="batch_from_directory", elem_id="extras_batch_directory_tab") as tab_batch_dir:
                     extras_batch_input_dir = gr.Textbox(label="Input directory", **shared.hide_dirs, placeholder="A directory on the same machine where the server is running.", elem_id="extras_batch_input_dir")
                     extras_batch_output_dir = gr.Textbox(label="Output directory", **shared.hide_dirs, placeholder="Leave blank to save images to the default path.", elem_id="extras_batch_output_dir")
                     show_extras_results = gr.Checkbox(label='Show result images', value=True, elem_id="extras_show_extras_results")