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-rw-r--r--modules/api/api.py25
-rw-r--r--modules/call_queue.py3
-rw-r--r--modules/cmd_args.py2
-rw-r--r--modules/codeformer_model.py4
-rw-r--r--modules/esrgan_model.py23
-rw-r--r--modules/extensions.py3
-rw-r--r--modules/generation_parameters_copypaste.py22
-rw-r--r--modules/gfpgan_model.py7
-rw-r--r--modules/images.py2
-rw-r--r--modules/img2img.py5
-rw-r--r--modules/launch_utils.py4
-rw-r--r--modules/modelloader.py34
-rw-r--r--modules/processing.py52
-rw-r--r--modules/realesrgan_model.py33
-rw-r--r--modules/scripts.py3
-rw-r--r--modules/sd_hijack_optimizations.py2
-rw-r--r--modules/sd_models.py10
-rw-r--r--modules/sd_samplers_kdiffusion.py11
-rw-r--r--modules/shared.py5
-rw-r--r--modules/textual_inversion/autocrop.py3
-rw-r--r--modules/textual_inversion/logging.py48
-rw-r--r--modules/txt2img.py6
-rw-r--r--modules/ui.py6
-rw-r--r--modules/ui_extensions.py16
24 files changed, 229 insertions, 100 deletions
diff --git a/modules/api/api.py b/modules/api/api.py
index 41cd7eca..279c384a 100644
--- a/modules/api/api.py
+++ b/modules/api/api.py
@@ -14,7 +14,7 @@ from fastapi.encoders import jsonable_encoder
from secrets import compare_digest
import modules.shared as shared
-from modules import sd_samplers, deepbooru, sd_hijack, images, scripts, ui, postprocessing, errors
+from modules import sd_samplers, deepbooru, sd_hijack, images, scripts, ui, postprocessing, errors, restart
from modules.api import models
from modules.shared import opts
from modules.processing import StableDiffusionProcessingTxt2Img, StableDiffusionProcessingImg2Img, process_images
@@ -22,7 +22,7 @@ from modules.textual_inversion.textual_inversion import create_embedding, train_
from modules.textual_inversion.preprocess import preprocess
from modules.hypernetworks.hypernetwork import create_hypernetwork, train_hypernetwork
from PIL import PngImagePlugin,Image
-from modules.sd_models import checkpoints_list, unload_model_weights, reload_model_weights
+from modules.sd_models import checkpoints_list, unload_model_weights, reload_model_weights, checkpoint_alisases
from modules.sd_vae import vae_dict
from modules.sd_models_config import find_checkpoint_config_near_filename
from modules.realesrgan_model import get_realesrgan_models
@@ -202,6 +202,11 @@ class Api:
self.add_api_route("/sdapi/v1/scripts", self.get_scripts_list, methods=["GET"], response_model=models.ScriptsList)
self.add_api_route("/sdapi/v1/script-info", self.get_script_info, methods=["GET"], response_model=List[models.ScriptInfo])
+ if shared.cmd_opts.add_stop_route:
+ self.add_api_route("/sdapi/v1/server-kill", self.kill_webui, methods=["POST"])
+ self.add_api_route("/sdapi/v1/server-restart", self.restart_webui, methods=["POST"])
+ self.add_api_route("/sdapi/v1/server-stop", self.stop_webui, methods=["POST"])
+
self.default_script_arg_txt2img = []
self.default_script_arg_img2img = []
@@ -510,6 +515,10 @@ class Api:
return options
def set_config(self, req: Dict[str, Any]):
+ checkpoint_name = req.get("sd_model_checkpoint", None)
+ if checkpoint_name is not None and checkpoint_name not in checkpoint_alisases:
+ raise RuntimeError(f"model {checkpoint_name!r} not found")
+
for k, v in req.items():
shared.opts.set(k, v)
@@ -708,3 +717,15 @@ class Api:
def launch(self, server_name, port):
self.app.include_router(self.router)
uvicorn.run(self.app, host=server_name, port=port, timeout_keep_alive=0)
+
+ def kill_webui(self):
+ restart.stop_program()
+
+ def restart_webui(self):
+ if restart.is_restartable():
+ restart.restart_program()
+ return Response(status_code=501)
+
+ def stop_webui(request):
+ shared.state.server_command = "stop"
+ return Response("Stopping.")
diff --git a/modules/call_queue.py b/modules/call_queue.py
index 1b5e5273..69bf63d2 100644
--- a/modules/call_queue.py
+++ b/modules/call_queue.py
@@ -1,3 +1,4 @@
+from functools import wraps
import html
import threading
import time
@@ -18,6 +19,7 @@ def wrap_queued_call(func):
def wrap_gradio_gpu_call(func, extra_outputs=None):
+ @wraps(func)
def f(*args, **kwargs):
# if the first argument is a string that says "task(...)", it is treated as a job id
@@ -45,6 +47,7 @@ def wrap_gradio_gpu_call(func, extra_outputs=None):
def wrap_gradio_call(func, extra_outputs=None, add_stats=False):
+ @wraps(func)
def f(*args, extra_outputs_array=extra_outputs, **kwargs):
run_memmon = shared.opts.memmon_poll_rate > 0 and not shared.mem_mon.disabled and add_stats
if run_memmon:
diff --git a/modules/cmd_args.py b/modules/cmd_args.py
index de905caa..624dcb4f 100644
--- a/modules/cmd_args.py
+++ b/modules/cmd_args.py
@@ -106,4 +106,4 @@ parser.add_argument("--skip-version-check", action='store_true', help="Do not ch
parser.add_argument("--no-hashing", action='store_true', help="disable sha256 hashing of checkpoints to help loading performance", default=False)
parser.add_argument("--no-download-sd-model", action='store_true', help="don't download SD1.5 model even if no model is found in --ckpt-dir", default=False)
parser.add_argument('--subpath', type=str, help='customize the subpath for gradio, use with reverse proxy')
-parser.add_argument('--add-stop-route', action='store_true', help='add /_stop route to stop server')
+parser.add_argument('--add-stop-route', action='store_true', help='enable server stop/restart/kill via api')
diff --git a/modules/codeformer_model.py b/modules/codeformer_model.py
index a01fe63d..f293acf5 100644
--- a/modules/codeformer_model.py
+++ b/modules/codeformer_model.py
@@ -19,9 +19,7 @@ codeformer = None
def setup_model(dirname):
- global model_path
- if not os.path.exists(model_path):
- os.makedirs(model_path)
+ os.makedirs(model_path, exist_ok=True)
path = modules.paths.paths.get("CodeFormer", None)
if path is None:
diff --git a/modules/esrgan_model.py b/modules/esrgan_model.py
index 2fced999..02a1727d 100644
--- a/modules/esrgan_model.py
+++ b/modules/esrgan_model.py
@@ -1,15 +1,13 @@
-import os
+import sys
import numpy as np
import torch
from PIL import Image
-from basicsr.utils.download_util import load_file_from_url
import modules.esrgan_model_arch as arch
from modules import modelloader, images, devices
-from modules.upscaler import Upscaler, UpscalerData
from modules.shared import opts
-
+from modules.upscaler import Upscaler, UpscalerData
def mod2normal(state_dict):
@@ -134,7 +132,7 @@ class UpscalerESRGAN(Upscaler):
scaler_data = UpscalerData(self.model_name, self.model_url, self, 4)
scalers.append(scaler_data)
for file in model_paths:
- if "http" in file:
+ if file.startswith("http"):
name = self.model_name
else:
name = modelloader.friendly_name(file)
@@ -143,26 +141,25 @@ class UpscalerESRGAN(Upscaler):
self.scalers.append(scaler_data)
def do_upscale(self, img, selected_model):
- model = self.load_model(selected_model)
- if model is None:
+ try:
+ model = self.load_model(selected_model)
+ except Exception as e:
+ print(f"Unable to load ESRGAN model {selected_model}: {e}", file=sys.stderr)
return img
model.to(devices.device_esrgan)
img = esrgan_upscale(model, img)
return img
def load_model(self, path: str):
- if "http" in path:
- filename = load_file_from_url(
+ if path.startswith("http"):
+ # TODO: this doesn't use `path` at all?
+ filename = modelloader.load_file_from_url(
url=self.model_url,
model_dir=self.model_download_path,
file_name=f"{self.model_name}.pth",
- progress=True,
)
else:
filename = path
- if not os.path.exists(filename) or filename is None:
- print(f"Unable to load {self.model_path} from {filename}")
- return None
state_dict = torch.load(filename, map_location='cpu' if devices.device_esrgan.type == 'mps' else None)
diff --git a/modules/extensions.py b/modules/extensions.py
index 8608584b..abc6e2b1 100644
--- a/modules/extensions.py
+++ b/modules/extensions.py
@@ -7,8 +7,7 @@ from modules.paths_internal import extensions_dir, extensions_builtin_dir, scrip
extensions = []
-if not os.path.exists(extensions_dir):
- os.makedirs(extensions_dir)
+os.makedirs(extensions_dir, exist_ok=True)
def active():
diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py
index 699b1a81..a3448be9 100644
--- a/modules/generation_parameters_copypaste.py
+++ b/modules/generation_parameters_copypaste.py
@@ -252,15 +252,18 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model
res["Negative prompt"] = negative_prompt
for k, v in re_param.findall(lastline):
- if v[0] == '"' and v[-1] == '"':
- v = unquote(v)
-
- m = re_imagesize.match(v)
- if m is not None:
- res[f"{k}-1"] = m.group(1)
- res[f"{k}-2"] = m.group(2)
- else:
- res[k] = v
+ try:
+ if v[0] == '"' and v[-1] == '"':
+ v = unquote(v)
+
+ m = re_imagesize.match(v)
+ if m is not None:
+ res[f"{k}-1"] = m.group(1)
+ res[f"{k}-2"] = m.group(2)
+ else:
+ res[k] = v
+ except Exception:
+ print(f"Error parsing \"{k}: {v}\"")
# Missing CLIP skip means it was set to 1 (the default)
if "Clip skip" not in res:
@@ -325,6 +328,7 @@ infotext_to_setting_name_mapping = [
('Token merging ratio hr', 'token_merging_ratio_hr'),
('RNG', 'randn_source'),
('NGMS', 's_min_uncond'),
+ ('Pad conds', 'pad_cond_uncond'),
]
diff --git a/modules/gfpgan_model.py b/modules/gfpgan_model.py
index e239a09d..8e0f13bd 100644
--- a/modules/gfpgan_model.py
+++ b/modules/gfpgan_model.py
@@ -25,7 +25,7 @@ def gfpgann():
return None
models = modelloader.load_models(model_path, model_url, user_path, ext_filter="GFPGAN")
- if len(models) == 1 and "http" in models[0]:
+ if len(models) == 1 and models[0].startswith("http"):
model_file = models[0]
elif len(models) != 0:
latest_file = max(models, key=os.path.getctime)
@@ -70,11 +70,8 @@ gfpgan_constructor = None
def setup_model(dirname):
- global model_path
- if not os.path.exists(model_path):
- os.makedirs(model_path)
-
try:
+ os.makedirs(model_path, exist_ok=True)
from gfpgan import GFPGANer
from facexlib import detection, parsing # noqa: F401
global user_path
diff --git a/modules/images.py b/modules/images.py
index 7bbfc3e0..1906e2ab 100644
--- a/modules/images.py
+++ b/modules/images.py
@@ -372,8 +372,8 @@ class FilenameGenerator:
'hasprompt': lambda self, *args: self.hasprompt(*args), # accepts formats:[hasprompt<prompt1|default><prompt2>..]
'clip_skip': lambda self: opts.data["CLIP_stop_at_last_layers"],
'denoising': lambda self: self.p.denoising_strength if self.p and self.p.denoising_strength else NOTHING_AND_SKIP_PREVIOUS_TEXT,
+ 'user': lambda self: self.p.user,
'vae_filename': lambda self: self.get_vae_filename(),
-
}
default_time_format = '%Y%m%d%H%M%S'
diff --git a/modules/img2img.py b/modules/img2img.py
index 2c497020..b07d7f2f 100644
--- a/modules/img2img.py
+++ b/modules/img2img.py
@@ -3,6 +3,7 @@ from pathlib import Path
import numpy as np
from PIL import Image, ImageOps, ImageFilter, ImageEnhance, ImageChops, UnidentifiedImageError
+import gradio as gr
from modules import sd_samplers
from modules.generation_parameters_copypaste import create_override_settings_dict
@@ -97,7 +98,7 @@ def process_batch(p, input_dir, output_dir, inpaint_mask_dir, args, to_scale=Fal
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, 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):
+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, request: gr.Request, *args):
override_settings = create_override_settings_dict(override_settings_texts)
is_batch = mode == 5
@@ -180,6 +181,8 @@ def img2img(id_task: str, mode: int, prompt: str, negative_prompt: str, prompt_s
p.scripts = modules.scripts.scripts_img2img
p.script_args = args
+ p.user = request.username
+
if shared.cmd_opts.enable_console_prompts:
print(f"\nimg2img: {prompt}", file=shared.progress_print_out)
diff --git a/modules/launch_utils.py b/modules/launch_utils.py
index 609a181e..97539e68 100644
--- a/modules/launch_utils.py
+++ b/modules/launch_utils.py
@@ -147,10 +147,10 @@ def git_clone(url, dir, name, commithash=None):
return
run(f'"{git}" -C "{dir}" fetch', f"Fetching updates for {name}...", f"Couldn't fetch {name}")
- run(f'"{git}" -C "{dir}" checkout {commithash}', f"Checking out commit for {name} with hash: {commithash}...", f"Couldn't checkout commit {commithash} for {name}")
+ run(f'"{git}" -C "{dir}" checkout {commithash}', f"Checking out commit for {name} with hash: {commithash}...", f"Couldn't checkout commit {commithash} for {name}", live=True)
return
- run(f'"{git}" clone "{url}" "{dir}"', f"Cloning {name} into {dir}...", f"Couldn't clone {name}")
+ run(f'"{git}" clone "{url}" "{dir}"', f"Cloning {name} into {dir}...", f"Couldn't clone {name}", live=True)
if commithash is not None:
run(f'"{git}" -C "{dir}" checkout {commithash}', None, "Couldn't checkout {name}'s hash: {commithash}")
diff --git a/modules/modelloader.py b/modules/modelloader.py
index be23071a..098bcb79 100644
--- a/modules/modelloader.py
+++ b/modules/modelloader.py
@@ -1,3 +1,5 @@
+from __future__ import annotations
+
import os
import shutil
import importlib
@@ -8,6 +10,29 @@ from modules.upscaler import Upscaler, UpscalerLanczos, UpscalerNearest, Upscale
from modules.paths import script_path, models_path
+def load_file_from_url(
+ url: str,
+ *,
+ model_dir: str,
+ progress: bool = True,
+ file_name: str | None = None,
+) -> str:
+ """Download a file from `url` into `model_dir`, using the file present if possible.
+
+ Returns the path to the downloaded file.
+ """
+ os.makedirs(model_dir, exist_ok=True)
+ if not file_name:
+ parts = urlparse(url)
+ file_name = os.path.basename(parts.path)
+ cached_file = os.path.abspath(os.path.join(model_dir, file_name))
+ if not os.path.exists(cached_file):
+ print(f'Downloading: "{url}" to {cached_file}\n')
+ from torch.hub import download_url_to_file
+ download_url_to_file(url, cached_file, progress=progress)
+ return cached_file
+
+
def load_models(model_path: str, model_url: str = None, command_path: str = None, ext_filter=None, download_name=None, ext_blacklist=None) -> list:
"""
A one-and done loader to try finding the desired models in specified directories.
@@ -46,9 +71,7 @@ def load_models(model_path: str, model_url: str = None, command_path: str = None
if model_url is not None and len(output) == 0:
if download_name is not None:
- from basicsr.utils.download_util import load_file_from_url
- dl = load_file_from_url(model_url, places[0], True, download_name)
- output.append(dl)
+ output.append(load_file_from_url(model_url, model_dir=places[0], file_name=download_name))
else:
output.append(model_url)
@@ -59,7 +82,7 @@ def load_models(model_path: str, model_url: str = None, command_path: str = None
def friendly_name(file: str):
- if "http" in file:
+ if file.startswith("http"):
file = urlparse(file).path
file = os.path.basename(file)
@@ -95,8 +118,7 @@ def cleanup_models():
def move_files(src_path: str, dest_path: str, ext_filter: str = None):
try:
- if not os.path.exists(dest_path):
- os.makedirs(dest_path)
+ os.makedirs(dest_path, exist_ok=True)
if os.path.exists(src_path):
for file in os.listdir(src_path):
fullpath = os.path.join(src_path, file)
diff --git a/modules/processing.py b/modules/processing.py
index f8225b83..d7df5db0 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -7,7 +7,7 @@ import hashlib
import torch
import numpy as np
-from PIL import Image, ImageFilter, ImageOps
+from PIL import Image, ImageOps
import random
import cv2
from skimage import exposure
@@ -106,6 +106,9 @@ class StableDiffusionProcessing:
"""
The first set of paramaters: sd_models -> do_not_reload_embeddings represent the minimum required to create a StableDiffusionProcessing
"""
+ cached_uc = [None, None]
+ cached_c = [None, 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)
@@ -176,11 +179,13 @@ class StableDiffusionProcessing:
self.subseeds = None
self.step_multiplier = 1
- self.cached_uc = [None, None]
- self.cached_c = [None, None]
+ self.cached_uc = StableDiffusionProcessing.cached_uc
+ self.cached_c = StableDiffusionProcessing.cached_c
self.uc = None
self.c = None
+ self.user = None
+
@property
def sd_model(self):
return shared.sd_model
@@ -289,8 +294,9 @@ class StableDiffusionProcessing:
self.sampler = None
self.c = None
self.uc = None
- self.cached_c = [None, None]
- self.cached_uc = [None, None]
+ if not opts.experimental_persistent_cond_cache:
+ StableDiffusionProcessing.cached_c = [None, None]
+ StableDiffusionProcessing.cached_uc = [None, None]
def get_token_merging_ratio(self, for_hr=False):
if for_hr:
@@ -324,7 +330,6 @@ class StableDiffusionProcessing:
caches is a list with items described above.
"""
-
for cache in caches:
if cache[0] is not None and (required_prompts, steps, opts.CLIP_stop_at_last_layers, shared.sd_model.sd_checkpoint_info, extra_network_data) == cache[0]:
return cache[1]
@@ -340,7 +345,6 @@ class StableDiffusionProcessing:
def setup_conds(self):
sampler_config = sd_samplers.find_sampler_config(self.sampler_name)
self.step_multiplier = 2 if sampler_config and sampler_config.options.get("second_order", False) else 1
-
self.uc = self.get_conds_with_caching(prompt_parser.get_learned_conditioning, self.negative_prompts, self.steps * self.step_multiplier, [self.cached_uc], self.extra_network_data)
self.c = self.get_conds_with_caching(prompt_parser.get_multicond_learned_conditioning, self.prompts, self.steps * self.step_multiplier, [self.cached_c], self.extra_network_data)
@@ -583,6 +587,7 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter
"NGMS": None if p.s_min_uncond == 0 else p.s_min_uncond,
**p.extra_generation_params,
"Version": program_version() if opts.add_version_to_infotext else None,
+ "User": p.user if opts.add_user_name_to_info else None,
}
generation_params_text = ", ".join([k if k == v else f'{k}: {generation_parameters_copypaste.quote(v)}' for k, v in generation_params.items() if v is not None])
@@ -868,6 +873,8 @@ def old_hires_fix_first_pass_dimensions(width, height):
class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
sampler = None
+ cached_hr_uc = [None, None]
+ cached_hr_c = [None, None]
def __init__(self, enable_hr: bool = False, denoising_strength: float = 0.75, firstphase_width: int = 0, firstphase_height: int = 0, hr_scale: float = 2.0, hr_upscaler: str = None, hr_second_pass_steps: int = 0, hr_resize_x: int = 0, hr_resize_y: int = 0, hr_sampler_name: str = None, hr_prompt: str = '', hr_negative_prompt: str = '', **kwargs):
super().__init__(**kwargs)
@@ -900,8 +907,8 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
self.hr_negative_prompts = None
self.hr_extra_network_data = None
- self.cached_hr_uc = [None, None]
- self.cached_hr_c = [None, None]
+ self.cached_hr_uc = StableDiffusionProcessingTxt2Img.cached_hr_uc
+ self.cached_hr_c = StableDiffusionProcessingTxt2Img.cached_hr_c
self.hr_c = None
self.hr_uc = None
@@ -1079,10 +1086,12 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
return samples
def close(self):
- self.cached_hr_uc = [None, None]
- self.cached_hr_c = [None, None]
+ super().close()
self.hr_c = None
self.hr_uc = None
+ if not opts.experimental_persistent_cond_cache:
+ StableDiffusionProcessingTxt2Img.cached_hr_uc = [None, None]
+ StableDiffusionProcessingTxt2Img.cached_hr_c = [None, None]
def setup_prompts(self):
super().setup_prompts()
@@ -1150,7 +1159,7 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
class StableDiffusionProcessingImg2Img(StableDiffusionProcessing):
sampler = None
- def __init__(self, init_images: list = None, resize_mode: int = 0, denoising_strength: float = 0.75, image_cfg_scale: float = None, mask: Any = None, mask_blur: int = 4, inpainting_fill: int = 0, inpaint_full_res: bool = True, inpaint_full_res_padding: int = 0, inpainting_mask_invert: int = 0, initial_noise_multiplier: float = None, **kwargs):
+ def __init__(self, init_images: list = None, resize_mode: int = 0, denoising_strength: float = 0.75, image_cfg_scale: float = None, mask: Any = None, mask_blur: int = None, mask_blur_x: int = 4, mask_blur_y: int = 4, inpainting_fill: int = 0, inpaint_full_res: bool = True, inpaint_full_res_padding: int = 0, inpainting_mask_invert: int = 0, initial_noise_multiplier: float = None, **kwargs):
super().__init__(**kwargs)
self.init_images = init_images
@@ -1161,7 +1170,11 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing):
self.image_mask = mask
self.latent_mask = None
self.mask_for_overlay = None
- self.mask_blur = mask_blur
+ if mask_blur is not None:
+ mask_blur_x = mask_blur
+ mask_blur_y = mask_blur
+ self.mask_blur_x = mask_blur_x
+ self.mask_blur_y = mask_blur_y
self.inpainting_fill = inpainting_fill
self.inpaint_full_res = inpaint_full_res
self.inpaint_full_res_padding = inpaint_full_res_padding
@@ -1183,8 +1196,17 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing):
if self.inpainting_mask_invert:
image_mask = ImageOps.invert(image_mask)
- if self.mask_blur > 0:
- image_mask = image_mask.filter(ImageFilter.GaussianBlur(self.mask_blur))
+ if self.mask_blur_x > 0:
+ np_mask = np.array(image_mask)
+ kernel_size = 2 * int(4 * self.mask_blur_x + 0.5) + 1
+ np_mask = cv2.GaussianBlur(np_mask, (kernel_size, 1), self.mask_blur_x)
+ image_mask = Image.fromarray(np_mask)
+
+ if self.mask_blur_y > 0:
+ np_mask = np.array(image_mask)
+ kernel_size = 2 * int(4 * self.mask_blur_y + 0.5) + 1
+ np_mask = cv2.GaussianBlur(np_mask, (1, kernel_size), self.mask_blur_y)
+ image_mask = Image.fromarray(np_mask)
if self.inpaint_full_res:
self.mask_for_overlay = image_mask
diff --git a/modules/realesrgan_model.py b/modules/realesrgan_model.py
index 2d27b321..0700b853 100644
--- a/modules/realesrgan_model.py
+++ b/modules/realesrgan_model.py
@@ -2,7 +2,6 @@ import os
import numpy as np
from PIL import Image
-from basicsr.utils.download_util import load_file_from_url
from realesrgan import RealESRGANer
from modules.upscaler import Upscaler, UpscalerData
@@ -43,9 +42,10 @@ class UpscalerRealESRGAN(Upscaler):
if not self.enable:
return img
- info = self.load_model(path)
- if not os.path.exists(info.local_data_path):
- print(f"Unable to load RealESRGAN model: {info.name}")
+ try:
+ info = self.load_model(path)
+ except Exception:
+ errors.report(f"Unable to load RealESRGAN model {path}", exc_info=True)
return img
upsampler = RealESRGANer(
@@ -63,20 +63,17 @@ class UpscalerRealESRGAN(Upscaler):
return image
def load_model(self, path):
- try:
- info = next(iter([scaler for scaler in self.scalers if scaler.data_path == path]), None)
-
- if info is None:
- print(f"Unable to find model info: {path}")
- return None
-
- if info.local_data_path.startswith("http"):
- info.local_data_path = load_file_from_url(url=info.data_path, model_dir=self.model_download_path, progress=True)
-
- return info
- except Exception:
- errors.report("Error making Real-ESRGAN models list", exc_info=True)
- return None
+ for scaler in self.scalers:
+ if scaler.data_path == path:
+ if scaler.local_data_path.startswith("http"):
+ scaler.local_data_path = modelloader.load_file_from_url(
+ scaler.data_path,
+ model_dir=self.model_download_path,
+ )
+ if not os.path.exists(scaler.local_data_path):
+ raise FileNotFoundError(f"RealESRGAN data missing: {scaler.local_data_path}")
+ return scaler
+ raise ValueError(f"Unable to find model info: {path}")
def load_models(self, _):
return get_realesrgan_models(self)
diff --git a/modules/scripts.py b/modules/scripts.py
index 99bf836a..49e4a611 100644
--- a/modules/scripts.py
+++ b/modules/scripts.py
@@ -1,6 +1,7 @@
import os
import re
import sys
+import inspect
from collections import namedtuple
import gradio as gr
@@ -249,7 +250,7 @@ def load_scripts():
def register_scripts_from_module(module):
for script_class in module.__dict__.values():
- if type(script_class) != type:
+ if not inspect.isclass(script_class):
continue
if issubclass(script_class, Script):
diff --git a/modules/sd_hijack_optimizations.py b/modules/sd_hijack_optimizations.py
index 3c71e6b5..53e27ade 100644
--- a/modules/sd_hijack_optimizations.py
+++ b/modules/sd_hijack_optimizations.py
@@ -602,7 +602,7 @@ def sdp_attnblock_forward(self, x):
q, k, v = (rearrange(t, 'b c h w -> b (h w) c') for t in (q, k, v))
dtype = q.dtype
if shared.opts.upcast_attn:
- q, k = q.float(), k.float()
+ q, k, v = q.float(), k.float(), v.float()
q = q.contiguous()
k = k.contiguous()
v = v.contiguous()
diff --git a/modules/sd_models.py b/modules/sd_models.py
index 918f6fd6..f65f4e36 100644
--- a/modules/sd_models.py
+++ b/modules/sd_models.py
@@ -95,8 +95,7 @@ except Exception:
def setup_model():
- if not os.path.exists(model_path):
- os.makedirs(model_path)
+ os.makedirs(model_path, exist_ok=True)
enable_midas_autodownload()
@@ -248,7 +247,12 @@ def read_state_dict(checkpoint_file, print_global_state=False, map_location=None
_, extension = os.path.splitext(checkpoint_file)
if extension.lower() == ".safetensors":
device = map_location or shared.weight_load_location or devices.get_optimal_device_name()
- pl_sd = safetensors.torch.load_file(checkpoint_file, device=device)
+
+ if not shared.opts.disable_mmap_load_safetensors:
+ pl_sd = safetensors.torch.load_file(checkpoint_file, device=device)
+ else:
+ pl_sd = safetensors.torch.load(open(checkpoint_file, 'rb').read())
+ pl_sd = {k: v.to(device) for k, v in pl_sd.items()}
else:
pl_sd = torch.load(checkpoint_file, map_location=map_location or shared.weight_load_location)
diff --git a/modules/sd_samplers_kdiffusion.py b/modules/sd_samplers_kdiffusion.py
index f8a0c7ba..71581b76 100644
--- a/modules/sd_samplers_kdiffusion.py
+++ b/modules/sd_samplers_kdiffusion.py
@@ -69,6 +69,7 @@ class CFGDenoiser(torch.nn.Module):
self.init_latent = None
self.step = 0
self.image_cfg_scale = None
+ self.padded_cond_uncond = False
def combine_denoised(self, x_out, conds_list, uncond, cond_scale):
denoised_uncond = x_out[-uncond.shape[0]:]
@@ -133,15 +134,17 @@ class CFGDenoiser(torch.nn.Module):
x_in = x_in[:-batch_size]
sigma_in = sigma_in[:-batch_size]
- # TODO add infotext entry
+ self.padded_cond_uncond = False
if shared.opts.pad_cond_uncond and tensor.shape[1] != uncond.shape[1]:
empty = shared.sd_model.cond_stage_model_empty_prompt
num_repeats = (tensor.shape[1] - uncond.shape[1]) // empty.shape[1]
if num_repeats < 0:
tensor = torch.cat([tensor, empty.repeat((tensor.shape[0], -num_repeats, 1))], axis=1)
+ self.padded_cond_uncond = True
elif num_repeats > 0:
uncond = torch.cat([uncond, empty.repeat((uncond.shape[0], num_repeats, 1))], axis=1)
+ self.padded_cond_uncond = True
if tensor.shape[1] == uncond.shape[1] or skip_uncond:
if is_edit_model:
@@ -405,6 +408,9 @@ class KDiffusionSampler:
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))
+ if self.model_wrap_cfg.padded_cond_uncond:
+ p.extra_generation_params["Pad conds"] = True
+
return samples
def sample(self, p, x, conditioning, unconditional_conditioning, steps=None, image_conditioning=None):
@@ -438,5 +444,8 @@ class KDiffusionSampler:
's_min_uncond': self.s_min_uncond
}, disable=False, callback=self.callback_state, **extra_params_kwargs))
+ if self.model_wrap_cfg.padded_cond_uncond:
+ p.extra_generation_params["Pad conds"] = True
+
return samples
diff --git a/modules/shared.py b/modules/shared.py
index c9ee2dd1..203ee1b9 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -376,6 +376,7 @@ options_templates.update(options_section(('system', "System"), {
"multiple_tqdm": OptionInfo(True, "Add a second progress bar to the console that shows progress for an entire job."),
"print_hypernet_extra": OptionInfo(False, "Print extra hypernetwork information to console."),
"list_hidden_files": OptionInfo(True, "Load models/files in hidden directories").info("directory is hidden if its name starts with \".\""),
+ "disable_mmap_load_safetensors": OptionInfo(False, "Disable memmapping for loading .safetensors files.").info("fixes very slow loading speed in some cases"),
}))
options_templates.update(options_section(('training', "Training"), {
@@ -409,7 +410,7 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), {
"enable_emphasis": OptionInfo(True, "Enable emphasis").info("use (text) to make model pay more attention to text and [text] to make it pay less attention"),
"enable_batch_seeds": OptionInfo(True, "Make K-diffusion samplers produce same images in a batch as when making a single image"),
"comma_padding_backtrack": OptionInfo(20, "Prompt word wrap length limit", gr.Slider, {"minimum": 0, "maximum": 74, "step": 1}).info("in tokens - for texts shorter than specified, if they don't fit into 75 token limit, move them to the next 75 token chunk"),
- "CLIP_stop_at_last_layers": OptionInfo(1, "Clip skip", gr.Slider, {"minimum": 1, "maximum": 12, "step": 1}).link("wiki", "https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Features#clip-skip").info("ignore last layers of CLIP nrtwork; 1 ignores none, 2 ignores one layer"),
+ "CLIP_stop_at_last_layers": OptionInfo(1, "Clip skip", gr.Slider, {"minimum": 1, "maximum": 12, "step": 1}).link("wiki", "https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Features#clip-skip").info("ignore last layers of CLIP network; 1 ignores none, 2 ignores one layer"),
"upcast_attn": OptionInfo(False, "Upcast cross attention layer to float32"),
"randn_source": OptionInfo("GPU", "Random number generator source.", gr.Radio, {"choices": ["GPU", "CPU"]}).info("changes seeds drastically; use CPU to produce the same picture across different videocard vendors"),
}))
@@ -421,6 +422,7 @@ options_templates.update(options_section(('optimizations', "Optimizations"), {
"token_merging_ratio_img2img": OptionInfo(0.0, "Token merging ratio for img2img", gr.Slider, {"minimum": 0.0, "maximum": 0.9, "step": 0.1}).info("only applies if non-zero and overrides above"),
"token_merging_ratio_hr": OptionInfo(0.0, "Token merging ratio for high-res pass", gr.Slider, {"minimum": 0.0, "maximum": 0.9, "step": 0.1}).info("only applies if non-zero and overrides above"),
"pad_cond_uncond": OptionInfo(False, "Pad prompt/negative prompt to be same length").info("improves performance when prompt and negative prompt have different lengths; changes seeds"),
+ "experimental_persistent_cond_cache": OptionInfo(False, "persistent cond cache").info("Experimental, keep cond caches across jobs, reduce overhead."),
}))
options_templates.update(options_section(('compatibility', "Compatibility"), {
@@ -492,6 +494,7 @@ options_templates.update(options_section(('ui', "User interface"), {
options_templates.update(options_section(('infotext', "Infotext"), {
"add_model_hash_to_info": OptionInfo(True, "Add model hash to generation information"),
"add_model_name_to_info": OptionInfo(True, "Add model name to generation information"),
+ "add_user_name_to_info": OptionInfo(False, "Add user name to generation information when authenticated"),
"add_version_to_infotext": OptionInfo(True, "Add program version to generation information"),
"disable_weights_auto_swap": OptionInfo(True, "Disregard checkpoint information from pasted infotext").info("when reading generation parameters from text into UI"),
"infotext_styles": OptionInfo("Apply if any", "Infer styles from prompts of pasted infotext", gr.Radio, {"choices": ["Ignore", "Apply", "Discard", "Apply if any"]}).info("when reading generation parameters from text into UI)").html("""<ul style='margin-left: 1.5em'>
diff --git a/modules/textual_inversion/autocrop.py b/modules/textual_inversion/autocrop.py
index 75705459..1675e39a 100644
--- a/modules/textual_inversion/autocrop.py
+++ b/modules/textual_inversion/autocrop.py
@@ -298,8 +298,7 @@ def download_and_cache_models(dirname):
download_url = 'https://github.com/opencv/opencv_zoo/blob/91fb0290f50896f38a0ab1e558b74b16bc009428/models/face_detection_yunet/face_detection_yunet_2022mar.onnx?raw=true'
model_file_name = 'face_detection_yunet.onnx'
- if not os.path.exists(dirname):
- os.makedirs(dirname)
+ os.makedirs(dirname, exist_ok=True)
cache_file = os.path.join(dirname, model_file_name)
if not os.path.exists(cache_file):
diff --git a/modules/textual_inversion/logging.py b/modules/textual_inversion/logging.py
index 734a4b6f..45823eb1 100644
--- a/modules/textual_inversion/logging.py
+++ b/modules/textual_inversion/logging.py
@@ -2,11 +2,51 @@ import datetime
import json
import os
-saved_params_shared = {"model_name", "model_hash", "initial_step", "num_of_dataset_images", "learn_rate", "batch_size", "clip_grad_mode", "clip_grad_value", "gradient_step", "data_root", "log_directory", "training_width", "training_height", "steps", "create_image_every", "template_file", "gradient_step", "latent_sampling_method"}
-saved_params_ti = {"embedding_name", "num_vectors_per_token", "save_embedding_every", "save_image_with_stored_embedding"}
-saved_params_hypernet = {"hypernetwork_name", "layer_structure", "activation_func", "weight_init", "add_layer_norm", "use_dropout", "save_hypernetwork_every"}
+saved_params_shared = {
+ "batch_size",
+ "clip_grad_mode",
+ "clip_grad_value",
+ "create_image_every",
+ "data_root",
+ "gradient_step",
+ "initial_step",
+ "latent_sampling_method",
+ "learn_rate",
+ "log_directory",
+ "model_hash",
+ "model_name",
+ "num_of_dataset_images",
+ "steps",
+ "template_file",
+ "training_height",
+ "training_width",
+}
+saved_params_ti = {
+ "embedding_name",
+ "num_vectors_per_token",
+ "save_embedding_every",
+ "save_image_with_stored_embedding",
+}
+saved_params_hypernet = {
+ "activation_func",
+ "add_layer_norm",
+ "hypernetwork_name",
+ "layer_structure",
+ "save_hypernetwork_every",
+ "use_dropout",
+ "weight_init",
+}
saved_params_all = saved_params_shared | saved_params_ti | saved_params_hypernet
-saved_params_previews = {"preview_prompt", "preview_negative_prompt", "preview_steps", "preview_sampler_index", "preview_cfg_scale", "preview_seed", "preview_width", "preview_height"}
+saved_params_previews = {
+ "preview_cfg_scale",
+ "preview_height",
+ "preview_negative_prompt",
+ "preview_prompt",
+ "preview_sampler_index",
+ "preview_seed",
+ "preview_steps",
+ "preview_width",
+}
def save_settings_to_file(log_directory, all_params):
diff --git a/modules/txt2img.py b/modules/txt2img.py
index 2e7d202d..6aa79f23 100644
--- a/modules/txt2img.py
+++ b/modules/txt2img.py
@@ -4,10 +4,10 @@ from modules.generation_parameters_copypaste import create_override_settings_dic
from modules.shared import opts, cmd_opts
import modules.shared as shared
from modules.ui import plaintext_to_html
+import gradio as gr
-
-def txt2img(id_task: str, prompt: str, negative_prompt: str, prompt_styles, steps: int, sampler_index: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: 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, enable_hr: bool, denoising_strength: float, hr_scale: float, hr_upscaler: str, hr_second_pass_steps: int, hr_resize_x: int, hr_resize_y: int, hr_sampler_index: int, hr_prompt: str, hr_negative_prompt, override_settings_texts, *args):
+def txt2img(id_task: str, prompt: str, negative_prompt: str, prompt_styles, steps: int, sampler_index: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: 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, enable_hr: bool, denoising_strength: float, hr_scale: float, hr_upscaler: str, hr_second_pass_steps: int, hr_resize_x: int, hr_resize_y: int, hr_sampler_index: int, hr_prompt: str, hr_negative_prompt, override_settings_texts, request: gr.Request, *args):
override_settings = create_override_settings_dict(override_settings_texts)
p = processing.StableDiffusionProcessingTxt2Img(
@@ -48,6 +48,8 @@ def txt2img(id_task: str, prompt: str, negative_prompt: str, prompt_styles, step
p.scripts = modules.scripts.scripts_txt2img
p.script_args = args
+ p.user = request.username
+
if cmd_opts.enable_console_prompts:
print(f"\ntxt2img: {prompt}", file=shared.progress_print_out)
diff --git a/modules/ui.py b/modules/ui.py
index 3315cc17..e3c8e43a 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -773,7 +773,7 @@ def create_ui():
selected_scale_tab = gr.State(value=0)
with gr.Tabs():
- with gr.Tab(label="Resize to") as tab_scale_to:
+ with gr.Tab(label="Resize to", elem_id="img2img_tab_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")
@@ -782,7 +782,7 @@ def create_ui():
res_switch_btn = ToolButton(value=switch_values_symbol, elem_id="img2img_res_switch_btn")
detect_image_size_btn = ToolButton(value=detect_image_size_symbol, elem_id="img2img_detect_image_size_btn")
- with gr.Tab(label="Resize by") as tab_scale_by:
+ with gr.Tab(label="Resize by", elem_id="img2img_tab_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():
@@ -1501,7 +1501,7 @@ def create_ui():
gr.Audio(interactive=False, value=os.path.join(script_path, "notification.mp3"), elem_id="audio_notification", visible=False)
footer = shared.html("footer.html")
- footer = footer.format(versions=versions_html())
+ footer = footer.format(versions=versions_html(), api_docs="/docs" if shared.cmd_opts.api else "https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/API")
gr.HTML(footer, elem_id="footer")
settings.add_functionality(demo)
diff --git a/modules/ui_extensions.py b/modules/ui_extensions.py
index 4379a641..278bf5e4 100644
--- a/modules/ui_extensions.py
+++ b/modules/ui_extensions.py
@@ -138,7 +138,10 @@ def extension_table():
<table id="extensions">
<thead>
<tr>
- <th><abbr title="Use checkbox to enable the extension; it will be enabled or disabled when you click apply button">Extension</abbr></th>
+ <th>
+ <input class="gr-check-radio gr-checkbox all_extensions_toggle" type="checkbox" {'checked="checked"' if all(ext.enabled for ext in extensions.extensions) else ''} onchange="toggle_all_extensions(event)" />
+ <abbr title="Use checkbox to enable the extension; it will be enabled or disabled when you click apply button">Extension</abbr>
+ </th>
<th>URL</th>
<th>Branch</th>
<th>Version</th>
@@ -170,7 +173,7 @@ def extension_table():
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><label{style}><input class="gr-check-radio gr-checkbox extension_toggle" name="enable_{html.escape(ext.name)}" type="checkbox" {'checked="checked"' if ext.enabled else ''} onchange="toggle_extension(event)" />{html.escape(ext.name)}</label></td>
<td>{remote}</td>
<td>{ext.branch}</td>
<td>{version_link}</td>
@@ -325,6 +328,11 @@ def normalize_git_url(url):
def install_extension_from_url(dirname, url, branch_name=None):
check_access()
+ if isinstance(dirname, str):
+ dirname = dirname.strip()
+ if isinstance(url, str):
+ url = url.strip()
+
assert url, 'No URL specified'
if dirname is None or dirname == "":
@@ -563,9 +571,9 @@ def create_ui():
available_extensions_table = gr.HTML()
refresh_available_extensions_button.click(
- fn=modules.ui.wrap_gradio_call(refresh_available_extensions, extra_outputs=[gr.update(), gr.update(), gr.update()]),
+ fn=modules.ui.wrap_gradio_call(refresh_available_extensions, extra_outputs=[gr.update(), gr.update(), gr.update(), gr.update()]),
inputs=[available_extensions_index, hide_tags, sort_column],
- outputs=[available_extensions_index, available_extensions_table, hide_tags, install_result, search_extensions_text],
+ outputs=[available_extensions_index, available_extensions_table, hide_tags, search_extensions_text, install_result],
)
install_extension_button.click(
generated by cgit v1.2.1 (git 2.18.0) at 2025-05-21 10:44:31 +0000