Skip to content

S
Stable Diffusion Webui
Commit 73d95645 authored by AUTOMATIC1111's avatar AUTOMATIC1111 Committed by GitHub
Browse files
Options

Merge branch 'dev' into tooltip

parents 57a3d146 b15bbef7
Expand all Hide whitespace changes
Inline Side-by-side
Showing with 1884 additions and 529 deletions
.gitignore
View file @ 73d95645
...@@ -32,4 +32,5 @@ notification.mp3 ...@@ -32,4 +32,5 @@ notification.mp3
/extensions /extensions
/test/stdout.txt /test/stdout.txt
/test/stderr.txt /test/stderr.txt
/cache.json /cache.json*
/config_states/
CHANGELOG.md 0 → 100644
View file @ 73d95645
## 1.1.1
### Bug Fixes:
* fix an error that prevents running webui on torch<2.0 without --disable-safe-unpickle
## 1.1.0
### Features:
* switch to torch 2.0.0 (except for AMD GPUs)
* visual improvements to custom code scripts
* add filename patterns: [clip_skip], [hasprompt<>], [batch_number], [generation_number]
* add support for saving init images in img2img, and record their hashes in infotext for reproducability
* automatically select current word when adjusting weight with ctrl+up/down
* add dropdowns for X/Y/Z plot
* setting: Stable Diffusion/Random number generator source: makes it possible to make images generated from a given manual seed consistent across different GPUs
* support Gradio's theme API
* use TCMalloc on Linux by default; possible fix for memory leaks
* (optimization) option to remove negative conditioning at low sigma values #9177
* embed model merge metadata in .safetensors file
* extension settings backup/restore feature #9169
* add "resize by" and "resize to" tabs to img2img
* add option "keep original size" to textual inversion images preprocess
* image viewer scrolling via analog stick
* button to restore the progress from session lost / tab reload
### Minor:
* gradio bumped to 3.28.1
* in extra tab, change extras "scale to" to sliders
* add labels to tool buttons to make it possible to hide them
* add tiled inference support for ScuNET
* add branch support for extension installation
* change linux installation script to insall into current directory rather than /home/username
* sort textual inversion embeddings by name (case insensitive)
* allow styles.csv to be symlinked or mounted in docker
* remove the "do not add watermark to images" option
* make selected tab configurable with UI config
* extra networks UI in now fixed height and scrollable
* add disable_tls_verify arg for use with self-signed certs
### Extensions:
* Add reload callback
* add is_hr_pass field for processing
### Bug Fixes:
* fix broken batch image processing on 'Extras/Batch Process' tab
* add "None" option to extra networks dropdowns
* fix FileExistsError for CLIP Interrogator
* fix /sdapi/v1/txt2img endpoint not working on Linux #9319
* fix disappearing live previews and progressbar during slow tasks
* fix fullscreen image view not working properly in some cases
* prevent alwayson_scripts args param resizing script_arg list when they are inserted in it
* fix prompt schedule for second order samplers
* fix image mask/composite for weird resolutions #9628
* use correct images for previews when using AND (see #9491)
* one broken image in img2img batch won't stop all processing
* fix image orientation bug in train/preprocess
* fix Ngrok recreating tunnels every reload
* fix --realesrgan-models-path and --ldsr-models-path not working
* fix --skip-install not working
* outpainting Mk2 & Poorman should use the SAMPLE file format to save images, not GRID file format
* do not fail all Loras if some have failed to load when making a picture
## 1.0.0
* everything
README.md
View file @ 73d95645
...@@ -100,7 +100,7 @@ Alternatively, use online services (like Google Colab): ...@@ -100,7 +100,7 @@ Alternatively, use online services (like Google Colab):
- [List of Online Services](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Online-Services) - [List of Online Services](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Online-Services)
### Automatic Installation on Windows ### Automatic Installation on Windows
1. Install [Python 3.10.6](https://www.python.org/downloads/windows/), checking "Add Python to PATH". 1. Install [Python 3.10.6](https://www.python.org/downloads/release/python-3106/) (Newer version of Python does not support torch), checking "Add Python to PATH".
2. Install [git](https://git-scm.com/download/win). 2. Install [git](https://git-scm.com/download/win).
3. Download the stable-diffusion-webui repository, for example by running `git clone https://github.com/AUTOMATIC1111/stable-diffusion-webui.git`. 3. Download the stable-diffusion-webui repository, for example by running `git clone https://github.com/AUTOMATIC1111/stable-diffusion-webui.git`.
4. Run `webui-user.bat` from Windows Explorer as normal, non-administrator, user. 4. Run `webui-user.bat` from Windows Explorer as normal, non-administrator, user.
...@@ -115,11 +115,12 @@ sudo dnf install wget git python3 ...@@ -115,11 +115,12 @@ sudo dnf install wget git python3
# Arch-based: # Arch-based:
sudo pacman -S wget git python3 sudo pacman -S wget git python3
``` ```
2. To install in `/home/$(whoami)/stable-diffusion-webui/`, run: 2. Navigate to the directory you would like the webui to be installed and execute the following command:
```bash ```bash
bash <(wget -qO- https://raw.githubusercontent.com/AUTOMATIC1111/stable-diffusion-webui/master/webui.sh) bash <(wget -qO- https://raw.githubusercontent.com/AUTOMATIC1111/stable-diffusion-webui/master/webui.sh)
``` ```
3. Run `webui.sh`. 3. Run `webui.sh`.
4. Check `webui-user.sh` for options.
### Installation on Apple Silicon ### Installation on Apple Silicon
Find the instructions [here](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Installation-on-Apple-Silicon). Find the instructions [here](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Installation-on-Apple-Silicon).
...@@ -158,4 +159,4 @@ Licenses for borrowed code can be found in `Settings -> Licenses` screen, and al ...@@ -158,4 +159,4 @@ Licenses for borrowed code can be found in `Settings -> Licenses` screen, and al
- Security advice - RyotaK - Security advice - RyotaK
- UniPC sampler - Wenliang Zhao - https://github.com/wl-zhao/UniPC - UniPC sampler - Wenliang Zhao - https://github.com/wl-zhao/UniPC
- Initial Gradio script - posted on 4chan by an Anonymous user. Thank you Anonymous user. - Initial Gradio script - posted on 4chan by an Anonymous user. Thank you Anonymous user.
- (You) - (You)
\ No newline at end of file
environment-wsl2.yaml
View file @ 73d95645
...@@ -4,8 +4,8 @@ channels: ...@@ -4,8 +4,8 @@ channels:
- defaults - defaults
dependencies: dependencies:
- python=3.10 - python=3.10
- pip=22.2.2 - pip=23.0
- cudatoolkit=11.3 - cudatoolkit=11.8
- pytorch=1.12.1 - pytorch=2.0
- torchvision=0.13.1 - torchvision=0.15
- numpy=1.23.1 - numpy=1.23
\ No newline at end of file
extensions-builtin/LDSR/scripts/ldsr_model.py
View file @ 73d95645
...@@ -25,22 +25,28 @@ class UpscalerLDSR(Upscaler): ...@@ -25,22 +25,28 @@ class UpscalerLDSR(Upscaler):
yaml_path = os.path.join(self.model_path, "project.yaml") yaml_path = os.path.join(self.model_path, "project.yaml")
old_model_path = os.path.join(self.model_path, "model.pth") old_model_path = os.path.join(self.model_path, "model.pth")
new_model_path = os.path.join(self.model_path, "model.ckpt") new_model_path = os.path.join(self.model_path, "model.ckpt")
safetensors_model_path = os.path.join(self.model_path, "model.safetensors")
local_model_paths = self.find_models(ext_filter=[".ckpt", ".safetensors"])
local_ckpt_path = next(iter([local_model for local_model in local_model_paths if local_model.endswith("model.ckpt")]), None)
local_safetensors_path = next(iter([local_model for local_model in local_model_paths if local_model.endswith("model.safetensors")]), None)
local_yaml_path = next(iter([local_model for local_model in local_model_paths if local_model.endswith("project.yaml")]), None)
if os.path.exists(yaml_path): if os.path.exists(yaml_path):
statinfo = os.stat(yaml_path) statinfo = os.stat(yaml_path)
if statinfo.st_size >= 10485760: if statinfo.st_size >= 10485760:
print("Removing invalid LDSR YAML file.") print("Removing invalid LDSR YAML file.")
os.remove(yaml_path) os.remove(yaml_path)
if os.path.exists(old_model_path): if os.path.exists(old_model_path):
print("Renaming model from model.pth to model.ckpt") print("Renaming model from model.pth to model.ckpt")
os.rename(old_model_path, new_model_path) os.rename(old_model_path, new_model_path)
if os.path.exists(safetensors_model_path):
model = safetensors_model_path if local_safetensors_path is not None and os.path.exists(local_safetensors_path):
model = local_safetensors_path
else: else:
model = load_file_from_url(url=self.model_url, model_dir=self.model_path, model = local_ckpt_path if local_ckpt_path is not None else load_file_from_url(url=self.model_url, model_dir=self.model_path, file_name="model.ckpt", progress=True)
file_name="model.ckpt", progress=True)
yaml = load_file_from_url(url=self.yaml_url, model_dir=self.model_path, yaml = local_yaml_path if local_yaml_path is not None else load_file_from_url(url=self.yaml_url, model_dir=self.model_path, file_name="project.yaml", progress=True)
file_name="project.yaml", progress=True)
try: try:
return LDSR(model, yaml) return LDSR(model, yaml)
......
extensions-builtin/Lora/extra_networks_lora.py
View file @ 73d95645
from modules import extra_networks, shared from modules import extra_networks, shared
import lora import lora
class ExtraNetworkLora(extra_networks.ExtraNetwork): class ExtraNetworkLora(extra_networks.ExtraNetwork):
def __init__(self): def __init__(self):
super().__init__('lora') super().__init__('lora')
...@@ -8,7 +9,7 @@ class ExtraNetworkLora(extra_networks.ExtraNetwork): ...@@ -8,7 +9,7 @@ class ExtraNetworkLora(extra_networks.ExtraNetwork):
def activate(self, p, params_list): def activate(self, p, params_list):
additional = shared.opts.sd_lora additional = shared.opts.sd_lora
if additional != "" and additional in lora.available_loras and len([x for x in params_list if x.items[0] == additional]) == 0: if additional != "None" and additional in lora.available_loras and len([x for x in params_list if x.items[0] == additional]) == 0:
p.all_prompts = [x + f"<lora:{additional}:{shared.opts.extra_networks_default_multiplier}>" for x in p.all_prompts] p.all_prompts = [x + f"<lora:{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])) params_list.append(extra_networks.ExtraNetworkParams(items=[additional, shared.opts.extra_networks_default_multiplier]))
......
extensions-builtin/Lora/lora.py
View file @ 73d95645
...@@ -4,7 +4,7 @@ import re ...@@ -4,7 +4,7 @@ import re
import torch import torch
from typing import Union from typing import Union
from modules import shared, devices, sd_models, errors from modules import shared, devices, sd_models, errors, scripts
metadata_tags_order = {"ss_sd_model_name": 1, "ss_resolution": 2, "ss_clip_skip": 3, "ss_num_train_images": 10, "ss_tag_frequency": 20} metadata_tags_order = {"ss_sd_model_name": 1, "ss_resolution": 2, "ss_clip_skip": 3, "ss_num_train_images": 10, "ss_tag_frequency": 20}
...@@ -93,6 +93,7 @@ class LoraOnDisk: ...@@ -93,6 +93,7 @@ class LoraOnDisk:
self.metadata = m self.metadata = m
self.ssmd_cover_images = self.metadata.pop('ssmd_cover_images', None) # those are cover images and they are too big to display in UI as text self.ssmd_cover_images = self.metadata.pop('ssmd_cover_images', None) # those are cover images and they are too big to display in UI as text
self.alias = self.metadata.get('ss_output_name', self.name)
class LoraModule: class LoraModule:
...@@ -165,8 +166,10 @@ def load_lora(name, filename): ...@@ -165,8 +166,10 @@ def load_lora(name, filename):
module = torch.nn.Linear(weight.shape[1], weight.shape[0], bias=False) module = torch.nn.Linear(weight.shape[1], weight.shape[0], bias=False)
elif type(sd_module) == torch.nn.MultiheadAttention: elif type(sd_module) == torch.nn.MultiheadAttention:
module = torch.nn.Linear(weight.shape[1], weight.shape[0], bias=False) module = torch.nn.Linear(weight.shape[1], weight.shape[0], bias=False)
elif type(sd_module) == torch.nn.Conv2d: elif type(sd_module) == torch.nn.Conv2d and weight.shape[2:] == (1, 1):
module = torch.nn.Conv2d(weight.shape[1], weight.shape[0], (1, 1), bias=False) module = torch.nn.Conv2d(weight.shape[1], weight.shape[0], (1, 1), bias=False)
elif type(sd_module) == torch.nn.Conv2d and weight.shape[2:] == (3, 3):
module = torch.nn.Conv2d(weight.shape[1], weight.shape[0], (3, 3), bias=False)
else: else:
print(f'Lora layer {key_diffusers} matched a layer with unsupported type: {type(sd_module).__name__}') print(f'Lora layer {key_diffusers} matched a layer with unsupported type: {type(sd_module).__name__}')
continue continue
...@@ -199,11 +202,11 @@ def load_loras(names, multipliers=None): ...@@ -199,11 +202,11 @@ def load_loras(names, multipliers=None):
loaded_loras.clear() loaded_loras.clear()
loras_on_disk = [available_loras.get(name, None) for name in names] loras_on_disk = [available_lora_aliases.get(name, None) for name in names]
if any([x is None for x in loras_on_disk]): if any([x is None for x in loras_on_disk]):
list_available_loras() list_available_loras()
loras_on_disk = [available_loras.get(name, None) for name in names] loras_on_disk = [available_lora_aliases.get(name, None) for name in names]
for i, name in enumerate(names): for i, name in enumerate(names):
lora = already_loaded.get(name, None) lora = already_loaded.get(name, None)
...@@ -211,7 +214,11 @@ def load_loras(names, multipliers=None): ...@@ -211,7 +214,11 @@ def load_loras(names, multipliers=None):
lora_on_disk = loras_on_disk[i] lora_on_disk = loras_on_disk[i]
if lora_on_disk is not None: if lora_on_disk is not None:
if lora is None or os.path.getmtime(lora_on_disk.filename) > lora.mtime: if lora is None or os.path.getmtime(lora_on_disk.filename) > lora.mtime:
lora = load_lora(name, lora_on_disk.filename) try:
lora = load_lora(name, lora_on_disk.filename)
except Exception as e:
errors.display(e, f"loading Lora {lora_on_disk.filename}")
continue
if lora is None: if lora is None:
print(f"Couldn't find Lora with name {name}") print(f"Couldn't find Lora with name {name}")
...@@ -228,6 +235,8 @@ def lora_calc_updown(lora, module, target): ...@@ -228,6 +235,8 @@ def lora_calc_updown(lora, module, target):
if up.shape[2:] == (1, 1) and down.shape[2:] == (1, 1): if up.shape[2:] == (1, 1) and down.shape[2:] == (1, 1):
updown = (up.squeeze(2).squeeze(2) @ down.squeeze(2).squeeze(2)).unsqueeze(2).unsqueeze(3) updown = (up.squeeze(2).squeeze(2) @ down.squeeze(2).squeeze(2)).unsqueeze(2).unsqueeze(3)
elif up.shape[2:] == (3, 3) or down.shape[2:] == (3, 3):
updown = torch.nn.functional.conv2d(down.permute(1, 0, 2, 3), up).permute(1, 0, 2, 3)
else: else:
updown = up @ down updown = up @ down
...@@ -339,6 +348,7 @@ def lora_MultiheadAttention_load_state_dict(self, *args, **kwargs): ...@@ -339,6 +348,7 @@ def lora_MultiheadAttention_load_state_dict(self, *args, **kwargs):
def list_available_loras(): def list_available_loras():
available_loras.clear() available_loras.clear()
available_lora_aliases.clear()
os.makedirs(shared.cmd_opts.lora_dir, exist_ok=True) os.makedirs(shared.cmd_opts.lora_dir, exist_ok=True)
...@@ -352,11 +362,50 @@ def list_available_loras(): ...@@ -352,11 +362,50 @@ def list_available_loras():
continue continue
name = os.path.splitext(os.path.basename(filename))[0] name = os.path.splitext(os.path.basename(filename))[0]
entry = LoraOnDisk(name, filename)
available_loras[name] = LoraOnDisk(name, filename) available_loras[name] = entry
available_lora_aliases[name] = entry
available_lora_aliases[entry.alias] = entry
re_lora_name = re.compile(r"(.*)\s*\([0-9a-fA-F]+\)")
def infotext_pasted(infotext, params):
if "AddNet Module 1" in [x[1] for x in scripts.scripts_txt2img.infotext_fields]:
return # if the other extension is active, it will handle those fields, no need to do anything
added = []
for k, v in params.items():
if not k.startswith("AddNet Model "):
continue
num = k[13:]
if params.get("AddNet Module " + num) != "LoRA":
continue
name = params.get("AddNet Model " + num)
if name is None:
continue
m = re_lora_name.match(name)
if m:
name = m.group(1)
multiplier = params.get("AddNet Weight A " + num, "1.0")
added.append(f"<lora:{name}:{multiplier}>")
if added:
params["Prompt"] += "\n" + "".join(added)
available_loras = {} available_loras = {}
available_lora_aliases = {}
loaded_loras = [] loaded_loras = []
list_available_loras() list_available_loras()
extensions-builtin/Lora/scripts/lora_script.py
View file @ 73d95645
...@@ -49,8 +49,9 @@ torch.nn.MultiheadAttention._load_from_state_dict = lora.lora_MultiheadAttention ...@@ -49,8 +49,9 @@ torch.nn.MultiheadAttention._load_from_state_dict = lora.lora_MultiheadAttention
script_callbacks.on_model_loaded(lora.assign_lora_names_to_compvis_modules) script_callbacks.on_model_loaded(lora.assign_lora_names_to_compvis_modules)
script_callbacks.on_script_unloaded(unload) script_callbacks.on_script_unloaded(unload)
script_callbacks.on_before_ui(before_ui) script_callbacks.on_before_ui(before_ui)
script_callbacks.on_infotext_pasted(lora.infotext_pasted)
shared.options_templates.update(shared.options_section(('extra_networks', "Extra Networks"), { shared.options_templates.update(shared.options_section(('extra_networks', "Extra Networks"), {
"sd_lora": shared.OptionInfo("None", "Add Lora to prompt", gr.Dropdown, lambda: {"choices": [""] + [x for x in lora.available_loras]}, refresh=lora.list_available_loras), "sd_lora": shared.OptionInfo("None", "Add Lora to prompt", gr.Dropdown, lambda: {"choices": ["None"] + [x for x in lora.available_loras]}, refresh=lora.list_available_loras),
})) }))
extensions-builtin/Lora/ui_extra_networks_lora.py
View file @ 73d95645
...@@ -21,7 +21,7 @@ class ExtraNetworksPageLora(ui_extra_networks.ExtraNetworksPage): ...@@ -21,7 +21,7 @@ class ExtraNetworksPageLora(ui_extra_networks.ExtraNetworksPage):
"preview": self.find_preview(path), "preview": self.find_preview(path),
"description": self.find_description(path), "description": self.find_description(path),
"search_term": self.search_terms_from_path(lora_on_disk.filename), "search_term": self.search_terms_from_path(lora_on_disk.filename),
"prompt": json.dumps(f"<lora:{name}:") + " + opts.extra_networks_default_multiplier + " + json.dumps(">"), "prompt": json.dumps(f"<lora:{lora_on_disk.alias}:") + " + opts.extra_networks_default_multiplier + " + json.dumps(">"),
"local_preview": f"{path}.{shared.opts.samples_format}", "local_preview": f"{path}.{shared.opts.samples_format}",
"metadata": json.dumps(lora_on_disk.metadata, indent=4) if lora_on_disk.metadata else None, "metadata": json.dumps(lora_on_disk.metadata, indent=4) if lora_on_disk.metadata else None,
} }
......
extensions-builtin/ScuNET/scripts/scunet_model.py
View file @ 73d95645
...@@ -5,11 +5,15 @@ import traceback ...@@ -5,11 +5,15 @@ import traceback
import PIL.Image import PIL.Image
import numpy as np import numpy as np
import torch import torch
from tqdm import tqdm
from basicsr.utils.download_util import load_file_from_url from basicsr.utils.download_util import load_file_from_url
import modules.upscaler import modules.upscaler
from modules import devices, modelloader from modules import devices, modelloader
from scunet_model_arch import SCUNet as net from scunet_model_arch import SCUNet as net
from modules.shared import opts
from modules import images
class UpscalerScuNET(modules.upscaler.Upscaler): class UpscalerScuNET(modules.upscaler.Upscaler):
...@@ -42,28 +46,78 @@ class UpscalerScuNET(modules.upscaler.Upscaler): ...@@ -42,28 +46,78 @@ class UpscalerScuNET(modules.upscaler.Upscaler):
scalers.append(scaler_data2) scalers.append(scaler_data2)
self.scalers = scalers self.scalers = scalers
def do_upscale(self, img: PIL.Image, selected_file): @staticmethod
@torch.no_grad()
def tiled_inference(img, model):
# test the image tile by tile
h, w = img.shape[2:]
tile = opts.SCUNET_tile
tile_overlap = opts.SCUNET_tile_overlap
if tile == 0:
return model(img)
device = devices.get_device_for('scunet')
assert tile % 8 == 0, "tile size should be a multiple of window_size"
sf = 1
stride = tile - tile_overlap
h_idx_list = list(range(0, h - tile, stride)) + [h - tile]
w_idx_list = list(range(0, w - tile, stride)) + [w - tile]
E = torch.zeros(1, 3, h * sf, w * sf, dtype=img.dtype, device=device)
W = torch.zeros_like(E, dtype=devices.dtype, device=device)
with tqdm(total=len(h_idx_list) * len(w_idx_list), desc="ScuNET tiles") as pbar:
for h_idx in h_idx_list:
for w_idx in w_idx_list:
in_patch = img[..., h_idx: h_idx + tile, w_idx: w_idx + tile]
out_patch = model(in_patch)
out_patch_mask = torch.ones_like(out_patch)
E[
..., h_idx * sf: (h_idx + tile) * sf, w_idx * sf: (w_idx + tile) * sf
].add_(out_patch)
W[
..., h_idx * sf: (h_idx + tile) * sf, w_idx * sf: (w_idx + tile) * sf
].add_(out_patch_mask)
pbar.update(1)
output = E.div_(W)
return output
def do_upscale(self, img: PIL.Image.Image, selected_file):
torch.cuda.empty_cache() torch.cuda.empty_cache()
model = self.load_model(selected_file) model = self.load_model(selected_file)
if model is None: if model is None:
print(f"ScuNET: Unable to load model from {selected_file}", file=sys.stderr)
return img return img
device = devices.get_device_for('scunet') device = devices.get_device_for('scunet')
img = np.array(img) tile = opts.SCUNET_tile
img = img[:, :, ::-1] h, w = img.height, img.width
img = np.moveaxis(img, 2, 0) / 255 np_img = np.array(img)
img = torch.from_numpy(img).float() np_img = np_img[:, :, ::-1] # RGB to BGR
img = img.unsqueeze(0).to(device) np_img = np_img.transpose((2, 0, 1)) / 255 # HWC to CHW
torch_img = torch.from_numpy(np_img).float().unsqueeze(0).to(device) # type: ignore
with torch.no_grad():
output = model(img) if tile > h or tile > w:
output = output.squeeze().float().cpu().clamp_(0, 1).numpy() _img = torch.zeros(1, 3, max(h, tile), max(w, tile), dtype=torch_img.dtype, device=torch_img.device)
output = 255. * np.moveaxis(output, 0, 2) _img[:, :, :h, :w] = torch_img # pad image
output = output.astype(np.uint8) torch_img = _img
output = output[:, :, ::-1]
torch_output = self.tiled_inference(torch_img, model).squeeze(0)
torch_output = torch_output[:, :h * 1, :w * 1] # remove padding, if any
np_output: np.ndarray = torch_output.float().cpu().clamp_(0, 1).numpy()
del torch_img, torch_output
torch.cuda.empty_cache() torch.cuda.empty_cache()
return PIL.Image.fromarray(output, 'RGB')
output = np_output.transpose((1, 2, 0)) # CHW to HWC
output = output[:, :, ::-1] # BGR to RGB
return PIL.Image.fromarray((output * 255).astype(np.uint8))
def load_model(self, path: str): def load_model(self, path: str):
device = devices.get_device_for('scunet') device = devices.get_device_for('scunet')
...@@ -84,4 +138,3 @@ class UpscalerScuNET(modules.upscaler.Upscaler): ...@@ -84,4 +138,3 @@ class UpscalerScuNET(modules.upscaler.Upscaler):
model = model.to(device) model = model.to(device)
return model return model
extensions-builtin/prompt-bracket-checker/javascript/prompt-bracket-checker.js
View file @ 73d95645
// Stable Diffusion WebUI - Bracket checker // Stable Diffusion WebUI - Bracket checker
// Version 1.0 // By Hingashi no Florin/Bwin4L & @akx
// By Hingashi no Florin/Bwin4L
// Counts open and closed brackets (round, square, curly) in the prompt and negative prompt text boxes in the txt2img and img2img tabs. // Counts open and closed brackets (round, square, curly) in the prompt and negative prompt text boxes in the txt2img and img2img tabs.
// If there's a mismatch, the keyword counter turns red and if you hover on it, a tooltip tells you what's wrong. // If there's a mismatch, the keyword counter turns red and if you hover on it, a tooltip tells you what's wrong.
function checkBrackets(evt, textArea, counterElt) { function checkBrackets(textArea, counterElt) {
errorStringParen = '(...) - Different number of opening and closing parentheses detected.\n'; var counts = {};
errorStringSquare = '[...] - Different number of opening and closing square brackets detected.\n'; (textArea.value.match(/[(){}\[\]]/g) || []).forEach(bracket => {
errorStringCurly = '{...} - Different number of opening and closing curly brackets detected.\n'; counts[bracket] = (counts[bracket] || 0) + 1;
});
openBracketRegExp = /\(/g; var errors = [];
closeBracketRegExp = /\)/g;
function checkPair(open, close, kind) {
openSquareBracketRegExp = /\[/g; if (counts[open] !== counts[close]) {
closeSquareBracketRegExp = /\]/g; errors.push(
`${open}...${close} - Detected ${counts[open] || 0} opening and ${counts[close] || 0} closing ${kind}.`
openCurlyBracketRegExp = /\{/g; );
closeCurlyBracketRegExp = /\}/g;
totalOpenBracketMatches = 0;
totalCloseBracketMatches = 0;
totalOpenSquareBracketMatches = 0;
totalCloseSquareBracketMatches = 0;
totalOpenCurlyBracketMatches = 0;
totalCloseCurlyBracketMatches = 0;
openBracketMatches = textArea.value.match(openBracketRegExp);
if(openBracketMatches) {
totalOpenBracketMatches = openBracketMatches.length;
}
closeBracketMatches = textArea.value.match(closeBracketRegExp);
if(closeBracketMatches) {
totalCloseBracketMatches = closeBracketMatches.length;
}
openSquareBracketMatches = textArea.value.match(openSquareBracketRegExp);
if(openSquareBracketMatches) {
totalOpenSquareBracketMatches = openSquareBracketMatches.length;
}
closeSquareBracketMatches = textArea.value.match(closeSquareBracketRegExp);
if(closeSquareBracketMatches) {
totalCloseSquareBracketMatches = closeSquareBracketMatches.length;
}
openCurlyBracketMatches = textArea.value.match(openCurlyBracketRegExp);
if(openCurlyBracketMatches) {
totalOpenCurlyBracketMatches = openCurlyBracketMatches.length;
}
closeCurlyBracketMatches = textArea.value.match(closeCurlyBracketRegExp);
if(closeCurlyBracketMatches) {
totalCloseCurlyBracketMatches = closeCurlyBracketMatches.length;
}
if(totalOpenBracketMatches != totalCloseBracketMatches) {
if(!counterElt.title.includes(errorStringParen)) {
counterElt.title += errorStringParen;
}
} else {
counterElt.title = counterElt.title.replace(errorStringParen, '');
}
if(totalOpenSquareBracketMatches != totalCloseSquareBracketMatches) {
if(!counterElt.title.includes(errorStringSquare)) {
counterElt.title += errorStringSquare;
}
} else {
counterElt.title = counterElt.title.replace(errorStringSquare, '');
}
if(totalOpenCurlyBracketMatches != totalCloseCurlyBracketMatches) {
if(!counterElt.title.includes(errorStringCurly)) {
counterElt.title += errorStringCurly;
} }
} else {
counterElt.title = counterElt.title.replace(errorStringCurly, '');
} }
if(counterElt.title != '') { checkPair('(', ')', 'round brackets');
counterElt.classList.add('error'); checkPair('[', ']', 'square brackets');
} else { checkPair('{', '}', 'curly brackets');
counterElt.classList.remove('error'); counterElt.title = errors.join('\n');
} counterElt.classList.toggle('error', errors.length !== 0);
} }
function setupBracketChecking(id_prompt, id_counter){ function setupBracketChecking(id_prompt, id_counter) {
var textarea = gradioApp().querySelector("#" + id_prompt + " > label > textarea"); var textarea = gradioApp().querySelector("#" + id_prompt + " > label > textarea");
var counter = gradioApp().getElementById(id_counter) var counter = gradioApp().getElementById(id_counter)
textarea.addEventListener("input", function(evt){ if (textarea && counter) {
checkBrackets(evt, textarea, counter) textarea.addEventListener("input", () => checkBrackets(textarea, counter));
}); }
} }
onUiLoaded(function(){ onUiLoaded(function () {
setupBracketChecking('txt2img_prompt', 'txt2img_token_counter') setupBracketChecking('txt2img_prompt', 'txt2img_token_counter');
setupBracketChecking('txt2img_neg_prompt', 'txt2img_negative_token_counter') setupBracketChecking('txt2img_neg_prompt', 'txt2img_negative_token_counter');
setupBracketChecking('img2img_prompt', 'img2img_token_counter') setupBracketChecking('img2img_prompt', 'img2img_token_counter');
setupBracketChecking('img2img_neg_prompt', 'img2img_negative_token_counter') setupBracketChecking('img2img_neg_prompt', 'img2img_negative_token_counter');
}) });
\ No newline at end of file
javascript/aspectRatioOverlay.js
View file @ 73d95645
...@@ -45,29 +45,24 @@ function dimensionChange(e, is_width, is_height){ ...@@ -45,29 +45,24 @@ function dimensionChange(e, is_width, is_height){
var viewportOffset = targetElement.getBoundingClientRect(); var viewportOffset = targetElement.getBoundingClientRect();
viewportscale = Math.min( targetElement.clientWidth/targetElement.naturalWidth, targetElement.clientHeight/targetElement.naturalHeight ) var viewportscale = Math.min( targetElement.clientWidth/targetElement.naturalWidth, targetElement.clientHeight/targetElement.naturalHeight )
scaledx = targetElement.naturalWidth*viewportscale var scaledx = targetElement.naturalWidth*viewportscale
scaledy = targetElement.naturalHeight*viewportscale var scaledy = targetElement.naturalHeight*viewportscale
cleintRectTop = (viewportOffset.top+window.scrollY) var cleintRectTop = (viewportOffset.top+window.scrollY)
cleintRectLeft = (viewportOffset.left+window.scrollX) var cleintRectLeft = (viewportOffset.left+window.scrollX)
cleintRectCentreY = cleintRectTop + (targetElement.clientHeight/2) var cleintRectCentreY = cleintRectTop + (targetElement.clientHeight/2)
cleintRectCentreX = cleintRectLeft + (targetElement.clientWidth/2) var cleintRectCentreX = cleintRectLeft + (targetElement.clientWidth/2)
viewRectTop = cleintRectCentreY-(scaledy/2) var arscale = Math.min( scaledx/currentWidth, scaledy/currentHeight )
viewRectLeft = cleintRectCentreX-(scaledx/2) var arscaledx = currentWidth*arscale
arRectWidth = scaledx var arscaledy = currentHeight*arscale
arRectHeight = scaledy
arscale = Math.min( arRectWidth/currentWidth, arRectHeight/currentHeight ) var arRectTop = cleintRectCentreY-(arscaledy/2)
arscaledx = currentWidth*arscale var arRectLeft = cleintRectCentreX-(arscaledx/2)
arscaledy = currentHeight*arscale var arRectWidth = arscaledx
var arRectHeight = arscaledy
arRectTop = cleintRectCentreY-(arscaledy/2)
arRectLeft = cleintRectCentreX-(arscaledx/2)
arRectWidth = arscaledx
arRectHeight = arscaledy
arPreviewRect.style.top = arRectTop+'px'; arPreviewRect.style.top = arRectTop+'px';
arPreviewRect.style.left = arRectLeft+'px'; arPreviewRect.style.left = arRectLeft+'px';
......
javascript/contextMenus.js
View file @ 73d95645
...@@ -4,7 +4,7 @@ contextMenuInit = function(){ ...@@ -4,7 +4,7 @@ contextMenuInit = function(){
let menuSpecs = new Map(); let menuSpecs = new Map();
const uid = function(){ const uid = function(){
return Date.now().toString(36) + Math.random().toString(36).substr(2); return Date.now().toString(36) + Math.random().toString(36).substring(2);
} }
function showContextMenu(event,element,menuEntries){ function showContextMenu(event,element,menuEntries){
...@@ -16,8 +16,7 @@ contextMenuInit = function(){ ...@@ -16,8 +16,7 @@ contextMenuInit = function(){
oldMenu.remove() oldMenu.remove()
} }
let tabButton = uiCurrentTab let baseStyle = window.getComputedStyle(uiCurrentTab)
let baseStyle = window.getComputedStyle(tabButton)
const contextMenu = document.createElement('nav') const contextMenu = document.createElement('nav')
contextMenu.id = "context-menu" contextMenu.id = "context-menu"
...@@ -36,7 +35,7 @@ contextMenuInit = function(){ ...@@ -36,7 +35,7 @@ contextMenuInit = function(){
menuEntries.forEach(function(entry){ menuEntries.forEach(function(entry){
let contextMenuEntry = document.createElement('a') let contextMenuEntry = document.createElement('a')
contextMenuEntry.innerHTML = entry['name'] contextMenuEntry.innerHTML = entry['name']
contextMenuEntry.addEventListener("click", function(e) { contextMenuEntry.addEventListener("click", function() {
entry['func'](); entry['func']();
}) })
contextMenuList.append(contextMenuEntry); contextMenuList.append(contextMenuEntry);
...@@ -63,7 +62,7 @@ contextMenuInit = function(){ ...@@ -63,7 +62,7 @@ contextMenuInit = function(){
function appendContextMenuOption(targetElementSelector,entryName,entryFunction){ function appendContextMenuOption(targetElementSelector,entryName,entryFunction){
currentItems = menuSpecs.get(targetElementSelector) var currentItems = menuSpecs.get(targetElementSelector)
if(!currentItems){ if(!currentItems){
currentItems = [] currentItems = []
...@@ -79,7 +78,7 @@ contextMenuInit = function(){ ...@@ -79,7 +78,7 @@ contextMenuInit = function(){
} }
function removeContextMenuOption(uid){ function removeContextMenuOption(uid){
menuSpecs.forEach(function(v,k) { menuSpecs.forEach(function(v) {
let index = -1 let index = -1
v.forEach(function(e,ei){if(e['id']==uid){index=ei}}) v.forEach(function(e,ei){if(e['id']==uid){index=ei}})
if(index>=0){ if(index>=0){
...@@ -112,7 +111,6 @@ contextMenuInit = function(){ ...@@ -112,7 +111,6 @@ contextMenuInit = function(){
if(e.composedPath()[0].matches(k)){ if(e.composedPath()[0].matches(k)){
showContextMenu(e,e.composedPath()[0],v) showContextMenu(e,e.composedPath()[0],v)
e.preventDefault() e.preventDefault()
return
} }
}) })
}); });
...@@ -161,14 +159,6 @@ addContextMenuEventListener = initResponse[2]; ...@@ -161,14 +159,6 @@ addContextMenuEventListener = initResponse[2];
appendContextMenuOption('#img2img_interrupt','Cancel generate forever',cancelGenerateForever) appendContextMenuOption('#img2img_interrupt','Cancel generate forever',cancelGenerateForever)
appendContextMenuOption('#img2img_generate', 'Cancel generate forever',cancelGenerateForever) appendContextMenuOption('#img2img_generate', 'Cancel generate forever',cancelGenerateForever)
appendContextMenuOption('#roll','Roll three',
function(){
let rollbutton = get_uiCurrentTabContent().querySelector('#roll');
setTimeout(function(){rollbutton.click()},100)
setTimeout(function(){rollbutton.click()},200)
setTimeout(function(){rollbutton.click()},300)
}
)
})(); })();
//End example Context Menu Items //End example Context Menu Items
......
javascript/edit-attention.js
View file @ 73d95645
...@@ -17,7 +17,7 @@ function keyupEditAttention(event){ ...@@ -17,7 +17,7 @@ function keyupEditAttention(event){
// Find opening parenthesis around current cursor // Find opening parenthesis around current cursor
const before = text.substring(0, selectionStart); const before = text.substring(0, selectionStart);
let beforeParen = before.lastIndexOf(OPEN); let beforeParen = before.lastIndexOf(OPEN);
if (beforeParen == -1) return false; if (beforeParen == -1) return false;
let beforeParenClose = before.lastIndexOf(CLOSE); let beforeParenClose = before.lastIndexOf(CLOSE);
while (beforeParenClose !== -1 && beforeParenClose > beforeParen) { while (beforeParenClose !== -1 && beforeParenClose > beforeParen) {
beforeParen = before.lastIndexOf(OPEN, beforeParen - 1); beforeParen = before.lastIndexOf(OPEN, beforeParen - 1);
...@@ -27,7 +27,7 @@ function keyupEditAttention(event){ ...@@ -27,7 +27,7 @@ function keyupEditAttention(event){
// Find closing parenthesis around current cursor // Find closing parenthesis around current cursor
const after = text.substring(selectionStart); const after = text.substring(selectionStart);
let afterParen = after.indexOf(CLOSE); let afterParen = after.indexOf(CLOSE);
if (afterParen == -1) return false; if (afterParen == -1) return false;
let afterParenOpen = after.indexOf(OPEN); let afterParenOpen = after.indexOf(OPEN);
while (afterParenOpen !== -1 && afterParen > afterParenOpen) { while (afterParenOpen !== -1 && afterParen > afterParenOpen) {
afterParen = after.indexOf(CLOSE, afterParen + 1); afterParen = after.indexOf(CLOSE, afterParen + 1);
...@@ -43,16 +43,34 @@ function keyupEditAttention(event){ ...@@ -43,16 +43,34 @@ function keyupEditAttention(event){
target.setSelectionRange(selectionStart, selectionEnd); target.setSelectionRange(selectionStart, selectionEnd);
return true; return true;
} }
function selectCurrentWord(){
if (selectionStart !== selectionEnd) return false;
const delimiters = opts.keyedit_delimiters + " \r\n\t";
// seek backward until to find beggining
while (!delimiters.includes(text[selectionStart - 1]) && selectionStart > 0) {
selectionStart--;
}
// seek forward to find end
while (!delimiters.includes(text[selectionEnd]) && selectionEnd < text.length) {
selectionEnd++;
}
// If the user hasn't selected anything, let's select their current parenthesis block target.setSelectionRange(selectionStart, selectionEnd);
if(! selectCurrentParenthesisBlock('<', '>')){ return true;
selectCurrentParenthesisBlock('(', ')') }
// If the user hasn't selected anything, let's select their current parenthesis block or word
if (!selectCurrentParenthesisBlock('<', '>') && !selectCurrentParenthesisBlock('(', ')')) {
selectCurrentWord();
} }
event.preventDefault(); event.preventDefault();
closeCharacter = ')' var closeCharacter = ')'
delta = opts.keyedit_precision_attention var delta = opts.keyedit_precision_attention
if (selectionStart > 0 && text[selectionStart - 1] == '<'){ if (selectionStart > 0 && text[selectionStart - 1] == '<'){
closeCharacter = '>' closeCharacter = '>'
...@@ -73,15 +91,21 @@ function keyupEditAttention(event){ ...@@ -73,15 +91,21 @@ function keyupEditAttention(event){
selectionEnd += 1; selectionEnd += 1;
} }
end = text.slice(selectionEnd + 1).indexOf(closeCharacter) + 1; var end = text.slice(selectionEnd + 1).indexOf(closeCharacter) + 1;
weight = parseFloat(text.slice(selectionEnd + 1, selectionEnd + 1 + end)); var weight = parseFloat(text.slice(selectionEnd + 1, selectionEnd + 1 + end));
if (isNaN(weight)) return; if (isNaN(weight)) return;
weight += isPlus ? delta : -delta; weight += isPlus ? delta : -delta;
weight = parseFloat(weight.toPrecision(12)); weight = parseFloat(weight.toPrecision(12));
if(String(weight).length == 1) weight += ".0" if(String(weight).length == 1) weight += ".0"
text = text.slice(0, selectionEnd + 1) + weight + text.slice(selectionEnd + 1 + end - 1); if (closeCharacter == ')' && weight == 1) {
text = text.slice(0, selectionStart - 1) + text.slice(selectionStart, selectionEnd) + text.slice(selectionEnd + 5);
selectionStart--;
selectionEnd--;
} else {
text = text.slice(0, selectionEnd + 1) + weight + text.slice(selectionEnd + 1 + end - 1);
}
target.focus(); target.focus();
target.value = text; target.value = text;
...@@ -93,4 +117,4 @@ function keyupEditAttention(event){ ...@@ -93,4 +117,4 @@ function keyupEditAttention(event){
addEventListener('keydown', (event) => { addEventListener('keydown', (event) => {
keyupEditAttention(event); keyupEditAttention(event);
}); });
\ No newline at end of file
javascript/extensions.js
View file @ 73d95645
function extensions_apply(_, _, disable_all){ function extensions_apply(_disabled_list, _update_list, disable_all){
var disable = [] var disable = []
var update = [] var update = []
gradioApp().querySelectorAll('#extensions input[type="checkbox"]').forEach(function(x){ gradioApp().querySelectorAll('#extensions input[type="checkbox"]').forEach(function(x){
if(x.name.startsWith("enable_") && ! x.checked) if(x.name.startsWith("enable_") && ! x.checked)
disable.push(x.name.substr(7)) disable.push(x.name.substring(7))
if(x.name.startsWith("update_") && x.checked) if(x.name.startsWith("update_") && x.checked)
update.push(x.name.substr(7)) update.push(x.name.substring(7))
}) })
restart_reload() restart_reload()
...@@ -16,12 +16,12 @@ function extensions_apply(_, _, disable_all){ ...@@ -16,12 +16,12 @@ function extensions_apply(_, _, disable_all){
return [JSON.stringify(disable), JSON.stringify(update), disable_all] return [JSON.stringify(disable), JSON.stringify(update), disable_all]
} }
function extensions_check(_, _){ function extensions_check(){
var disable = [] var disable = []
gradioApp().querySelectorAll('#extensions input[type="checkbox"]').forEach(function(x){ gradioApp().querySelectorAll('#extensions input[type="checkbox"]').forEach(function(x){
if(x.name.startsWith("enable_") && ! x.checked) if(x.name.startsWith("enable_") && ! x.checked)
disable.push(x.name.substr(7)) disable.push(x.name.substring(7))
}) })
gradioApp().querySelectorAll('#extensions .extension_status').forEach(function(x){ gradioApp().querySelectorAll('#extensions .extension_status').forEach(function(x){
...@@ -41,9 +41,31 @@ function install_extension_from_index(button, url){ ...@@ -41,9 +41,31 @@ function install_extension_from_index(button, url){
button.disabled = "disabled" button.disabled = "disabled"
button.value = "Installing..." button.value = "Installing..."
textarea = gradioApp().querySelector('#extension_to_install textarea') var textarea = gradioApp().querySelector('#extension_to_install textarea')
textarea.value = url textarea.value = url
updateInput(textarea) updateInput(textarea)
gradioApp().querySelector('#install_extension_button').click() gradioApp().querySelector('#install_extension_button').click()
} }
function config_state_confirm_restore(_, config_state_name, config_restore_type) {
if (config_state_name == "Current") {
return [false, config_state_name, config_restore_type];
}
let restored = "";
if (config_restore_type == "extensions") {
restored = "all saved extension versions";
} else if (config_restore_type == "webui") {
restored = "the webui version";
} else {
restored = "the webui version and all saved extension versions";
}
let confirmed = confirm("Are you sure you want to restore from this state?\nThis will reset " + restored + ".");
if (confirmed) {
restart_reload();
gradioApp().querySelectorAll('#extensions .extension_status').forEach(function(x){
x.innerHTML = "Loading..."
})
}
return [confirmed, config_state_name, config_restore_type];
}
javascript/extraNetworks.js
View file @ 73d95645
...@@ -10,11 +10,11 @@ function setupExtraNetworksForTab(tabname){ ...@@ -10,11 +10,11 @@ function setupExtraNetworksForTab(tabname){
tabs.appendChild(search) tabs.appendChild(search)
tabs.appendChild(refresh) tabs.appendChild(refresh)
search.addEventListener("input", function(evt){ search.addEventListener("input", function(){
searchTerm = search.value.toLowerCase() var searchTerm = search.value.toLowerCase()
gradioApp().querySelectorAll('#'+tabname+'_extra_tabs div.card').forEach(function(elem){ gradioApp().querySelectorAll('#'+tabname+'_extra_tabs div.card').forEach(function(elem){
text = elem.querySelector('.name').textContent.toLowerCase() + " " + elem.querySelector('.search_term').textContent.toLowerCase() var text = elem.querySelector('.name').textContent.toLowerCase() + " " + elem.querySelector('.search_term').textContent.toLowerCase()
elem.style.display = text.indexOf(searchTerm) == -1 ? "none" : "" elem.style.display = text.indexOf(searchTerm) == -1 ? "none" : ""
}) })
}); });
...@@ -55,7 +55,7 @@ function tryToRemoveExtraNetworkFromPrompt(textarea, text){ ...@@ -55,7 +55,7 @@ function tryToRemoveExtraNetworkFromPrompt(textarea, text){
var partToSearch = m[1] var partToSearch = m[1]
var replaced = false var replaced = false
var newTextareaText = textarea.value.replaceAll(re_extranet_g, function(found, index){ var newTextareaText = textarea.value.replaceAll(re_extranet_g, function(found){
m = found.match(re_extranet); m = found.match(re_extranet);
if(m[1] == partToSearch){ if(m[1] == partToSearch){
replaced = true; replaced = true;
...@@ -96,9 +96,9 @@ function saveCardPreview(event, tabname, filename){ ...@@ -96,9 +96,9 @@ function saveCardPreview(event, tabname, filename){
} }
function extraNetworksSearchButton(tabs_id, event){ function extraNetworksSearchButton(tabs_id, event){
searchTextarea = gradioApp().querySelector("#" + tabs_id + ' > div > textarea') var searchTextarea = gradioApp().querySelector("#" + tabs_id + ' > div > textarea')
button = event.target var button = event.target
text = button.classList.contains("search-all") ? "" : button.textContent.trim() var text = button.classList.contains("search-all") ? "" : button.textContent.trim()
searchTextarea.value = text searchTextarea.value = text
updateInput(searchTextarea) updateInput(searchTextarea)
...@@ -133,7 +133,7 @@ function popup(contents){ ...@@ -133,7 +133,7 @@ function popup(contents){
} }
function extraNetworksShowMetadata(text){ function extraNetworksShowMetadata(text){
elem = document.createElement('pre') var elem = document.createElement('pre')
elem.classList.add('popup-metadata'); elem.classList.add('popup-metadata');
elem.textContent = text; elem.textContent = text;
...@@ -165,7 +165,7 @@ function requestGet(url, data, handler, errorHandler){ ...@@ -165,7 +165,7 @@ function requestGet(url, data, handler, errorHandler){
} }
function extraNetworksRequestMetadata(event, extraPage, cardName){ function extraNetworksRequestMetadata(event, extraPage, cardName){
showError = function(){ extraNetworksShowMetadata("there was an error getting metadata"); } var showError = function(){ extraNetworksShowMetadata("there was an error getting metadata"); }
requestGet("./sd_extra_networks/metadata", {"page": extraPage, "item": cardName}, function(data){ requestGet("./sd_extra_networks/metadata", {"page": extraPage, "item": cardName}, function(data){
if(data && data.metadata){ if(data && data.metadata){
......
javascript/generationParams.js
View file @ 73d95645
...@@ -16,14 +16,14 @@ onUiUpdate(function(){ ...@@ -16,14 +16,14 @@ onUiUpdate(function(){
let modalObserver = new MutationObserver(function(mutations) { let modalObserver = new MutationObserver(function(mutations) {
mutations.forEach(function(mutationRecord) { mutations.forEach(function(mutationRecord) {
let selectedTab = gradioApp().querySelector('#tabs div button.bg-white')?.innerText let selectedTab = gradioApp().querySelector('#tabs div button.selected')?.innerText
if (mutationRecord.target.style.display === 'none' && selectedTab === 'txt2img' || selectedTab === 'img2img') if (mutationRecord.target.style.display === 'none' && (selectedTab === 'txt2img' || selectedTab === 'img2img'))
gradioApp().getElementById(selectedTab+"_generation_info_button").click() gradioApp().getElementById(selectedTab+"_generation_info_button")?.click()
}); });
}); });
function attachGalleryListeners(tab_name) { function attachGalleryListeners(tab_name) {
gallery = gradioApp().querySelector('#'+tab_name+'_gallery') var gallery = gradioApp().querySelector('#'+tab_name+'_gallery')
gallery?.addEventListener('click', () => gradioApp().getElementById(tab_name+"_generation_info_button").click()); gallery?.addEventListener('click', () => gradioApp().getElementById(tab_name+"_generation_info_button").click());
gallery?.addEventListener('keydown', (e) => { gallery?.addEventListener('keydown', (e) => {
if (e.keyCode == 37 || e.keyCode == 39) // left or right arrow if (e.keyCode == 37 || e.keyCode == 39) // left or right arrow
......
javascript/hints.js
View file @ 73d95645
...@@ -22,6 +22,7 @@ titles = { ...@@ -22,6 +22,7 @@ titles = {
"\u{1f4cb}": "Apply selected styles to current prompt", "\u{1f4cb}": "Apply selected styles to current prompt",
"\u{1f4d2}": "Paste available values into the field", "\u{1f4d2}": "Paste available values into the field",
"\u{1f3b4}": "Show/hide extra networks", "\u{1f3b4}": "Show/hide extra networks",
"\u{1f300}": "Restore progress",
"Inpaint a part of image": "Draw a mask over an image, and the script will regenerate the masked area with content according to prompt", "Inpaint a part of image": "Draw a mask over an image, and the script will regenerate the masked area with content according to prompt",
"SD upscale": "Upscale image normally, split result into tiles, improve each tile using img2img, merge whole image back", "SD upscale": "Upscale image normally, split result into tiles, improve each tile using img2img, merge whole image back",
...@@ -65,8 +66,8 @@ titles = { ...@@ -65,8 +66,8 @@ titles = {
"Interrogate": "Reconstruct prompt from existing image and put it into the prompt field.", "Interrogate": "Reconstruct prompt from existing image and put it into the prompt field.",
"Images filename pattern": "Use following tags to define how filenames for images are chosen: [steps], [cfg], [prompt_hash], [prompt], [prompt_no_styles], [prompt_spaces], [width], [height], [styles], [sampler], [seed], [model_hash], [model_name], [prompt_words], [date], [datetime], [datetime<Format>], [datetime<Format><Time Zone>], [job_timestamp]; leave empty for default.", "Images filename pattern": "Use following tags to define how filenames for images are chosen: [steps], [cfg], [denoising], [clip_skip], [batch_number], [generation_number], [prompt_hash], [prompt], [prompt_no_styles], [prompt_spaces], [width], [height], [styles], [sampler], [seed], [model_hash], [model_name], [prompt_words], [date], [datetime], [datetime<Format>], [datetime<Format><Time Zone>], [job_timestamp], [hasprompt<prompt1|default><prompt2>..]; leave empty for default.",
"Directory name pattern": "Use following tags to define how subdirectories for images and grids are chosen: [steps], [cfg],[prompt_hash], [prompt], [prompt_no_styles], [prompt_spaces], [width], [height], [styles], [sampler], [seed], [model_hash], [model_name], [prompt_words], [date], [datetime], [datetime<Format>], [datetime<Format><Time Zone>], [job_timestamp]; leave empty for default.", "Directory name pattern": "Use following tags to define how subdirectories for images and grids are chosen: [steps], [cfg], [denoising], [clip_skip], [batch_number], [generation_number], [prompt_hash], [prompt], [prompt_no_styles], [prompt_spaces], [width], [height], [styles], [sampler], [seed], [model_hash], [model_name], [prompt_words], [date], [datetime], [datetime<Format>], [datetime<Format><Time Zone>], [job_timestamp], [hasprompt<prompt1|default><prompt2>..]; leave empty for default.",
"Max prompt words": "Set the maximum number of words to be used in the [prompt_words] option; ATTENTION: If the words are too long, they may exceed the maximum length of the file path that the system can handle", "Max prompt words": "Set the maximum number of words to be used in the [prompt_words] option; ATTENTION: If the words are too long, they may exceed the maximum length of the file path that the system can handle",
"Loopback": "Performs img2img processing multiple times. Output images are used as input for the next loop.", "Loopback": "Performs img2img processing multiple times. Output images are used as input for the next loop.",
...@@ -85,7 +86,6 @@ titles = { ...@@ -85,7 +86,6 @@ titles = {
"vram": "Torch active: Peak amount of VRAM used by Torch during generation, excluding cached data.\nTorch reserved: Peak amount of VRAM allocated by Torch, including all active and cached data.\nSys VRAM: Peak amount of VRAM allocation across all applications / total GPU VRAM (peak utilization%).", "vram": "Torch active: Peak amount of VRAM used by Torch during generation, excluding cached data.\nTorch reserved: Peak amount of VRAM allocated by Torch, including all active and cached data.\nSys VRAM: Peak amount of VRAM allocation across all applications / total GPU VRAM (peak utilization%).",
"Eta noise seed delta": "If this values is non-zero, it will be added to seed and used to initialize RNG for noises when using samplers with Eta. You can use this to produce even more variation of images, or you can use this to match images of other software if you know what you are doing.", "Eta noise seed delta": "If this values is non-zero, it will be added to seed and used to initialize RNG for noises when using samplers with Eta. You can use this to produce even more variation of images, or you can use this to match images of other software if you know what you are doing.",
"Do not add watermark to images": "If this option is enabled, watermark will not be added to created images. Warning: if you do not add watermark, you may be behaving in an unethical manner.",
"Filename word regex": "This regular expression will be used extract words from filename, and they will be joined using the option below into label text used for training. Leave empty to keep filename text as it is.", "Filename word regex": "This regular expression will be used extract words from filename, and they will be joined using the option below into label text used for training. Leave empty to keep filename text as it is.",
"Filename join string": "This string will be used to join split words into a single line if the option above is enabled.", "Filename join string": "This string will be used to join split words into a single line if the option above is enabled.",
...@@ -111,15 +111,18 @@ titles = { ...@@ -111,15 +111,18 @@ titles = {
"Resize height to": "Resizes image to this height. If 0, height is inferred from either of two nearby sliders.", "Resize height to": "Resizes image to this height. If 0, height is inferred from either of two nearby sliders.",
"Multiplier for extra networks": "When adding extra network such as Hypernetwork or Lora to prompt, use this multiplier for it.", "Multiplier for extra networks": "When adding extra network such as Hypernetwork or Lora to prompt, use this multiplier for it.",
"Discard weights with matching name": "Regular expression; if weights's name matches it, the weights is not written to the resulting checkpoint. Use ^model_ema to discard EMA weights.", "Discard weights with matching name": "Regular expression; if weights's name matches it, the weights is not written to the resulting checkpoint. Use ^model_ema to discard EMA weights.",
"Extra networks tab order": "Comma-separated list of tab names; tabs listed here will appear in the extra networks UI first and in order lsited." "Extra networks tab order": "Comma-separated list of tab names; tabs listed here will appear in the extra networks UI first and in order lsited.",
"Negative Guidance minimum sigma": "Skip negative prompt for steps where image is already mostly denoised; the higher this value, the more skips there will be; provides increased performance in exchange for minor quality reduction."
} }
onUiUpdate(function(){ onUiUpdate(function(){
gradioApp().querySelectorAll('span, button, select, p').forEach(function(span){ gradioApp().querySelectorAll('span, button, select, p').forEach(function(span){
tooltip = localization[titles[span.textContent]] || titles[span.textContent]; if (span.title) return; // already has a title
if(!tooltip){ let tooltip = localization[titles[span.textContent]] || titles[span.textContent];
if(!tooltip){
tooltip = localization[titles[span.value]] || titles[span.value]; tooltip = localization[titles[span.value]] || titles[span.value];
} }
......
javascript/hires_fix.js
View file @ 73d95645
function setInactive(elem, inactive){ function onCalcResolutionHires(enable, width, height, hr_scale, hr_resize_x, hr_resize_y){
if(inactive){ function setInactive(elem, inactive){
elem.classList.add('inactive') elem.classList.toggle('inactive', !!inactive)
} else{
elem.classList.remove('inactive')
} }
}
function onCalcResolutionHires(enable, width, height, hr_scale, hr_resize_x, hr_resize_y){ var hrUpscaleBy = gradioApp().getElementById('txt2img_hr_scale')
hrUpscaleBy = gradioApp().getElementById('txt2img_hr_scale') var hrResizeX = gradioApp().getElementById('txt2img_hr_resize_x')
hrResizeX = gradioApp().getElementById('txt2img_hr_resize_x') var hrResizeY = gradioApp().getElementById('txt2img_hr_resize_y')
hrResizeY = gradioApp().getElementById('txt2img_hr_resize_y')
gradioApp().getElementById('txt2img_hires_fix_row2').style.display = opts.use_old_hires_fix_width_height ? "none" : "" gradioApp().getElementById('txt2img_hires_fix_row2').style.display = opts.use_old_hires_fix_width_height ? "none" : ""
......
javascript/imageMaskFix.js
View file @ 73d95645
...@@ -2,11 +2,10 @@ ...@@ -2,11 +2,10 @@
* temporary fix for https://github.com/AUTOMATIC1111/stable-diffusion-webui/issues/668 * temporary fix for https://github.com/AUTOMATIC1111/stable-diffusion-webui/issues/668
* @see https://github.com/gradio-app/gradio/issues/1721 * @see https://github.com/gradio-app/gradio/issues/1721
*/ */
window.addEventListener( 'resize', () => imageMaskResize());
function imageMaskResize() { function imageMaskResize() {
const canvases = gradioApp().querySelectorAll('#img2maskimg .touch-none canvas'); const canvases = gradioApp().querySelectorAll('#img2maskimg .touch-none canvas');
if ( ! canvases.length ) { if ( ! canvases.length ) {
canvases_fixed = false; canvases_fixed = false; // TODO: this is unused..?
window.removeEventListener( 'resize', imageMaskResize ); window.removeEventListener( 'resize', imageMaskResize );
return; return;
} }
...@@ -15,7 +14,7 @@ function imageMaskResize() { ...@@ -15,7 +14,7 @@ function imageMaskResize() {
const previewImage = wrapper.previousElementSibling; const previewImage = wrapper.previousElementSibling;
if ( ! previewImage.complete ) { if ( ! previewImage.complete ) {
previewImage.addEventListener( 'load', () => imageMaskResize()); previewImage.addEventListener( 'load', imageMaskResize);
return; return;
} }
...@@ -24,7 +23,6 @@ function imageMaskResize() { ...@@ -24,7 +23,6 @@ function imageMaskResize() {
const nw = previewImage.naturalWidth; const nw = previewImage.naturalWidth;
const nh = previewImage.naturalHeight; const nh = previewImage.naturalHeight;
const portrait = nh > nw; const portrait = nh > nw;
const factor = portrait;
const wW = Math.min(w, portrait ? h/nh*nw : w/nw*nw); const wW = Math.min(w, portrait ? h/nh*nw : w/nw*nw);
const wH = Math.min(h, portrait ? h/nh*nh : w/nw*nh); const wH = Math.min(h, portrait ? h/nh*nh : w/nw*nh);
...@@ -40,6 +38,7 @@ function imageMaskResize() { ...@@ -40,6 +38,7 @@ function imageMaskResize() {
c.style.maxHeight = '100%'; c.style.maxHeight = '100%';
c.style.objectFit = 'contain'; c.style.objectFit = 'contain';
}); });
} }
onUiUpdate(() => imageMaskResize()); onUiUpdate(imageMaskResize);
window.addEventListener( 'resize', imageMaskResize);
javascript/imageParams.js
View file @ 73d95645
window.onload = (function(){ window.onload = (function(){
window.addEventListener('drop', e => { window.addEventListener('drop', e => {
const target = e.composedPath()[0]; const target = e.composedPath()[0];
const idx = selected_gallery_index();
if (target.placeholder.indexOf("Prompt") == -1) return; if (target.placeholder.indexOf("Prompt") == -1) return;
let prompt_target = get_tab_index('tabs') == 1 ? "img2img_prompt_image" : "txt2img_prompt_image"; let prompt_target = get_tab_index('tabs') == 1 ? "img2img_prompt_image" : "txt2img_prompt_image";
......
javascript/imageviewer.js
View file @ 73d95645
...@@ -57,7 +57,7 @@ function modalImageSwitch(offset) { ...@@ -57,7 +57,7 @@ function modalImageSwitch(offset) {
}) })
if (result != -1) { if (result != -1) {
nextButton = galleryButtons[negmod((result + offset), galleryButtons.length)] var nextButton = galleryButtons[negmod((result + offset), galleryButtons.length)]
nextButton.click() nextButton.click()
const modalImage = gradioApp().getElementById("modalImage"); const modalImage = gradioApp().getElementById("modalImage");
const modal = gradioApp().getElementById("lightboxModal"); const modal = gradioApp().getElementById("lightboxModal");
...@@ -144,15 +144,11 @@ function setupImageForLightbox(e) { ...@@ -144,15 +144,11 @@ function setupImageForLightbox(e) {
} }
function modalZoomSet(modalImage, enable) { function modalZoomSet(modalImage, enable) {
if (enable) { if(modalImage) modalImage.classList.toggle('modalImageFullscreen', !!enable);
modalImage.classList.add('modalImageFullscreen');
} else {
modalImage.classList.remove('modalImageFullscreen');
}
} }
function modalZoomToggle(event) { function modalZoomToggle(event) {
modalImage = gradioApp().getElementById("modalImage"); var modalImage = gradioApp().getElementById("modalImage");
modalZoomSet(modalImage, !modalImage.classList.contains('modalImageFullscreen')) modalZoomSet(modalImage, !modalImage.classList.contains('modalImageFullscreen'))
event.stopPropagation() event.stopPropagation()
} }
...@@ -179,7 +175,7 @@ function galleryImageHandler(e) { ...@@ -179,7 +175,7 @@ function galleryImageHandler(e) {
} }
onUiUpdate(function() { onUiUpdate(function() {
fullImg_preview = gradioApp().querySelectorAll('.gradio-gallery > div > img') var fullImg_preview = gradioApp().querySelectorAll('.gradio-gallery > div > img')
if (fullImg_preview != null) { if (fullImg_preview != null) {
fullImg_preview.forEach(setupImageForLightbox); fullImg_preview.forEach(setupImageForLightbox);
} }
...@@ -251,8 +247,11 @@ document.addEventListener("DOMContentLoaded", function() { ...@@ -251,8 +247,11 @@ document.addEventListener("DOMContentLoaded", function() {
modal.appendChild(modalNext) modal.appendChild(modalNext)
gradioApp().appendChild(modal) try {
gradioApp().appendChild(modal);
} catch (e) {
gradioApp().body.appendChild(modal);
}
document.body.appendChild(modal); document.body.appendChild(modal);
......
javascript/imageviewerGamepad.js 0 → 100644
View file @ 73d95645
window.addEventListener('gamepadconnected', (e) => {
const index = e.gamepad.index;
let isWaiting = false;
setInterval(async () => {
if (!opts.js_modal_lightbox_gamepad || isWaiting) return;
const gamepad = navigator.getGamepads()[index];
const xValue = gamepad.axes[0];
if (xValue <= -0.3) {
modalPrevImage(e);
isWaiting = true;
} else if (xValue >= 0.3) {
modalNextImage(e);
isWaiting = true;
}
if (isWaiting) {
await sleepUntil(() => {
const xValue = navigator.getGamepads()[index].axes[0]
if (xValue < 0.3 && xValue > -0.3) {
return true;
}
}, opts.js_modal_lightbox_gamepad_repeat);
isWaiting = false;
}
}, 10);
});
/*
Primarily for vr controller type pointer devices.
I use the wheel event because there's currently no way to do it properly with web xr.
*/
let isScrolling = false;
window.addEventListener('wheel', (e) => {
if (!opts.js_modal_lightbox_gamepad || isScrolling) return;
isScrolling = true;
if (e.deltaX <= -0.6) {
modalPrevImage(e);
} else if (e.deltaX >= 0.6) {
modalNextImage(e);
}
setTimeout(() => {
isScrolling = false;
}, opts.js_modal_lightbox_gamepad_repeat);
});
function sleepUntil(f, timeout) {
return new Promise((resolve) => {
const timeStart = new Date();
const wait = setInterval(function() {
if (f() || new Date() - timeStart > timeout) {
clearInterval(wait);
resolve();
}
}, 20);
});
}
javascript/localization.js
View file @ 73d95645
...@@ -25,6 +25,10 @@ re_emoji = /[\p{Extended_Pictographic}\u{1F3FB}-\u{1F3FF}\u{1F9B0}-\u{1F9B3}]/u ...@@ -25,6 +25,10 @@ re_emoji = /[\p{Extended_Pictographic}\u{1F3FB}-\u{1F3FF}\u{1F9B0}-\u{1F9B3}]/u
original_lines = {} original_lines = {}
translated_lines = {} translated_lines = {}
function hasLocalization() {
return window.localization && Object.keys(window.localization).length > 0;
}
function textNodesUnder(el){ function textNodesUnder(el){
var n, a=[], walk=document.createTreeWalker(el,NodeFilter.SHOW_TEXT,null,false); var n, a=[], walk=document.createTreeWalker(el,NodeFilter.SHOW_TEXT,null,false);
while(n=walk.nextNode()) a.push(n); while(n=walk.nextNode()) a.push(n);
...@@ -35,11 +39,11 @@ function canBeTranslated(node, text){ ...@@ -35,11 +39,11 @@ function canBeTranslated(node, text){
if(! text) return false; if(! text) return false;
if(! node.parentElement) return false; if(! node.parentElement) return false;
parentType = node.parentElement.nodeName var parentType = node.parentElement.nodeName
if(parentType=='SCRIPT' || parentType=='STYLE' || parentType=='TEXTAREA') return false; if(parentType=='SCRIPT' || parentType=='STYLE' || parentType=='TEXTAREA') return false;
if (parentType=='OPTION' || parentType=='SPAN'){ if (parentType=='OPTION' || parentType=='SPAN'){
pnode = node var pnode = node
for(var level=0; level<4; level++){ for(var level=0; level<4; level++){
pnode = pnode.parentElement pnode = pnode.parentElement
if(! pnode) break; if(! pnode) break;
...@@ -69,7 +73,7 @@ function getTranslation(text){ ...@@ -69,7 +73,7 @@ function getTranslation(text){
} }
function processTextNode(node){ function processTextNode(node){
text = node.textContent.trim() var text = node.textContent.trim()
if(! canBeTranslated(node, text)) return if(! canBeTranslated(node, text)) return
...@@ -105,7 +109,7 @@ function processNode(node){ ...@@ -105,7 +109,7 @@ function processNode(node){
} }
function dumpTranslations(){ function dumpTranslations(){
dumped = {} var dumped = {}
if (localization.rtl) { if (localization.rtl) {
dumped.rtl = true dumped.rtl = true
} }
...@@ -119,39 +123,8 @@ function dumpTranslations(){ ...@@ -119,39 +123,8 @@ function dumpTranslations(){
return dumped return dumped
} }
onUiUpdate(function(m){
m.forEach(function(mutation){
mutation.addedNodes.forEach(function(node){
processNode(node)
})
});
})
document.addEventListener("DOMContentLoaded", function() {
processNode(gradioApp())
if (localization.rtl) { // if the language is from right to left,
(new MutationObserver((mutations, observer) => { // wait for the style to load
mutations.forEach(mutation => {
mutation.addedNodes.forEach(node => {
if (node.tagName === 'STYLE') {
observer.disconnect();
for (const x of node.sheet.rules) { // find all rtl media rules
if (Array.from(x.media || []).includes('rtl')) {
x.media.appendMedium('all'); // enable them
}
}
}
})
});
})).observe(gradioApp(), { childList: true });
}
})
function download_localization() { function download_localization() {
text = JSON.stringify(dumpTranslations(), null, 4) var text = JSON.stringify(dumpTranslations(), null, 4)
var element = document.createElement('a'); var element = document.createElement('a');
element.setAttribute('href', 'data:text/plain;charset=utf-8,' + encodeURIComponent(text)); element.setAttribute('href', 'data:text/plain;charset=utf-8,' + encodeURIComponent(text));
...@@ -163,3 +136,36 @@ function download_localization() { ...@@ -163,3 +136,36 @@ function download_localization() {
document.body.removeChild(element); document.body.removeChild(element);
} }
if(hasLocalization()) {
onUiUpdate(function (m) {
m.forEach(function (mutation) {
mutation.addedNodes.forEach(function (node) {
processNode(node)
})
});
})
document.addEventListener("DOMContentLoaded", function () {
processNode(gradioApp())
if (localization.rtl) { // if the language is from right to left,
(new MutationObserver((mutations, observer) => { // wait for the style to load
mutations.forEach(mutation => {
mutation.addedNodes.forEach(node => {
if (node.tagName === 'STYLE') {
observer.disconnect();
for (const x of node.sheet.rules) { // find all rtl media rules
if (Array.from(x.media || []).includes('rtl')) {
x.media.appendMedium('all'); // enable them
}
}
}
})
});
})).observe(gradioApp(), { childList: true });
}
})
}
javascript/notification.js
View file @ 73d95645
...@@ -2,15 +2,15 @@ ...@@ -2,15 +2,15 @@
let lastHeadImg = null; let lastHeadImg = null;
notificationButton = null let notificationButton = null;
onUiUpdate(function(){ onUiUpdate(function(){
if(notificationButton == null){ if(notificationButton == null){
notificationButton = gradioApp().getElementById('request_notifications') notificationButton = gradioApp().getElementById('request_notifications')
if(notificationButton != null){ if(notificationButton != null){
notificationButton.addEventListener('click', function (evt) { notificationButton.addEventListener('click', () => {
Notification.requestPermission(); void Notification.requestPermission();
},true); },true);
} }
} }
......
javascript/progressbar.js
View file @ 73d95645
// code related to showing and updating progressbar shown as the image is being made // code related to showing and updating progressbar shown as the image is being made
function rememberGallerySelection(id_gallery){ function rememberGallerySelection(){
} }
function getGallerySelectedIndex(id_gallery){ function getGallerySelectedIndex(){
} }
function request(url, data, handler, errorHandler){ function request(url, data, handler, errorHandler){
var xhr = new XMLHttpRequest(); var xhr = new XMLHttpRequest();
var url = url;
xhr.open("POST", url, true); xhr.open("POST", url, true);
xhr.setRequestHeader("Content-Type", "application/json"); xhr.setRequestHeader("Content-Type", "application/json");
xhr.onreadystatechange = function () { xhr.onreadystatechange = function () {
...@@ -66,7 +65,7 @@ function randomId(){ ...@@ -66,7 +65,7 @@ function randomId(){
// starts sending progress requests to "/internal/progress" uri, creating progressbar above progressbarContainer element and // starts sending progress requests to "/internal/progress" uri, creating progressbar above progressbarContainer element and
// preview inside gallery element. Cleans up all created stuff when the task is over and calls atEnd. // preview inside gallery element. Cleans up all created stuff when the task is over and calls atEnd.
// calls onProgress every time there is a progress update // calls onProgress every time there is a progress update
function requestProgress(id_task, progressbarContainer, gallery, atEnd, onProgress){ function requestProgress(id_task, progressbarContainer, gallery, atEnd, onProgress, inactivityTimeout=40){
var dateStart = new Date() var dateStart = new Date()
var wasEverActive = false var wasEverActive = false
var parentProgressbar = progressbarContainer.parentNode var parentProgressbar = progressbarContainer.parentNode
...@@ -107,7 +106,7 @@ function requestProgress(id_task, progressbarContainer, gallery, atEnd, onProgre ...@@ -107,7 +106,7 @@ function requestProgress(id_task, progressbarContainer, gallery, atEnd, onProgre
divProgress.style.width = rect.width + "px"; divProgress.style.width = rect.width + "px";
} }
progressText = "" let progressText = ""
divInner.style.width = ((res.progress || 0) * 100.0) + '%' divInner.style.width = ((res.progress || 0) * 100.0) + '%'
divInner.style.background = res.progress ? "" : "transparent" divInner.style.background = res.progress ? "" : "transparent"
...@@ -138,7 +137,7 @@ function requestProgress(id_task, progressbarContainer, gallery, atEnd, onProgre ...@@ -138,7 +137,7 @@ function requestProgress(id_task, progressbarContainer, gallery, atEnd, onProgre
return return
} }
if(elapsedFromStart > 5 && !res.queued && !res.active){ if(elapsedFromStart > inactivityTimeout && !res.queued && !res.active){
removeProgressBar() removeProgressBar()
return return
} }
......
javascript/ui.js
View file @ 73d95645
// various functions for interaction with ui.py not large enough to warrant putting them in separate files // various functions for interaction with ui.py not large enough to warrant putting them in separate files
function set_theme(theme){ function set_theme(theme){
gradioURL = window.location.href var gradioURL = window.location.href
if (!gradioURL.includes('?__theme=')) { if (!gradioURL.includes('?__theme=')) {
window.location.replace(gradioURL + '?__theme=' + theme); window.location.replace(gradioURL + '?__theme=' + theme);
} }
...@@ -47,7 +47,7 @@ function extract_image_from_gallery(gallery){ ...@@ -47,7 +47,7 @@ function extract_image_from_gallery(gallery){
return [gallery[0]]; return [gallery[0]];
} }
index = selected_gallery_index() var index = selected_gallery_index()
if (index < 0 || index >= gallery.length){ if (index < 0 || index >= gallery.length){
// Use the first image in the gallery as the default // Use the first image in the gallery as the default
...@@ -58,7 +58,7 @@ function extract_image_from_gallery(gallery){ ...@@ -58,7 +58,7 @@ function extract_image_from_gallery(gallery){
} }
function args_to_array(args){ function args_to_array(args){
res = [] var res = []
for(var i=0;i<args.length;i++){ for(var i=0;i<args.length;i++){
res.push(args[i]) res.push(args[i])
} }
...@@ -138,7 +138,7 @@ function get_img2img_tab_index() { ...@@ -138,7 +138,7 @@ function get_img2img_tab_index() {
} }
function create_submit_args(args){ function create_submit_args(args){
res = [] var res = []
for(var i=0;i<args.length;i++){ for(var i=0;i<args.length;i++){
res.push(args[i]) res.push(args[i])
} }
...@@ -159,14 +159,24 @@ function showSubmitButtons(tabname, show){ ...@@ -159,14 +159,24 @@ function showSubmitButtons(tabname, show){
gradioApp().getElementById(tabname+'_skip').style.display = show ? "none" : "block" gradioApp().getElementById(tabname+'_skip').style.display = show ? "none" : "block"
} }
function showRestoreProgressButton(tabname, show){
var button = gradioApp().getElementById(tabname + "_restore_progress")
if(! button) return
button.style.display = show ? "flex" : "none"
}
function submit(){ function submit(){
rememberGallerySelection('txt2img_gallery') rememberGallerySelection('txt2img_gallery')
showSubmitButtons('txt2img', false) showSubmitButtons('txt2img', false)
var id = randomId() var id = randomId()
localStorage.setItem("txt2img_task_id", id);
requestProgress(id, gradioApp().getElementById('txt2img_gallery_container'), gradioApp().getElementById('txt2img_gallery'), function(){ requestProgress(id, gradioApp().getElementById('txt2img_gallery_container'), gradioApp().getElementById('txt2img_gallery'), function(){
showSubmitButtons('txt2img', true) showSubmitButtons('txt2img', true)
localStorage.removeItem("txt2img_task_id")
showRestoreProgressButton('txt2img', false)
}) })
var res = create_submit_args(arguments) var res = create_submit_args(arguments)
...@@ -181,8 +191,12 @@ function submit_img2img(){ ...@@ -181,8 +191,12 @@ function submit_img2img(){
showSubmitButtons('img2img', false) showSubmitButtons('img2img', false)
var id = randomId() var id = randomId()
localStorage.setItem("img2img_task_id", id);
requestProgress(id, gradioApp().getElementById('img2img_gallery_container'), gradioApp().getElementById('img2img_gallery'), function(){ requestProgress(id, gradioApp().getElementById('img2img_gallery_container'), gradioApp().getElementById('img2img_gallery'), function(){
showSubmitButtons('img2img', true) showSubmitButtons('img2img', true)
localStorage.removeItem("img2img_task_id")
showRestoreProgressButton('img2img', false)
}) })
var res = create_submit_args(arguments) var res = create_submit_args(arguments)
...@@ -193,6 +207,42 @@ function submit_img2img(){ ...@@ -193,6 +207,42 @@ function submit_img2img(){
return res return res
} }
function restoreProgressTxt2img(){
showRestoreProgressButton("txt2img", false)
var id = localStorage.getItem("txt2img_task_id")
id = localStorage.getItem("txt2img_task_id")
if(id) {
requestProgress(id, gradioApp().getElementById('txt2img_gallery_container'), gradioApp().getElementById('txt2img_gallery'), function(){
showSubmitButtons('txt2img', true)
}, null, 0)
}
return id
}
function restoreProgressImg2img(){
showRestoreProgressButton("img2img", false)
var id = localStorage.getItem("img2img_task_id")
if(id) {
requestProgress(id, gradioApp().getElementById('img2img_gallery_container'), gradioApp().getElementById('img2img_gallery'), function(){
showSubmitButtons('img2img', true)
}, null, 0)
}
return id
}
onUiLoaded(function () {
showRestoreProgressButton('txt2img', localStorage.getItem("txt2img_task_id"))
showRestoreProgressButton('img2img', localStorage.getItem("img2img_task_id"))
});
function modelmerger(){ function modelmerger(){
var id = randomId() var id = randomId()
requestProgress(id, gradioApp().getElementById('modelmerger_results_panel'), null, function(){}) requestProgress(id, gradioApp().getElementById('modelmerger_results_panel'), null, function(){})
...@@ -204,7 +254,7 @@ function modelmerger(){ ...@@ -204,7 +254,7 @@ function modelmerger(){
function ask_for_style_name(_, prompt_text, negative_prompt_text) { function ask_for_style_name(_, prompt_text, negative_prompt_text) {
name_ = prompt('Style name:') var name_ = prompt('Style name:')
return [name_, prompt_text, negative_prompt_text] return [name_, prompt_text, negative_prompt_text]
} }
...@@ -239,11 +289,11 @@ function recalculate_prompts_img2img(){ ...@@ -239,11 +289,11 @@ function recalculate_prompts_img2img(){
} }
opts = {} var opts = {}
onUiUpdate(function(){ onUiUpdate(function(){
if(Object.keys(opts).length != 0) return; if(Object.keys(opts).length != 0) return;
json_elem = gradioApp().getElementById('settings_json') var json_elem = gradioApp().getElementById('settings_json')
if(json_elem == null) return; if(json_elem == null) return;
var textarea = json_elem.querySelector('textarea') var textarea = json_elem.querySelector('textarea')
...@@ -292,8 +342,8 @@ onUiUpdate(function(){ ...@@ -292,8 +342,8 @@ onUiUpdate(function(){
registerTextarea('img2img_prompt', 'img2img_token_counter', 'img2img_token_button') registerTextarea('img2img_prompt', 'img2img_token_counter', 'img2img_token_button')
registerTextarea('img2img_neg_prompt', 'img2img_negative_token_counter', 'img2img_negative_token_button') registerTextarea('img2img_neg_prompt', 'img2img_negative_token_counter', 'img2img_negative_token_button')
show_all_pages = gradioApp().getElementById('settings_show_all_pages') var show_all_pages = gradioApp().getElementById('settings_show_all_pages')
settings_tabs = gradioApp().querySelector('#settings div') var settings_tabs = gradioApp().querySelector('#settings div')
if(show_all_pages && settings_tabs){ if(show_all_pages && settings_tabs){
settings_tabs.appendChild(show_all_pages) settings_tabs.appendChild(show_all_pages)
show_all_pages.onclick = function(){ show_all_pages.onclick = function(){
...@@ -305,9 +355,9 @@ onUiUpdate(function(){ ...@@ -305,9 +355,9 @@ onUiUpdate(function(){
}) })
onOptionsChanged(function(){ onOptionsChanged(function(){
elem = gradioApp().getElementById('sd_checkpoint_hash') var elem = gradioApp().getElementById('sd_checkpoint_hash')
sd_checkpoint_hash = opts.sd_checkpoint_hash || "" var sd_checkpoint_hash = opts.sd_checkpoint_hash || ""
shorthash = sd_checkpoint_hash.substr(0,10) var shorthash = sd_checkpoint_hash.substring(0,10)
if(elem && elem.textContent != shorthash){ if(elem && elem.textContent != shorthash){
elem.textContent = shorthash elem.textContent = shorthash
...@@ -361,3 +411,19 @@ function selectCheckpoint(name){ ...@@ -361,3 +411,19 @@ function selectCheckpoint(name){
desiredCheckpointName = name; desiredCheckpointName = name;
gradioApp().getElementById('change_checkpoint').click() gradioApp().getElementById('change_checkpoint').click()
} }
function currentImg2imgSourceResolution(_, _, scaleBy){
var img = gradioApp().querySelector('#mode_img2img > div[style="display: block;"] img')
return img ? [img.naturalWidth, img.naturalHeight, scaleBy] : [0, 0, scaleBy]
}
function updateImg2imgResizeToTextAfterChangingImage(){
// At the time this is called from gradio, the image has no yet been replaced.
// There may be a better solution, but this is simple and straightforward so I'm going with it.
setTimeout(function() {
gradioApp().getElementById('img2img_update_resize_to').click()
}, 500);
return []
}
launch.py
View file @ 73d95645
...@@ -19,7 +19,6 @@ python = sys.executable ...@@ -19,7 +19,6 @@ python = sys.executable
git = os.environ.get('GIT', "git") git = os.environ.get('GIT', "git")
index_url = os.environ.get('INDEX_URL', "") index_url = os.environ.get('INDEX_URL', "")
stored_commit_hash = None stored_commit_hash = None
skip_install = False
dir_repos = "repositories" dir_repos = "repositories"
if 'GRADIO_ANALYTICS_ENABLED' not in os.environ: if 'GRADIO_ANALYTICS_ENABLED' not in os.environ:
...@@ -49,7 +48,7 @@ or any other error regarding unsuccessful package (library) installation, ...@@ -49,7 +48,7 @@ or any other error regarding unsuccessful package (library) installation,
please downgrade (or upgrade) to the latest version of 3.10 Python please downgrade (or upgrade) to the latest version of 3.10 Python
and delete current Python and "venv" folder in WebUI's directory. and delete current Python and "venv" folder in WebUI's directory.
You can download 3.10 Python from here: https://www.python.org/downloads/release/python-3109/ You can download 3.10 Python from here: https://www.python.org/downloads/release/python-3106/
{"Alternatively, use a binary release of WebUI: https://github.com/AUTOMATIC1111/stable-diffusion-webui/releases" if is_windows else ""} {"Alternatively, use a binary release of WebUI: https://github.com/AUTOMATIC1111/stable-diffusion-webui/releases" if is_windows else ""}
...@@ -121,12 +120,12 @@ def run_python(code, desc=None, errdesc=None): ...@@ -121,12 +120,12 @@ def run_python(code, desc=None, errdesc=None):
return run(f'"{python}" -c "{code}"', desc, errdesc) return run(f'"{python}" -c "{code}"', desc, errdesc)
def run_pip(args, desc=None): def run_pip(command, desc=None, live=False):
if skip_install: if args.skip_install:
return return
index_url_line = f' --index-url {index_url}' if index_url != '' else '' index_url_line = f' --index-url {index_url}' if index_url != '' else ''
return run(f'"{python}" -m pip {args} --prefer-binary{index_url_line}', desc=f"Installing {desc}", errdesc=f"Couldn't install {desc}") return run(f'"{python}" -m pip {command} --prefer-binary{index_url_line}', desc=f"Installing {desc}", errdesc=f"Couldn't install {desc}", live=live)
def check_run_python(code): def check_run_python(code):
...@@ -223,12 +222,10 @@ def run_extensions_installers(settings_file): ...@@ -223,12 +222,10 @@ def run_extensions_installers(settings_file):
def prepare_environment(): def prepare_environment():
global skip_install torch_command = os.environ.get('TORCH_COMMAND', "pip install torch==2.0.0 torchvision==0.15.1 --extra-index-url https://download.pytorch.org/whl/cu118")
torch_command = os.environ.get('TORCH_COMMAND', "pip install torch==1.13.1+cu117 torchvision==0.14.1+cu117 --extra-index-url https://download.pytorch.org/whl/cu117")
requirements_file = os.environ.get('REQS_FILE', "requirements_versions.txt") requirements_file = os.environ.get('REQS_FILE', "requirements_versions.txt")
xformers_package = os.environ.get('XFORMERS_PACKAGE', 'xformers==0.0.16rc425') xformers_package = os.environ.get('XFORMERS_PACKAGE', 'xformers==0.0.17')
gfpgan_package = os.environ.get('GFPGAN_PACKAGE', "git+https://github.com/TencentARC/GFPGAN.git@8d2447a2d918f8eba5a4a01463fd48e45126a379") gfpgan_package = os.environ.get('GFPGAN_PACKAGE', "git+https://github.com/TencentARC/GFPGAN.git@8d2447a2d918f8eba5a4a01463fd48e45126a379")
clip_package = os.environ.get('CLIP_PACKAGE', "git+https://github.com/openai/CLIP.git@d50d76daa670286dd6cacf3bcd80b5e4823fc8e1") clip_package = os.environ.get('CLIP_PACKAGE', "git+https://github.com/openai/CLIP.git@d50d76daa670286dd6cacf3bcd80b5e4823fc8e1")
openclip_package = os.environ.get('OPENCLIP_PACKAGE', "git+https://github.com/mlfoundations/open_clip.git@bb6e834e9c70d9c27d0dc3ecedeebeaeb1ffad6b") openclip_package = os.environ.get('OPENCLIP_PACKAGE', "git+https://github.com/mlfoundations/open_clip.git@bb6e834e9c70d9c27d0dc3ecedeebeaeb1ffad6b")
...@@ -271,7 +268,7 @@ def prepare_environment(): ...@@ -271,7 +268,7 @@ def prepare_environment():
if (not is_installed("xformers") or args.reinstall_xformers) and args.xformers: if (not is_installed("xformers") or args.reinstall_xformers) and args.xformers:
if platform.system() == "Windows": if platform.system() == "Windows":
if platform.python_version().startswith("3.10"): if platform.python_version().startswith("3.10"):
run_pip(f"install -U -I --no-deps {xformers_package}", "xformers") run_pip(f"install -U -I --no-deps {xformers_package}", "xformers", live=True)
else: else:
print("Installation of xformers is not supported in this version of Python.") print("Installation of xformers is not supported in this version of Python.")
print("You can also check this and build manually: https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Xformers#building-xformers-on-windows-by-duckness") print("You can also check this and build manually: https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Xformers#building-xformers-on-windows-by-duckness")
...@@ -296,7 +293,7 @@ def prepare_environment(): ...@@ -296,7 +293,7 @@ def prepare_environment():
if not os.path.isfile(requirements_file): if not os.path.isfile(requirements_file):
requirements_file = os.path.join(script_path, requirements_file) requirements_file = os.path.join(script_path, requirements_file)
run_pip(f"install -r \"{requirements_file}\"", "requirements for Web UI") run_pip(f"install -r \"{requirements_file}\"", "requirements")
run_extensions_installers(settings_file=args.ui_settings_file) run_extensions_installers(settings_file=args.ui_settings_file)
......
modules/api/api.py
View file @ 73d95645
...@@ -6,7 +6,6 @@ import uvicorn ...@@ -6,7 +6,6 @@ import uvicorn
import gradio as gr import gradio as gr
from threading import Lock from threading import Lock
from io import BytesIO from io import BytesIO
from gradio.processing_utils import decode_base64_to_file
from fastapi import APIRouter, Depends, FastAPI, Request, Response from fastapi import APIRouter, Depends, FastAPI, Request, Response
from fastapi.security import HTTPBasic, HTTPBasicCredentials from fastapi.security import HTTPBasic, HTTPBasicCredentials
from fastapi.exceptions import HTTPException from fastapi.exceptions import HTTPException
...@@ -131,8 +130,8 @@ def api_middleware(app: FastAPI): ...@@ -131,8 +130,8 @@ def api_middleware(app: FastAPI):
"body": vars(e).get('body', ''), "body": vars(e).get('body', ''),
"errors": str(e), "errors": str(e),
} }
print(f"API error: {request.method}: {request.url} {err}")
if not isinstance(e, HTTPException): # do not print backtrace on known httpexceptions if not isinstance(e, HTTPException): # do not print backtrace on known httpexceptions
print(f"API error: {request.method}: {request.url} {err}")
if rich_available: 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])) console.print_exception(show_locals=True, max_frames=2, extra_lines=1, suppress=[anyio, starlette], word_wrap=False, width=min([console.width, 200]))
else: else:
...@@ -272,7 +271,9 @@ class Api: ...@@ -272,7 +271,9 @@ class Api:
raise HTTPException(status_code=422, detail=f"Cannot have a selectable script in the always on scripts params") 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 # 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]: 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 return script_args
def text2imgapi(self, txt2imgreq: StableDiffusionTxt2ImgProcessingAPI): def text2imgapi(self, txt2imgreq: StableDiffusionTxt2ImgProcessingAPI):
...@@ -395,16 +396,11 @@ class Api: ...@@ -395,16 +396,11 @@ class Api:
def extras_batch_images_api(self, req: ExtrasBatchImagesRequest): def extras_batch_images_api(self, req: ExtrasBatchImagesRequest):
reqDict = setUpscalers(req) reqDict = setUpscalers(req)
def prepareFiles(file): image_list = reqDict.pop('imageList', [])
file = decode_base64_to_file(file.data, file_path=file.name) image_folder = [decode_base64_to_image(x.data) for x in image_list]
file.orig_name = file.name
return file
reqDict['image_folder'] = list(map(prepareFiles, reqDict['imageList']))
reqDict.pop('imageList')
with self.queue_lock: 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]) return ExtrasBatchImagesResponse(images=list(map(encode_pil_to_base64, result[0])), html_info=result[1])
......
modules/call_queue.py
View file @ 73d95645
...@@ -35,6 +35,7 @@ def wrap_gradio_gpu_call(func, extra_outputs=None): ...@@ -35,6 +35,7 @@ def wrap_gradio_gpu_call(func, extra_outputs=None):
try: try:
res = func(*args, **kwargs) res = func(*args, **kwargs)
progress.record_results(id_task, res)
finally: finally:
progress.finish_task(id_task) progress.finish_task(id_task)
......
modules/cmd_args.py
View file @ 73d95645
...@@ -95,9 +95,11 @@ parser.add_argument("--cors-allow-origins", type=str, help="Allowed CORS origin( ...@@ -95,9 +95,11 @@ parser.add_argument("--cors-allow-origins", type=str, help="Allowed CORS origin(
parser.add_argument("--cors-allow-origins-regex", type=str, help="Allowed CORS origin(s) in the form of a single regular expression", default=None) parser.add_argument("--cors-allow-origins-regex", type=str, help="Allowed CORS origin(s) in the form of a single regular expression", default=None)
parser.add_argument("--tls-keyfile", type=str, help="Partially enables TLS, requires --tls-certfile to fully function", default=None) parser.add_argument("--tls-keyfile", type=str, help="Partially enables TLS, requires --tls-certfile to fully function", default=None)
parser.add_argument("--tls-certfile", type=str, help="Partially enables TLS, requires --tls-keyfile to fully function", default=None) parser.add_argument("--tls-certfile", type=str, help="Partially enables TLS, requires --tls-keyfile to fully function", default=None)
parser.add_argument("--disable-tls-verify", action="store_false", help="When passed, enables the use of self-signed certificates.", default=None)
parser.add_argument("--server-name", type=str, help="Sets hostname of server", default=None) parser.add_argument("--server-name", type=str, help="Sets hostname of server", default=None)
parser.add_argument("--gradio-queue", action='store_true', help="does not do anything", default=True) parser.add_argument("--gradio-queue", action='store_true', help="does not do anything", default=True)
parser.add_argument("--no-gradio-queue", action='store_true', help="Disables gradio queue; causes the webpage to use http requests instead of websockets; was the defaul in earlier versions") parser.add_argument("--no-gradio-queue", action='store_true', help="Disables gradio queue; causes the webpage to use http requests instead of websockets; was the defaul in earlier versions")
parser.add_argument("--skip-version-check", action='store_true', help="Do not check versions of torch and xformers") parser.add_argument("--skip-version-check", action='store_true', help="Do not check versions of torch and xformers")
parser.add_argument("--no-hashing", action='store_true', help="disable sha256 hashing of checkpoints to help loading performance", default=False) 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("--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')
\ No newline at end of file
modules/config_states.py 0 → 100644
View file @ 73d95645
"""
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
View file @ 73d95645
...@@ -92,14 +92,18 @@ def cond_cast_float(input): ...@@ -92,14 +92,18 @@ def cond_cast_float(input):
def randn(seed, shape): def randn(seed, shape):
from modules.shared import opts
torch.manual_seed(seed) 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=cpu).to(device)
return torch.randn(shape, device=device) return torch.randn(shape, device=device)
def randn_without_seed(shape): 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=cpu).to(device)
return torch.randn(shape, device=device) return torch.randn(shape, device=device)
......
modules/extensions.py
View file @ 73d95645
...@@ -3,10 +3,11 @@ import sys ...@@ -3,10 +3,11 @@ import sys
import traceback import traceback
import time import time
from datetime import datetime
import git import git
from modules import shared 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 = [] extensions = []
...@@ -31,12 +32,15 @@ class Extension: ...@@ -31,12 +32,15 @@ class Extension:
self.status = '' self.status = ''
self.can_update = False self.can_update = False
self.is_builtin = is_builtin self.is_builtin = is_builtin
self.commit_hash = ''
self.commit_date = None
self.version = '' self.version = ''
self.branch = None
self.remote = None self.remote = None
self.have_info_from_repo = False self.have_info_from_repo = False
def read_info_from_repo(self): def read_info_from_repo(self):
if self.have_info_from_repo: if self.is_builtin or self.have_info_from_repo:
return return
self.have_info_from_repo = True self.have_info_from_repo = True
...@@ -56,10 +60,15 @@ class Extension: ...@@ -56,10 +60,15 @@ class Extension:
self.status = 'unknown' self.status = 'unknown'
self.remote = next(repo.remote().urls, None) self.remote = next(repo.remote().urls, None)
head = repo.head.commit head = repo.head.commit
ts = time.asctime(time.gmtime(repo.head.commit.committed_date)) self.commit_date = repo.head.commit.committed_date
self.version = f'{head.hexsha[:8]} ({ts})' ts = time.asctime(time.gmtime(self.commit_date))
if repo.active_branch:
except Exception: self.branch = repo.active_branch.name
self.commit_hash = head.hexsha
self.version = f'{self.commit_hash[:8]} ({ts})'
except Exception as ex:
print(f"Failed reading extension data from Git repository ({self.name}): {ex}", file=sys.stderr)
self.remote = None self.remote = None
def list_files(self, subdir, extension): def list_files(self, subdir, extension):
...@@ -82,18 +91,30 @@ class Extension: ...@@ -82,18 +91,30 @@ class Extension:
for fetch in repo.remote().fetch(dry_run=True): for fetch in repo.remote().fetch(dry_run=True):
if fetch.flags != fetch.HEAD_UPTODATE: if fetch.flags != fetch.HEAD_UPTODATE:
self.can_update = True 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 return
except Exception:
self.can_update = False
self.status = "unknown (remote error)"
return
self.can_update = False self.can_update = False
self.status = "latest" self.status = "latest"
def fetch_and_reset_hard(self): def fetch_and_reset_hard(self, commit='origin'):
repo = git.Repo(self.path) repo = git.Repo(self.path)
# Fix: `error: Your local changes to the following files would be overwritten by merge`, # 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. # because WSL2 Docker set 755 file permissions instead of 644, this results to the error.
repo.git.fetch(all=True) 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(): def list_extensions():
......
modules/extra_networks_hypernet.py
View file @ 73d95645
...@@ -9,7 +9,7 @@ class ExtraNetworkHypernet(extra_networks.ExtraNetwork): ...@@ -9,7 +9,7 @@ class ExtraNetworkHypernet(extra_networks.ExtraNetwork):
def activate(self, p, params_list): def activate(self, p, params_list):
additional = shared.opts.sd_hypernetwork 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] 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])) params_list.append(extra_networks.ExtraNetworkParams(items=[additional, shared.opts.extra_networks_default_multiplier]))
......
modules/extras.py
View file @ 73d95645
import os import os
import re import re
import shutil import shutil
import json
import torch import torch
...@@ -71,7 +72,7 @@ def to_half(tensor, enable): ...@@ -71,7 +72,7 @@ def to_half(tensor, enable):
return tensor 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.begin()
shared.state.job = 'model-merge' shared.state.job = 'model-merge'
...@@ -241,13 +242,54 @@ def run_modelmerger(id_task, primary_model_name, secondary_model_name, tertiary_ ...@@ -241,13 +242,54 @@ def run_modelmerger(id_task, primary_model_name, secondary_model_name, tertiary_
shared.state.textinfo = "Saving" shared.state.textinfo = "Saving"
print(f"Saving to {output_modelname}...") 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) _, extension = os.path.splitext(output_modelname)
if extension.lower() == ".safetensors": 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: else:
torch.save(theta_0, output_modelname) torch.save(theta_0, output_modelname)
sd_models.list_models() 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) create_config(output_modelname, config_source, primary_model_info, secondary_model_info, tertiary_model_info)
......
modules/generation_parameters_copypaste.py
View file @ 73d95645
...@@ -284,6 +284,10 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model ...@@ -284,6 +284,10 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model
restore_old_hires_fix_params(res) 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 return res
...@@ -304,6 +308,8 @@ infotext_to_setting_name_mapping = [ ...@@ -304,6 +308,8 @@ infotext_to_setting_name_mapping = [
('UniPC skip type', 'uni_pc_skip_type'), ('UniPC skip type', 'uni_pc_skip_type'),
('UniPC order', 'uni_pc_order'), ('UniPC order', 'uni_pc_order'),
('UniPC lower order final', 'uni_pc_lower_order_final'), ('UniPC lower order final', 'uni_pc_lower_order_final'),
('RNG', 'randn_source'),
('NGMS', 's_min_uncond'),
] ]
......
modules/images.py
View file @ 73d95645
...@@ -318,6 +318,7 @@ re_nonletters = re.compile(r'[\s' + string.punctuation + ']+') ...@@ -318,6 +318,7 @@ re_nonletters = re.compile(r'[\s' + string.punctuation + ']+')
re_pattern = re.compile(r"(.*?)(?:\[([^\[\]]+)\]|$)") re_pattern = re.compile(r"(.*?)(?:\[([^\[\]]+)\]|$)")
re_pattern_arg = re.compile(r"(.*)<([^>]*)>$") re_pattern_arg = re.compile(r"(.*)<([^>]*)>$")
max_filename_part_length = 128 max_filename_part_length = 128
NOTHING_AND_SKIP_PREVIOUS_TEXT = object()
def sanitize_filename_part(text, replace_spaces=True): def sanitize_filename_part(text, replace_spaces=True):
...@@ -352,6 +353,11 @@ class FilenameGenerator: ...@@ -352,6 +353,11 @@ class FilenameGenerator:
'prompt_no_styles': lambda self: self.prompt_no_style(), 'prompt_no_styles': lambda self: self.prompt_no_style(),
'prompt_spaces': lambda self: sanitize_filename_part(self.prompt, replace_spaces=False), 'prompt_spaces': lambda self: sanitize_filename_part(self.prompt, replace_spaces=False),
'prompt_words': lambda self: self.prompt_words(), '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"],
'denoising': lambda self: self.p.denoising_strength if self.p and self.p.denoising_strength else NOTHING_AND_SKIP_PREVIOUS_TEXT,
} }
default_time_format = '%Y%m%d%H%M%S' default_time_format = '%Y%m%d%H%M%S'
...@@ -360,6 +366,22 @@ class FilenameGenerator: ...@@ -360,6 +366,22 @@ class FilenameGenerator:
self.seed = seed self.seed = seed
self.prompt = prompt self.prompt = prompt
self.image = image 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): def prompt_no_style(self):
if self.p is None or self.prompt is None: if self.p is None or self.prompt is None:
...@@ -403,9 +425,9 @@ class FilenameGenerator: ...@@ -403,9 +425,9 @@ class FilenameGenerator:
for m in re_pattern.finditer(x): for m in re_pattern.finditer(x):
text, pattern = m.groups() text, pattern = m.groups()
res += text
if pattern is None: if pattern is None:
res += text
continue continue
pattern_args = [] pattern_args = []
...@@ -426,11 +448,13 @@ class FilenameGenerator: ...@@ -426,11 +448,13 @@ class FilenameGenerator:
print(f"Error adding [{pattern}] to filename", file=sys.stderr) print(f"Error adding [{pattern}] to filename", file=sys.stderr)
print(traceback.format_exc(), file=sys.stderr) print(traceback.format_exc(), file=sys.stderr)
if replacement is not None: if replacement == NOTHING_AND_SKIP_PREVIOUS_TEXT:
res += str(replacement) continue
elif replacement is not None:
res += text + str(replacement)
continue continue
res += f'[{pattern}]' res += f'{text}[{pattern}]'
return res return res
......
modules/img2img.py
View file @ 73d95645
...@@ -4,7 +4,7 @@ import sys ...@@ -4,7 +4,7 @@ import sys
import traceback import traceback
import numpy as np 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 import devices, sd_samplers
from modules.generation_parameters_copypaste import create_override_settings_dict 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): ...@@ -46,7 +46,10 @@ def process_batch(p, input_dir, output_dir, inpaint_mask_dir, args):
if state.interrupted: if state.interrupted:
break break
img = Image.open(image) try:
img = Image.open(image)
except UnidentifiedImageError:
continue
# Use the EXIF orientation of photos taken by smartphones. # Use the EXIF orientation of photos taken by smartphones.
img = ImageOps.exif_transpose(img) img = ImageOps.exif_transpose(img)
p.init_images = [img] * p.batch_size p.init_images = [img] * p.batch_size
...@@ -78,7 +81,7 @@ def process_batch(p, input_dir, output_dir, inpaint_mask_dir, args): ...@@ -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)) 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) override_settings = create_override_settings_dict(override_settings_texts)
is_batch = mode == 5 is_batch = mode == 5
...@@ -114,6 +117,12 @@ def img2img(id_task: str, mode: int, prompt: str, negative_prompt: str, prompt_s ...@@ -114,6 +117,12 @@ def img2img(id_task: str, mode: int, prompt: str, negative_prompt: str, prompt_s
if image is not None: if image is not None:
image = ImageOps.exif_transpose(image) 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]' assert 0. <= denoising_strength <= 1., 'can only work with strength in [0.0, 1.0]'
p = StableDiffusionProcessingImg2Img( p = StableDiffusionProcessingImg2Img(
...@@ -151,7 +160,7 @@ def img2img(id_task: str, mode: int, prompt: str, negative_prompt: str, prompt_s ...@@ -151,7 +160,7 @@ def img2img(id_task: str, mode: int, prompt: str, negative_prompt: str, prompt_s
override_settings=override_settings, override_settings=override_settings,
) )
p.scripts = modules.scripts.scripts_txt2img p.scripts = modules.scripts.scripts_img2img
p.script_args = args p.script_args = args
if shared.cmd_opts.enable_console_prompts: if shared.cmd_opts.enable_console_prompts:
......
modules/interrogate.py
View file @ 73d95645
...@@ -32,7 +32,7 @@ def download_default_clip_interrogate_categories(content_dir): ...@@ -32,7 +32,7 @@ def download_default_clip_interrogate_categories(content_dir):
category_types = ["artists", "flavors", "mediums", "movements"] category_types = ["artists", "flavors", "mediums", "movements"]
try: try:
os.makedirs(tmpdir) os.makedirs(tmpdir, exist_ok=True)
for category_type in category_types: 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")) 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) os.rename(tmpdir, content_dir)
...@@ -41,7 +41,7 @@ def download_default_clip_interrogate_categories(content_dir): ...@@ -41,7 +41,7 @@ def download_default_clip_interrogate_categories(content_dir):
errors.display(e, "downloading default CLIP interrogate categories") errors.display(e, "downloading default CLIP interrogate categories")
finally: finally:
if os.path.exists(tmpdir): if os.path.exists(tmpdir):
os.remove(tmpdir) os.removedirs(tmpdir)
class InterrogateModels: class InterrogateModels:
......
modules/ngrok.py
View file @ 73d95645
...@@ -13,6 +13,18 @@ def connect(token, port, region): ...@@ -13,6 +13,18 @@ def connect(token, port, region):
config = conf.PyngrokConfig( config = conf.PyngrokConfig(
auth_token=token, region=region 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: try:
if account is None: if account is None:
public_url = ngrok.connect(port, pyngrok_config=config, bind_tls=True).public_url public_url = ngrok.connect(port, pyngrok_config=config, bind_tls=True).public_url
......
modules/paths_internal.py
View file @ 73d95645
...@@ -20,3 +20,4 @@ data_path = cmd_opts_pre.data_dir ...@@ -20,3 +20,4 @@ data_path = cmd_opts_pre.data_dir
models_path = os.path.join(data_path, "models") models_path = os.path.join(data_path, "models")
extensions_dir = os.path.join(data_path, "extensions") extensions_dir = os.path.join(data_path, "extensions")
extensions_builtin_dir = os.path.join(script_path, "extensions-builtin") extensions_builtin_dir = os.path.join(script_path, "extensions-builtin")
config_states_dir = os.path.join(script_path, "config_states")
modules/postprocessing.py
View file @ 73d95645
...@@ -18,9 +18,14 @@ def run_postprocessing(extras_mode, image, image_folder, input_dir, output_dir, ...@@ -18,9 +18,14 @@ def run_postprocessing(extras_mode, image, image_folder, input_dir, output_dir,
if extras_mode == 1: if extras_mode == 1:
for img in image_folder: 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_data.append(image)
image_names.append(os.path.splitext(img.orig_name)[0]) image_names.append(fn)
elif extras_mode == 2: elif extras_mode == 2:
assert not shared.cmd_opts.hide_ui_dir_config, '--hide-ui-dir-config option must be disabled' assert not shared.cmd_opts.hide_ui_dir_config, '--hide-ui-dir-config option must be disabled'
assert input_dir, 'input directory not selected' assert input_dir, 'input directory not selected'
......
modules/processing.py
View file @ 73d95645
...@@ -3,6 +3,7 @@ import math ...@@ -3,6 +3,7 @@ import math
import os import os
import sys import sys
import warnings import warnings
import hashlib
import torch import torch
import numpy as np import numpy as np
...@@ -105,7 +106,7 @@ class StableDiffusionProcessing: ...@@ -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 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: if sampler_index is not None:
print("sampler_index argument for StableDiffusionProcessing does not do anything; use sampler_name", file=sys.stderr) print("sampler_index argument for StableDiffusionProcessing does not do anything; use sampler_name", file=sys.stderr)
...@@ -140,6 +141,7 @@ class StableDiffusionProcessing: ...@@ -140,6 +141,7 @@ class StableDiffusionProcessing:
self.denoising_strength: float = denoising_strength self.denoising_strength: float = denoising_strength
self.sampler_noise_scheduler_override = None self.sampler_noise_scheduler_override = None
self.ddim_discretize = ddim_discretize or opts.ddim_discretize 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_churn = s_churn or opts.s_churn
self.s_tmin = s_tmin or opts.s_tmin self.s_tmin = s_tmin or opts.s_tmin
self.s_tmax = s_tmax or float('inf') # not representable as a standard ui option self.s_tmax = s_tmax or float('inf') # not representable as a standard ui option
...@@ -162,6 +164,8 @@ class StableDiffusionProcessing: ...@@ -162,6 +164,8 @@ class StableDiffusionProcessing:
self.all_seeds = None self.all_seeds = None
self.all_subseeds = None self.all_subseeds = None
self.iteration = 0 self.iteration = 0
self.is_hr_pass = False
@property @property
def sd_model(self): def sd_model(self):
...@@ -476,6 +480,9 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter ...@@ -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, "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, "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, "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) generation_params.update(p.extra_generation_params)
...@@ -491,6 +498,11 @@ def process_images(p: StableDiffusionProcessing) -> Processed: ...@@ -491,6 +498,11 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
stored_opts = {k: opts.data[k] for k in p.override_settings.keys()} stored_opts = {k: opts.data[k] for k in p.override_settings.keys()}
try: try:
# if no checkpoint override or the override checkpoint can't be found, remove override entry and load opts checkpoint
if sd_models.checkpoint_alisases.get(p.override_settings.get('sd_model_checkpoint')) is None:
p.override_settings.pop('sd_model_checkpoint', None)
sd_models.reload_model_weights()
for k, v in p.override_settings.items(): for k, v in p.override_settings.items():
setattr(opts, k, v) setattr(opts, k, v)
...@@ -507,8 +519,6 @@ def process_images(p: StableDiffusionProcessing) -> Processed: ...@@ -507,8 +519,6 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
if p.override_settings_restore_afterwards: if p.override_settings_restore_afterwards:
for k, v in stored_opts.items(): for k, v in stored_opts.items():
setattr(opts, k, v) setattr(opts, k, v)
if k == 'sd_model_checkpoint':
sd_models.reload_model_weights()
if k == 'sd_vae': if k == 'sd_vae':
sd_vae.reload_vae_weights() sd_vae.reload_vae_weights()
...@@ -639,8 +649,14 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed: ...@@ -639,8 +649,14 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
processed = Processed(p, [], p.seed, "") processed = Processed(p, [], p.seed, "")
file.write(processed.infotext(p, 0)) file.write(processed.infotext(p, 0))
uc = get_conds_with_caching(prompt_parser.get_learned_conditioning, negative_prompts, p.steps, cached_uc) step_multiplier = 1
c = get_conds_with_caching(prompt_parser.get_multicond_learned_conditioning, prompts, p.steps, cached_c) 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: if len(model_hijack.comments) > 0:
for comment in model_hijack.comments: for comment in model_hijack.comments:
...@@ -670,6 +686,8 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed: ...@@ -670,6 +686,8 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
p.scripts.postprocess_batch(p, x_samples_ddim, batch_number=n) p.scripts.postprocess_batch(p, x_samples_ddim, batch_number=n)
for i, x_sample in enumerate(x_samples_ddim): 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 = 255. * np.moveaxis(x_sample.cpu().numpy(), 0, 2)
x_sample = x_sample.astype(np.uint8) x_sample = x_sample.astype(np.uint8)
...@@ -706,9 +724,9 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed: ...@@ -706,9 +724,9 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
image.info["parameters"] = text image.info["parameters"] = text
output_images.append(image) 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 = 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: 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") 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 +736,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed: ...@@ -718,7 +736,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
if opts.return_mask: if opts.return_mask:
output_images.append(image_mask) output_images.append(image_mask)
if opts.return_mask_composite: if opts.return_mask_composite:
output_images.append(image_mask_composite) output_images.append(image_mask_composite)
...@@ -871,6 +889,8 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): ...@@ -871,6 +889,8 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
if not self.enable_hr: if not self.enable_hr:
return samples return samples
self.is_hr_pass = True
target_width = self.hr_upscale_to_x target_width = self.hr_upscale_to_x
target_height = self.hr_upscale_to_y target_height = self.hr_upscale_to_y
...@@ -940,6 +960,8 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): ...@@ -940,6 +960,8 @@ 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) 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 return samples
...@@ -1007,6 +1029,12 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing): ...@@ -1007,6 +1029,12 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing):
self.color_corrections = [] self.color_corrections = []
imgs = [] imgs = []
for img in self.init_images: 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) image = images.flatten(img, opts.img2img_background_color)
if crop_region is None and self.resize_mode != 3: if crop_region is None and self.resize_mode != 3:
......
modules/progress.py
View file @ 73d95645
...@@ -13,6 +13,8 @@ import modules.shared as shared ...@@ -13,6 +13,8 @@ import modules.shared as shared
current_task = None current_task = None
pending_tasks = {} pending_tasks = {}
finished_tasks = [] finished_tasks = []
recorded_results = []
recorded_results_limit = 2
def start_task(id_task): def start_task(id_task):
...@@ -33,6 +35,12 @@ def finish_task(id_task): ...@@ -33,6 +35,12 @@ def finish_task(id_task):
finished_tasks.pop(0) finished_tasks.pop(0)
def record_results(id_task, res):
recorded_results.append((id_task, res))
if len(recorded_results) > recorded_results_limit:
recorded_results.pop(0)
def add_task_to_queue(id_job): def add_task_to_queue(id_job):
pending_tasks[id_job] = time.time() pending_tasks[id_job] = time.time()
...@@ -97,3 +105,13 @@ def progressapi(req: ProgressRequest): ...@@ -97,3 +105,13 @@ def progressapi(req: ProgressRequest):
return ProgressResponse(active=active, queued=queued, completed=completed, progress=progress, eta=eta, live_preview=live_preview, id_live_preview=id_live_preview, textinfo=shared.state.textinfo) return ProgressResponse(active=active, queued=queued, completed=completed, progress=progress, eta=eta, live_preview=live_preview, id_live_preview=id_live_preview, textinfo=shared.state.textinfo)
def restore_progress(id_task):
while id_task == current_task or id_task in pending_tasks:
time.sleep(0.1)
res = next(iter([x[1] for x in recorded_results if id_task == x[0]]), None)
if res is not None:
return res
return gr.update(), gr.update(), gr.update(), f"Couldn't restore progress for {id_task}: results either have been discarded or never were obtained"
modules/realesrgan_model.py
View file @ 73d95645
...@@ -9,7 +9,7 @@ from realesrgan import RealESRGANer ...@@ -9,7 +9,7 @@ from realesrgan import RealESRGANer
from modules.upscaler import Upscaler, UpscalerData from modules.upscaler import Upscaler, UpscalerData
from modules.shared import cmd_opts, opts from modules.shared import cmd_opts, opts
from modules import modelloader
class UpscalerRealESRGAN(Upscaler): class UpscalerRealESRGAN(Upscaler):
def __init__(self, path): def __init__(self, path):
...@@ -23,7 +23,15 @@ class UpscalerRealESRGAN(Upscaler): ...@@ -23,7 +23,15 @@ class UpscalerRealESRGAN(Upscaler):
self.enable = True self.enable = True
self.scalers = [] self.scalers = []
scalers = self.load_models(path) scalers = self.load_models(path)
local_model_paths = self.find_models(ext_filter=[".pth"])
for scaler in scalers: 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: if scaler.name in opts.realesrgan_enabled_models:
self.scalers.append(scaler) self.scalers.append(scaler)
...@@ -64,7 +72,9 @@ class UpscalerRealESRGAN(Upscaler): ...@@ -64,7 +72,9 @@ class UpscalerRealESRGAN(Upscaler):
print(f"Unable to find model info: {path}") print(f"Unable to find model info: {path}")
return None 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 return info
except Exception as e: except Exception as e:
print(f"Error making Real-ESRGAN models list: {e}", file=sys.stderr) print(f"Error making Real-ESRGAN models list: {e}", file=sys.stderr)
......
modules/safe.py
View file @ 73d95645
# this code is adapted from the script contributed by anon from /h/ # this code is adapted from the script contributed by anon from /h/
import io
import pickle import pickle
import collections import collections
import sys import sys
...@@ -12,11 +11,9 @@ import _codecs ...@@ -12,11 +11,9 @@ import _codecs
import zipfile import zipfile
import re import re
# PyTorch 1.13 and later have _TypedStorage renamed to TypedStorage # PyTorch 1.13 and later have _TypedStorage renamed to TypedStorage
TypedStorage = torch.storage.TypedStorage if hasattr(torch.storage, 'TypedStorage') else torch.storage._TypedStorage TypedStorage = torch.storage.TypedStorage if hasattr(torch.storage, 'TypedStorage') else torch.storage._TypedStorage
def encode(*args): def encode(*args):
out = _codecs.encode(*args) out = _codecs.encode(*args)
return out return out
...@@ -27,7 +24,11 @@ class RestrictedUnpickler(pickle.Unpickler): ...@@ -27,7 +24,11 @@ class RestrictedUnpickler(pickle.Unpickler):
def persistent_load(self, saved_id): def persistent_load(self, saved_id):
assert saved_id[0] == 'storage' assert saved_id[0] == 'storage'
return TypedStorage()
try:
return TypedStorage(_internal=True)
except TypeError:
return TypedStorage() # PyTorch before 2.0 does not have the _internal argument
def find_class(self, module, name): def find_class(self, module, name):
if self.extra_handler is not None: if self.extra_handler is not None:
......
modules/script_callbacks.py
View file @ 73d95645
...@@ -93,6 +93,7 @@ callback_map = dict( ...@@ -93,6 +93,7 @@ callback_map = dict(
callbacks_infotext_pasted=[], callbacks_infotext_pasted=[],
callbacks_script_unloaded=[], callbacks_script_unloaded=[],
callbacks_before_ui=[], callbacks_before_ui=[],
callbacks_on_reload=[],
) )
...@@ -109,6 +110,14 @@ def app_started_callback(demo: Optional[Blocks], app: FastAPI): ...@@ -109,6 +110,14 @@ def app_started_callback(demo: Optional[Blocks], app: FastAPI):
report_exception(c, 'app_started_callback') 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): def model_loaded_callback(sd_model):
for c in callback_map['callbacks_model_loaded']: for c in callback_map['callbacks_model_loaded']:
try: try:
...@@ -254,6 +263,11 @@ def on_app_started(callback): ...@@ -254,6 +263,11 @@ def on_app_started(callback):
add_callback(callback_map['callbacks_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): def on_model_loaded(callback):
"""register a function to be called when the stable diffusion model is created; the model is """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. """ passed as an argument; this function is also called when the script is reloaded. """
......
modules/sd_models.py
View file @ 73d95645
...@@ -2,6 +2,8 @@ import collections ...@@ -2,6 +2,8 @@ import collections
import os.path import os.path
import sys import sys
import gc import gc
import threading
import torch import torch
import re import re
import safetensors.torch import safetensors.torch
...@@ -52,6 +54,15 @@ class CheckpointInfo: ...@@ -52,6 +54,15 @@ 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.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): def register(self):
checkpoints_list[self.title] = self checkpoints_list[self.title] = self
for id in self.ids: for id in self.ids:
...@@ -395,13 +406,39 @@ def repair_config(sd_config): ...@@ -395,13 +406,39 @@ def repair_config(sd_config):
sd1_clip_weight = 'cond_stage_model.transformer.text_model.embeddings.token_embedding.weight' sd1_clip_weight = 'cond_stage_model.transformer.text_model.embeddings.token_embedding.weight'
sd2_clip_weight = 'cond_stage_model.model.transformer.resblocks.0.attn.in_proj_weight' sd2_clip_weight = 'cond_stage_model.model.transformer.resblocks.0.attn.in_proj_weight'
def load_model(checkpoint_info=None, already_loaded_state_dict=None, time_taken_to_load_state_dict=None):
class SdModelData:
def __init__(self):
self.sd_model = None
self.lock = threading.Lock()
def get_sd_model(self):
if self.sd_model is None:
with self.lock:
try:
load_model()
except Exception as e:
errors.display(e, "loading stable diffusion model")
print("", file=sys.stderr)
print("Stable diffusion model failed to load", file=sys.stderr)
self.sd_model = None
return self.sd_model
def set_sd_model(self, v):
self.sd_model = v
model_data = SdModelData()
def load_model(checkpoint_info=None, already_loaded_state_dict=None):
from modules import lowvram, sd_hijack from modules import lowvram, sd_hijack
checkpoint_info = checkpoint_info or select_checkpoint() checkpoint_info = checkpoint_info or select_checkpoint()
if shared.sd_model: if model_data.sd_model:
sd_hijack.model_hijack.undo_hijack(shared.sd_model) sd_hijack.model_hijack.undo_hijack(model_data.sd_model)
shared.sd_model = None model_data.sd_model = None
gc.collect() gc.collect()
devices.torch_gc() devices.torch_gc()
...@@ -455,7 +492,7 @@ def load_model(checkpoint_info=None, already_loaded_state_dict=None, time_taken_ ...@@ -455,7 +492,7 @@ def load_model(checkpoint_info=None, already_loaded_state_dict=None, time_taken_
timer.record("hijack") timer.record("hijack")
sd_model.eval() sd_model.eval()
shared.sd_model = sd_model model_data.sd_model = sd_model
sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings(force_reload=True) # Reload embeddings after model load as they may or may not fit the model sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings(force_reload=True) # Reload embeddings after model load as they may or may not fit the model
...@@ -475,7 +512,7 @@ def reload_model_weights(sd_model=None, info=None): ...@@ -475,7 +512,7 @@ def reload_model_weights(sd_model=None, info=None):
checkpoint_info = info or select_checkpoint() checkpoint_info = info or select_checkpoint()
if not sd_model: if not sd_model:
sd_model = shared.sd_model sd_model = model_data.sd_model
if sd_model is None: # previous model load failed if sd_model is None: # previous model load failed
current_checkpoint_info = None current_checkpoint_info = None
...@@ -503,7 +540,7 @@ def reload_model_weights(sd_model=None, info=None): ...@@ -503,7 +540,7 @@ def reload_model_weights(sd_model=None, info=None):
del sd_model del sd_model
checkpoints_loaded.clear() checkpoints_loaded.clear()
load_model(checkpoint_info, already_loaded_state_dict=state_dict) load_model(checkpoint_info, already_loaded_state_dict=state_dict)
return shared.sd_model return model_data.sd_model
try: try:
load_model_weights(sd_model, checkpoint_info, state_dict, timer) load_model_weights(sd_model, checkpoint_info, state_dict, timer)
...@@ -526,17 +563,15 @@ def reload_model_weights(sd_model=None, info=None): ...@@ -526,17 +563,15 @@ def reload_model_weights(sd_model=None, info=None):
return sd_model return sd_model
def unload_model_weights(sd_model=None, info=None): def unload_model_weights(sd_model=None, info=None):
from modules import lowvram, devices, sd_hijack from modules import lowvram, devices, sd_hijack
timer = Timer() timer = Timer()
if shared.sd_model: if model_data.sd_model:
model_data.sd_model.to(devices.cpu)
# shared.sd_model.cond_stage_model.to(devices.cpu) sd_hijack.model_hijack.undo_hijack(model_data.sd_model)
# shared.sd_model.first_stage_model.to(devices.cpu) model_data.sd_model = None
shared.sd_model.to(devices.cpu)
sd_hijack.model_hijack.undo_hijack(shared.sd_model)
shared.sd_model = None
sd_model = None sd_model = None
gc.collect() gc.collect()
devices.torch_gc() devices.torch_gc()
...@@ -544,4 +579,4 @@ def unload_model_weights(sd_model=None, info=None): ...@@ -544,4 +579,4 @@ def unload_model_weights(sd_model=None, info=None):
print(f"Unloaded weights {timer.summary()}.") print(f"Unloaded weights {timer.summary()}.")
return sd_model return sd_model
\ No newline at end of file
modules/sd_samplers_common.py
View file @ 73d95645
...@@ -60,3 +60,13 @@ def store_latent(decoded): ...@@ -60,3 +60,13 @@ def store_latent(decoded):
class InterruptedException(BaseException): class InterruptedException(BaseException):
pass 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
View file @ 73d95645
...@@ -76,7 +76,7 @@ class CFGDenoiser(torch.nn.Module): ...@@ -76,7 +76,7 @@ class CFGDenoiser(torch.nn.Module):
return denoised 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: if state.interrupted or state.skipped:
raise sd_samplers_common.InterruptedException raise sd_samplers_common.InterruptedException
...@@ -115,12 +115,21 @@ class CFGDenoiser(torch.nn.Module): ...@@ -115,12 +115,21 @@ class CFGDenoiser(torch.nn.Module):
sigma_in = denoiser_params.sigma sigma_in = denoiser_params.sigma
tensor = denoiser_params.text_cond tensor = denoiser_params.text_cond
uncond = denoiser_params.text_uncond uncond = denoiser_params.text_uncond
skip_uncond = False
if tensor.shape[1] == uncond.shape[1]: # alternating uncond allows for higher thresholds without the quality loss normally expected from raising it
if not is_edit_model: if self.step % 2 and s_min_uncond > 0 and sigma[0] < s_min_uncond and not is_edit_model:
cond_in = torch.cat([tensor, uncond]) skip_uncond = True
else: 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]) 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: if shared.batch_cond_uncond:
x_out = self.inner_model(x_in, sigma_in, cond=make_condition_dict([cond_in], image_cond_in)) 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): ...@@ -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[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) denoised_params = CFGDenoisedParams(x_out, state.sampling_step, state.sampling_steps)
cfg_denoised_callback(denoised_params) cfg_denoised_callback(denoised_params)
...@@ -152,20 +167,21 @@ class CFGDenoiser(torch.nn.Module): ...@@ -152,20 +167,21 @@ class CFGDenoiser(torch.nn.Module):
devices.test_for_nans(x_out, "unet") devices.test_for_nans(x_out, "unet")
if opts.live_preview_content == "Prompt": 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": elif opts.live_preview_content == "Negative prompt":
sd_samplers_common.store_latent(x_out[-uncond.shape[0]:]) sd_samplers_common.store_latent(x_out[-uncond.shape[0]:])
if not is_edit_model: if is_edit_model:
denoised = self.combine_denoised(x_out, conds_list, uncond, cond_scale)
else:
denoised = self.combine_denoised_for_edit_model(x_out, cond_scale) 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: if self.mask is not None:
denoised = self.init_latent * self.mask + self.nmask * denoised denoised = self.init_latent * self.mask + self.nmask * denoised
self.step += 1 self.step += 1
return denoised return denoised
...@@ -190,7 +206,7 @@ class TorchHijack: ...@@ -190,7 +206,7 @@ class TorchHijack:
if noise.shape == x.shape: if noise.shape == x.shape:
return noise 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) return torch.randn_like(x, device=devices.cpu).to(x.device)
else: else:
return torch.randn_like(x) return torch.randn_like(x)
...@@ -210,6 +226,7 @@ class KDiffusionSampler: ...@@ -210,6 +226,7 @@ class KDiffusionSampler:
self.eta = None self.eta = None
self.config = None self.config = None
self.last_latent = None self.last_latent = None
self.s_min_uncond = None
self.conditioning_key = sd_model.model.conditioning_key self.conditioning_key = sd_model.model.conditioning_key
...@@ -244,6 +261,7 @@ class KDiffusionSampler: ...@@ -244,6 +261,7 @@ class KDiffusionSampler:
self.model_wrap_cfg.step = 0 self.model_wrap_cfg.step = 0
self.model_wrap_cfg.image_cfg_scale = getattr(p, 'image_cfg_scale', None) 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.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 []) k_diffusion.sampling.torch = TorchHijack(self.sampler_noises if self.sampler_noises is not None else [])
...@@ -326,6 +344,7 @@ class KDiffusionSampler: ...@@ -326,6 +344,7 @@ class KDiffusionSampler:
'image_cond': image_conditioning, 'image_cond': image_conditioning,
'uncond': unconditional_conditioning, 'uncond': unconditional_conditioning,
'cond_scale': p.cfg_scale, '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)) 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: ...@@ -359,7 +378,8 @@ class KDiffusionSampler:
'cond': conditioning, 'cond': conditioning,
'image_cond': image_conditioning, 'image_cond': image_conditioning,
'uncond': unconditional_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)) }, disable=False, callback=self.callback_state, **extra_params_kwargs))
return samples return samples
......
modules/shared.py
View file @ 73d95645
This diff is collapsed.
modules/styles.py
View file @ 73d95645
...@@ -72,16 +72,14 @@ class StyleDatabase: ...@@ -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]) 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: def save_styles(self, path: str) -> None:
# Write to temporary file first, so we don't nuke the file if something goes wrong # Always keep a backup file around
fd, temp_path = tempfile.mkstemp(".csv") 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: 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, # _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() # and collections.NamedTuple has explicit documentation for accessing _fields. Same goes for _asdict()
writer = csv.DictWriter(file, fieldnames=PromptStyle._fields) writer = csv.DictWriter(file, fieldnames=PromptStyle._fields)
writer.writeheader() writer.writeheader()
writer.writerows(style._asdict() for k, style in self.styles.items()) 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
View file @ 73d95645
...@@ -11,7 +11,7 @@ from modules.shared import opts, cmd_opts ...@@ -11,7 +11,7 @@ from modules.shared import opts, cmd_opts
from modules.textual_inversion import autocrop 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: try:
if process_caption: if process_caption:
shared.interrogator.load() shared.interrogator.load()
...@@ -19,7 +19,7 @@ def preprocess(id_task, process_src, process_dst, process_width, process_height, ...@@ -19,7 +19,7 @@ def preprocess(id_task, process_src, process_dst, process_width, process_height,
if process_caption_deepbooru: if process_caption_deepbooru:
deepbooru.model.start() 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: finally:
...@@ -131,7 +131,7 @@ def multicrop_pic(image: Image, mindim, maxdim, minarea, maxarea, objective, thr ...@@ -131,7 +131,7 @@ def multicrop_pic(image: Image, mindim, maxdim, minarea, maxarea, objective, thr
return wh and center_crop(image, *wh) 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 width = process_width
height = process_height height = process_height
src = os.path.abspath(process_src) src = os.path.abspath(process_src)
...@@ -161,7 +161,9 @@ def preprocess_work(process_src, process_dst, process_width, process_height, pre ...@@ -161,7 +161,9 @@ def preprocess_work(process_src, process_dst, process_width, process_height, pre
params.subindex = 0 params.subindex = 0
filename = os.path.join(src, imagefile) filename = os.path.join(src, imagefile)
try: try:
img = Image.open(filename).convert("RGB") img = Image.open(filename)
img = ImageOps.exif_transpose(img)
img = img.convert("RGB")
except Exception: except Exception:
continue continue
...@@ -223,6 +225,10 @@ def preprocess_work(process_src, process_dst, process_width, process_height, pre ...@@ -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)") print(f"skipped {img.width}x{img.height} image {filename} (can't find suitable size within error threshold)")
process_default_resize = False 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: if process_default_resize:
img = images.resize_image(1, img, width, height) img = images.resize_image(1, img, width, height)
save_pic(img, index, params, existing_caption=existing_caption) save_pic(img, index, params, existing_caption=existing_caption)
......
modules/textual_inversion/textual_inversion.py
View file @ 73d95645
...@@ -233,6 +233,12 @@ class EmbeddingDatabase: ...@@ -233,6 +233,12 @@ class EmbeddingDatabase:
self.load_from_dir(embdir) self.load_from_dir(embdir)
embdir.update() 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())) displayed_embeddings = (tuple(self.word_embeddings.keys()), tuple(self.skipped_embeddings.keys()))
if self.previously_displayed_embeddings != displayed_embeddings: if self.previously_displayed_embeddings != displayed_embeddings:
self.previously_displayed_embeddings = displayed_embeddings self.previously_displayed_embeddings = displayed_embeddings
......
modules/ui.py
View file @ 73d95645
This diff is collapsed.
modules/ui_common.py
View file @ 73d95645
...@@ -125,7 +125,7 @@ Requested path was: {f} ...@@ -125,7 +125,7 @@ Requested path was: {f}
with gr.Column(variant='panel', elem_id=f"{tabname}_results"): with gr.Column(variant='panel', elem_id=f"{tabname}_results"):
with gr.Group(elem_id=f"{tabname}_gallery_container"): 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 generation_info = None
with gr.Column(): with gr.Column():
......
modules/ui_components.py
View file @ 73d95645
...@@ -62,3 +62,13 @@ class DropdownMulti(FormComponent, gr.Dropdown): ...@@ -62,3 +62,13 @@ class DropdownMulti(FormComponent, gr.Dropdown):
def get_block_name(self): def get_block_name(self):
return "dropdown" 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
View file @ 73d95645
This diff is collapsed.
modules/ui_extra_networks.py
View file @ 73d95645
...@@ -241,7 +241,7 @@ def create_ui(container, button, tabname): ...@@ -241,7 +241,7 @@ def create_ui(container, button, tabname):
with gr.Tabs(elem_id=tabname+"_extra_tabs") as tabs: with gr.Tabs(elem_id=tabname+"_extra_tabs") as tabs:
for page in ui.stored_extra_pages: 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)) page_elem = gr.HTML(page.create_html(ui.tabname))
ui.pages.append(page_elem) ui.pages.append(page_elem)
......
modules/ui_postprocessing.py
View file @ 73d95645
...@@ -9,13 +9,13 @@ def create_ui(): ...@@ -9,13 +9,13 @@ def create_ui():
with gr.Row().style(equal_height=False, variant='compact'): with gr.Row().style(equal_height=False, variant='compact'):
with gr.Column(variant='compact'): with gr.Column(variant='compact'):
with gr.Tabs(elem_id="mode_extras"): 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") 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: with gr.TabItem('Batch Process', id="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") 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_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") 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") show_extras_results = gr.Checkbox(label='Show result images', value=True, elem_id="extras_show_extras_results")
......
modules/ui_tempdir.py
View file @ 73d95645
...@@ -36,7 +36,7 @@ def save_pil_to_file(pil_image, dir=None): ...@@ -36,7 +36,7 @@ def save_pil_to_file(pil_image, dir=None):
if already_saved_as and os.path.isfile(already_saved_as): if already_saved_as and os.path.isfile(already_saved_as):
register_tmp_file(shared.demo, already_saved_as) register_tmp_file(shared.demo, already_saved_as)
file_obj = Savedfile(already_saved_as) file_obj = Savedfile(f"{already_saved_as}?{os.path.getmtime(already_saved_as)}")
return file_obj return file_obj
if shared.opts.temp_dir != "": if shared.opts.temp_dir != "":
......
requirements_versions.txt
View file @ 73d95645
blendmodes==2022 blendmodes==2022
transformers==4.25.1 transformers==4.25.1
accelerate==0.12.0 accelerate==0.18.0
basicsr==1.4.2 basicsr==1.4.2
gfpgan==1.3.8 gfpgan==1.3.8
gradio==3.23 gradio==3.28.1
numpy==1.23.3 numpy==1.23.5
Pillow==9.4.0 Pillow==9.4.0
realesrgan==0.3.0 realesrgan==0.3.0
torch torch
...@@ -25,6 +25,6 @@ lark==1.1.2 ...@@ -25,6 +25,6 @@ lark==1.1.2
inflection==0.5.1 inflection==0.5.1
GitPython==3.1.30 GitPython==3.1.30
torchsde==0.2.5 torchsde==0.2.5
safetensors==0.3.0 safetensors==0.3.1
httpcore<=0.15 httpcore<=0.15
fastapi==0.94.0 fastapi==0.94.0
script.js
View file @ 73d95645
...@@ -7,7 +7,7 @@ function gradioApp() { ...@@ -7,7 +7,7 @@ function gradioApp() {
} }
function get_uiCurrentTab() { function get_uiCurrentTab() {
return gradioApp().querySelector('#tabs button:not(.border-transparent)') return gradioApp().querySelector('#tabs button.selected')
} }
function get_uiCurrentTabContent() { function get_uiCurrentTabContent() {
......
scripts/custom_code.py
View file @ 73d95645
import modules.scripts as scripts import modules.scripts as scripts
import gradio as gr import gradio as gr
import ast
import copy
from modules.processing import Processed from modules.processing import Processed
from modules.shared import opts, cmd_opts, state from modules.shared import opts, cmd_opts, state
def convertExpr2Expression(expr):
expr.lineno = 0
expr.col_offset = 0
result = ast.Expression(expr.value, lineno=0, col_offset = 0)
return result
def exec_with_return(code, module):
"""
like exec() but can return values
https://stackoverflow.com/a/52361938/5862977
"""
code_ast = ast.parse(code)
init_ast = copy.deepcopy(code_ast)
init_ast.body = code_ast.body[:-1]
last_ast = copy.deepcopy(code_ast)
last_ast.body = code_ast.body[-1:]
exec(compile(init_ast, "<ast>", "exec"), module.__dict__)
if type(last_ast.body[0]) == ast.Expr:
return eval(compile(convertExpr2Expression(last_ast.body[0]), "<ast>", "eval"), module.__dict__)
else:
exec(compile(last_ast, "<ast>", "exec"), module.__dict__)
class Script(scripts.Script): class Script(scripts.Script):
def title(self): def title(self):
...@@ -13,12 +44,23 @@ class Script(scripts.Script): ...@@ -13,12 +44,23 @@ class Script(scripts.Script):
return cmd_opts.allow_code return cmd_opts.allow_code
def ui(self, is_img2img): def ui(self, is_img2img):
code = gr.Textbox(label="Python code", lines=1, elem_id=self.elem_id("code")) example = """from modules.processing import process_images
p.width = 768
p.height = 768
p.batch_size = 2
p.steps = 10
return process_images(p)
"""
return [code] code = gr.Code(value=example, language="python", label="Python code", elem_id=self.elem_id("code"))
indent_level = gr.Number(label='Indent level', value=2, precision=0, elem_id=self.elem_id("indent_level"))
return [code, indent_level]
def run(self, p, code): def run(self, p, code, indent_level):
assert cmd_opts.allow_code, '--allow-code option must be enabled' assert cmd_opts.allow_code, '--allow-code option must be enabled'
display_result_data = [[], -1, ""] display_result_data = [[], -1, ""]
...@@ -29,13 +71,20 @@ class Script(scripts.Script): ...@@ -29,13 +71,20 @@ class Script(scripts.Script):
display_result_data[2] = i display_result_data[2] = i
from types import ModuleType from types import ModuleType
compiled = compile(code, '', 'exec')
module = ModuleType("testmodule") module = ModuleType("testmodule")
module.__dict__.update(globals()) module.__dict__.update(globals())
module.p = p module.p = p
module.display = display module.display = display
exec(compiled, module.__dict__)
indent = " " * indent_level
indented = code.replace('\n', '\n' + indent)
body = f"""def __webuitemp__():
{indent}{indented}
__webuitemp__()"""
result = exec_with_return(body, module)
if isinstance(result, Processed):
return result
return Processed(p, *display_result_data) return Processed(p, *display_result_data)
\ No newline at end of file
scripts/outpainting_mk_2.py
View file @ 73d95645
...@@ -275,7 +275,7 @@ class Script(scripts.Script): ...@@ -275,7 +275,7 @@ class Script(scripts.Script):
if opts.samples_save: if opts.samples_save:
for img in all_processed_images: for img in all_processed_images:
images.save_image(img, p.outpath_samples, "", res.seed, p.prompt, opts.grid_format, info=res.info, p=p) images.save_image(img, p.outpath_samples, "", res.seed, p.prompt, opts.samples_format, info=res.info, p=p)
if opts.grid_save and not unwanted_grid_because_of_img_count: if opts.grid_save and not unwanted_grid_because_of_img_count:
images.save_image(combined_grid_image, p.outpath_grids, "grid", res.seed, p.prompt, opts.grid_format, info=res.info, short_filename=not opts.grid_extended_filename, grid=True, p=p) images.save_image(combined_grid_image, p.outpath_grids, "grid", res.seed, p.prompt, opts.grid_format, info=res.info, short_filename=not opts.grid_extended_filename, grid=True, p=p)
......
scripts/poor_mans_outpainting.py
View file @ 73d95645
...@@ -138,7 +138,7 @@ class Script(scripts.Script): ...@@ -138,7 +138,7 @@ class Script(scripts.Script):
combined_image = images.combine_grid(grid) combined_image = images.combine_grid(grid)
if opts.samples_save: if opts.samples_save:
images.save_image(combined_image, p.outpath_samples, "", initial_seed, p.prompt, opts.grid_format, info=initial_info, p=p) images.save_image(combined_image, p.outpath_samples, "", initial_seed, p.prompt, opts.samples_format, info=initial_info, p=p)
processed = Processed(p, [combined_image], initial_seed, initial_info) processed = Processed(p, [combined_image], initial_seed, initial_info)
......
scripts/postprocessing_upscale.py
View file @ 73d95645
...@@ -4,8 +4,8 @@ import numpy as np ...@@ -4,8 +4,8 @@ import numpy as np
from modules import scripts_postprocessing, shared from modules import scripts_postprocessing, shared
import gradio as gr import gradio as gr
from modules.ui_components import FormRow from modules.ui_components import FormRow, ToolButton
from modules.ui import switch_values_symbol
upscale_cache = {} upscale_cache = {}
...@@ -25,9 +25,12 @@ class ScriptPostprocessingUpscale(scripts_postprocessing.ScriptPostprocessing): ...@@ -25,9 +25,12 @@ class ScriptPostprocessingUpscale(scripts_postprocessing.ScriptPostprocessing):
with gr.TabItem('Scale to', elem_id="extras_scale_to_tab") as tab_scale_to: with gr.TabItem('Scale to', elem_id="extras_scale_to_tab") as tab_scale_to:
with FormRow(): with FormRow():
upscaling_resize_w = gr.Number(label="Width", value=512, precision=0, elem_id="extras_upscaling_resize_w") with gr.Column(elem_id="upscaling_column_size", scale=4):
upscaling_resize_h = gr.Number(label="Height", value=512, precision=0, elem_id="extras_upscaling_resize_h") upscaling_resize_w = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="extras_upscaling_resize_w")
upscaling_crop = gr.Checkbox(label='Crop to fit', value=True, elem_id="extras_upscaling_crop") upscaling_resize_h = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="extras_upscaling_resize_h")
with gr.Column(elem_id="upscaling_dimensions_row", scale=1, elem_classes="dimensions-tools"):
upscaling_res_switch_btn = ToolButton(value=switch_values_symbol, elem_id="upscaling_res_switch_btn")
upscaling_crop = gr.Checkbox(label='Crop to fit', value=True, elem_id="extras_upscaling_crop")
with FormRow(): with FormRow():
extras_upscaler_1 = gr.Dropdown(label='Upscaler 1', elem_id="extras_upscaler_1", choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name) extras_upscaler_1 = gr.Dropdown(label='Upscaler 1', elem_id="extras_upscaler_1", choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name)
...@@ -36,6 +39,7 @@ class ScriptPostprocessingUpscale(scripts_postprocessing.ScriptPostprocessing): ...@@ -36,6 +39,7 @@ class ScriptPostprocessingUpscale(scripts_postprocessing.ScriptPostprocessing):
extras_upscaler_2 = gr.Dropdown(label='Upscaler 2', elem_id="extras_upscaler_2", choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name) extras_upscaler_2 = gr.Dropdown(label='Upscaler 2', elem_id="extras_upscaler_2", choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name)
extras_upscaler_2_visibility = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="Upscaler 2 visibility", value=0.0, elem_id="extras_upscaler_2_visibility") extras_upscaler_2_visibility = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="Upscaler 2 visibility", value=0.0, elem_id="extras_upscaler_2_visibility")
upscaling_res_switch_btn.click(lambda w, h: (h, w), inputs=[upscaling_resize_w, upscaling_resize_h], outputs=[upscaling_resize_w, upscaling_resize_h], show_progress=False)
tab_scale_by.select(fn=lambda: 0, inputs=[], outputs=[selected_tab]) tab_scale_by.select(fn=lambda: 0, inputs=[], outputs=[selected_tab])
tab_scale_to.select(fn=lambda: 1, inputs=[], outputs=[selected_tab]) tab_scale_to.select(fn=lambda: 1, inputs=[], outputs=[selected_tab])
......
scripts/xyz_grid.py
View file @ 73d95645
This diff is collapsed.
style.css
View file @ 73d95645
...@@ -246,7 +246,7 @@ button.custom-button{ ...@@ -246,7 +246,7 @@ button.custom-button{
} }
} }
#txt2img_gallery img, #img2img_gallery img{ #txt2img_gallery img, #img2img_gallery img, #extras_gallery img{
object-fit: scale-down; object-fit: scale-down;
} }
#txt2img_actions_column, #img2img_actions_column { #txt2img_actions_column, #img2img_actions_column {
...@@ -293,7 +293,12 @@ button.custom-button{ ...@@ -293,7 +293,12 @@ button.custom-button{
margin-left: -0.75em margin-left: -0.75em
} }
#txtimg_hr_finalres .resolution{ #img2img_scale_resolution_preview.block{
display: flex;
align-items: end;
}
#txtimg_hr_finalres .resolution, #img2img_scale_resolution_preview .resolution{
font-weight: bold; font-weight: bold;
} }
...@@ -312,6 +317,10 @@ div.dimensions-tools{ ...@@ -312,6 +317,10 @@ div.dimensions-tools{
align-content: center; align-content: center;
} }
div#extras_scale_to_tab div.form{
flex-direction: row;
}
#mode_img2img .gradio-image > div.fixed-height, #mode_img2img .gradio-image > div.fixed-height img{ #mode_img2img .gradio-image > div.fixed-height, #mode_img2img .gradio-image > div.fixed-height img{
height: 480px !important; height: 480px !important;
max-height: 480px !important; max-height: 480px !important;
...@@ -333,6 +342,18 @@ div.dimensions-tools{ ...@@ -333,6 +342,18 @@ div.dimensions-tools{
overflow-wrap: break-word; overflow-wrap: break-word;
} }
#img2img_column_batch{
align-self: end;
margin-bottom: 0.9em;
}
#img2img_unused_scale_by_slider{
visibility: hidden;
width: 0.5em;
max-width: 0.5em;
min-width: 0.5em;
}
/* settings */ /* settings */
#quicksettings { #quicksettings {
width: fit-content; width: fit-content;
...@@ -513,6 +534,8 @@ div.dimensions-tools{ ...@@ -513,6 +534,8 @@ div.dimensions-tools{
#lightboxModal > img.modalImageFullscreen{ #lightboxModal > img.modalImageFullscreen{
object-fit: contain; object-fit: contain;
height: 100%; height: 100%;
width: 100%;
min-height: 0;
} }
.modalPrev, .modalPrev,
...@@ -642,6 +665,12 @@ footer { ...@@ -642,6 +665,12 @@ footer {
/* extra networks UI */ /* extra networks UI */
.extra-network-cards{
height: 725px;
overflow: scroll;
resize: vertical;
}
.extra-networks > div > [id *= '_extra_']{ .extra-networks > div > [id *= '_extra_']{
margin: 0.3em; margin: 0.3em;
} }
......
webui-macos-env.sh
View file @ 73d95645
...@@ -11,7 +11,7 @@ fi ...@@ -11,7 +11,7 @@ fi
export install_dir="$HOME" export install_dir="$HOME"
export COMMANDLINE_ARGS="--skip-torch-cuda-test --upcast-sampling --no-half-vae --use-cpu interrogate" export COMMANDLINE_ARGS="--skip-torch-cuda-test --upcast-sampling --no-half-vae --use-cpu interrogate"
export TORCH_COMMAND="pip install torch==1.12.1 torchvision==0.13.1" export TORCH_COMMAND="pip install torch torchvision"
export K_DIFFUSION_REPO="https://github.com/brkirch/k-diffusion.git" export K_DIFFUSION_REPO="https://github.com/brkirch/k-diffusion.git"
export K_DIFFUSION_COMMIT_HASH="51c9778f269cedb55a4d88c79c0246d35bdadb71" export K_DIFFUSION_COMMIT_HASH="51c9778f269cedb55a4d88c79c0246d35bdadb71"
export PYTORCH_ENABLE_MPS_FALLBACK=1 export PYTORCH_ENABLE_MPS_FALLBACK=1
......
webui-user.sh
View file @ 73d95645
...@@ -43,4 +43,7 @@ ...@@ -43,4 +43,7 @@
# Uncomment to enable accelerated launch # Uncomment to enable accelerated launch
#export ACCELERATE="True" #export ACCELERATE="True"
# Uncomment to disable TCMalloc
#export NO_TCMALLOC="True"
########################################### ###########################################
webui.py
View file @ 73d95645
...@@ -5,6 +5,9 @@ import importlib ...@@ -5,6 +5,9 @@ import importlib
import signal import signal
import re import re
import warnings import warnings
import json
from threading import Thread
from fastapi import FastAPI from fastapi import FastAPI
from fastapi.middleware.cors import CORSMiddleware from fastapi.middleware.cors import CORSMiddleware
from fastapi.middleware.gzip import GZipMiddleware from fastapi.middleware.gzip import GZipMiddleware
...@@ -20,6 +23,9 @@ startup_timer = timer.Timer() ...@@ -20,6 +23,9 @@ startup_timer = timer.Timer()
import torch import torch
import pytorch_lightning # pytorch_lightning should be imported after torch, but it re-enables warnings on import so import once to disable them import pytorch_lightning # pytorch_lightning should be imported after torch, but it re-enables warnings on import so import once to disable them
warnings.filterwarnings(action="ignore", category=DeprecationWarning, module="pytorch_lightning") warnings.filterwarnings(action="ignore", category=DeprecationWarning, module="pytorch_lightning")
warnings.filterwarnings(action="ignore", category=UserWarning, module="torchvision")
startup_timer.record("import torch") startup_timer.record("import torch")
import gradio import gradio
...@@ -37,7 +43,7 @@ if ".dev" in torch.__version__ or "+git" in torch.__version__: ...@@ -37,7 +43,7 @@ if ".dev" in torch.__version__ or "+git" in torch.__version__:
torch.__long_version__ = torch.__version__ torch.__long_version__ = torch.__version__
torch.__version__ = re.search(r'[\d.]+[\d]', torch.__version__).group(0) torch.__version__ = re.search(r'[\d.]+[\d]', torch.__version__).group(0)
from modules import shared, devices, sd_samplers, upscaler, extensions, localization, ui_tempdir, ui_extra_networks from modules import shared, devices, sd_samplers, upscaler, extensions, localization, ui_tempdir, ui_extra_networks, config_states
import modules.codeformer_model as codeformer import modules.codeformer_model as codeformer
import modules.face_restoration import modules.face_restoration
import modules.gfpgan_model as gfpgan import modules.gfpgan_model as gfpgan
...@@ -67,11 +73,51 @@ else: ...@@ -67,11 +73,51 @@ else:
server_name = "0.0.0.0" if cmd_opts.listen else None server_name = "0.0.0.0" if cmd_opts.listen else None
def fix_asyncio_event_loop_policy():
"""
The default `asyncio` event loop policy only automatically creates
event loops in the main threads. Other threads must create event
loops explicitly or `asyncio.get_event_loop` (and therefore
`.IOLoop.current`) will fail. Installing this policy allows event
loops to be created automatically on any thread, matching the
behavior of Tornado versions prior to 5.0 (or 5.0 on Python 2).
"""
import asyncio
if sys.platform == "win32" and hasattr(asyncio, "WindowsSelectorEventLoopPolicy"):
# "Any thread" and "selector" should be orthogonal, but there's not a clean
# interface for composing policies so pick the right base.
_BasePolicy = asyncio.WindowsSelectorEventLoopPolicy # type: ignore
else:
_BasePolicy = asyncio.DefaultEventLoopPolicy
class AnyThreadEventLoopPolicy(_BasePolicy): # type: ignore
"""Event loop policy that allows loop creation on any thread.
Usage::
asyncio.set_event_loop_policy(AnyThreadEventLoopPolicy())
"""
def get_event_loop(self) -> asyncio.AbstractEventLoop:
try:
return super().get_event_loop()
except (RuntimeError, AssertionError):
# This was an AssertionError in python 3.4.2 (which ships with debian jessie)
# and changed to a RuntimeError in 3.4.3.
# "There is no current event loop in thread %r"
loop = self.new_event_loop()
self.set_event_loop(loop)
return loop
asyncio.set_event_loop_policy(AnyThreadEventLoopPolicy())
def check_versions(): def check_versions():
if shared.cmd_opts.skip_version_check: if shared.cmd_opts.skip_version_check:
return return
expected_torch_version = "1.13.1" expected_torch_version = "2.0.0"
if version.parse(torch.__version__) < version.parse(expected_torch_version): if version.parse(torch.__version__) < version.parse(expected_torch_version):
errors.print_error_explanation(f""" errors.print_error_explanation(f"""
...@@ -84,7 +130,7 @@ there are reports of issues with training tab on the latest version. ...@@ -84,7 +130,7 @@ there are reports of issues with training tab on the latest version.
Use --skip-version-check commandline argument to disable this check. Use --skip-version-check commandline argument to disable this check.
""".strip()) """.strip())
expected_xformers_version = "0.0.16rc425" expected_xformers_version = "0.0.17"
if shared.xformers_available: if shared.xformers_available:
import xformers import xformers
...@@ -99,12 +145,27 @@ Use --skip-version-check commandline argument to disable this check. ...@@ -99,12 +145,27 @@ Use --skip-version-check commandline argument to disable this check.
def initialize(): def initialize():
fix_asyncio_event_loop_policy()
check_versions() check_versions()
extensions.list_extensions() extensions.list_extensions()
localization.list_localizations(cmd_opts.localizations_dir) localization.list_localizations(cmd_opts.localizations_dir)
startup_timer.record("list extensions") startup_timer.record("list extensions")
config_state_file = shared.opts.restore_config_state_file
shared.opts.restore_config_state_file = ""
shared.opts.save(shared.config_filename)
if os.path.isfile(config_state_file):
print(f"*** About to restore extension state from file: {config_state_file}")
with open(config_state_file, "r", encoding="utf-8") as f:
config_state = json.load(f)
config_states.restore_extension_config(config_state)
startup_timer.record("restore extension config")
elif config_state_file:
print(f"!!! Config state backup not found: {config_state_file}")
if cmd_opts.ui_debug_mode: if cmd_opts.ui_debug_mode:
shared.sd_upscalers = upscaler.UpscalerLanczos().scalers shared.sd_upscalers = upscaler.UpscalerLanczos().scalers
modules.scripts.load_scripts() modules.scripts.load_scripts()
...@@ -126,30 +187,20 @@ def initialize(): ...@@ -126,30 +187,20 @@ def initialize():
modules.scripts.load_scripts() modules.scripts.load_scripts()
startup_timer.record("load scripts") startup_timer.record("load scripts")
modelloader.load_upscalers()
startup_timer.record("load upscalers")
modules.sd_vae.refresh_vae_list() modules.sd_vae.refresh_vae_list()
startup_timer.record("refresh VAE") startup_timer.record("refresh VAE")
modules.textual_inversion.textual_inversion.list_textual_inversion_templates() modules.textual_inversion.textual_inversion.list_textual_inversion_templates()
startup_timer.record("refresh textual inversion templates") startup_timer.record("refresh textual inversion templates")
try: # load model in parallel to other startup stuff
modules.sd_models.load_model() Thread(target=lambda: shared.sd_model).start()
except Exception as e:
errors.display(e, "loading stable diffusion model")
print("", file=sys.stderr)
print("Stable diffusion model failed to load, exiting", file=sys.stderr)
exit(1)
startup_timer.record("load SD checkpoint")
shared.opts.data["sd_model_checkpoint"] = shared.sd_model.sd_checkpoint_info.title
shared.opts.onchange("sd_model_checkpoint", wrap_queued_call(lambda: modules.sd_models.reload_model_weights())) shared.opts.onchange("sd_model_checkpoint", wrap_queued_call(lambda: modules.sd_models.reload_model_weights()), call=False)
shared.opts.onchange("sd_vae", wrap_queued_call(lambda: modules.sd_vae.reload_vae_weights()), call=False) shared.opts.onchange("sd_vae", wrap_queued_call(lambda: modules.sd_vae.reload_vae_weights()), call=False)
shared.opts.onchange("sd_vae_as_default", wrap_queued_call(lambda: modules.sd_vae.reload_vae_weights()), call=False) shared.opts.onchange("sd_vae_as_default", wrap_queued_call(lambda: modules.sd_vae.reload_vae_weights()), call=False)
shared.opts.onchange("temp_dir", ui_tempdir.on_tmpdir_changed) shared.opts.onchange("temp_dir", ui_tempdir.on_tmpdir_changed)
shared.opts.onchange("gradio_theme", shared.reload_gradio_theme)
startup_timer.record("opts onchange") startup_timer.record("opts onchange")
shared.reload_hypernetworks() shared.reload_hypernetworks()
...@@ -212,6 +263,8 @@ def wait_on_server(demo=None): ...@@ -212,6 +263,8 @@ def wait_on_server(demo=None):
time.sleep(0.5) time.sleep(0.5)
demo.close() demo.close()
time.sleep(0.5) time.sleep(0.5)
modules.script_callbacks.app_reload_callback()
break break
...@@ -227,7 +280,6 @@ def api_only(): ...@@ -227,7 +280,6 @@ def api_only():
print(f"Startup time: {startup_timer.summary()}.") print(f"Startup time: {startup_timer.summary()}.")
api.launch(server_name="0.0.0.0" if cmd_opts.listen else "127.0.0.1", port=cmd_opts.port if cmd_opts.port else 7861) api.launch(server_name="0.0.0.0" if cmd_opts.listen else "127.0.0.1", port=cmd_opts.port if cmd_opts.port else 7861)
def webui(): def webui():
launch_api = cmd_opts.api launch_api = cmd_opts.api
initialize() initialize()
...@@ -254,12 +306,23 @@ def webui(): ...@@ -254,12 +306,23 @@ def webui():
for line in file.readlines(): for line in file.readlines():
gradio_auth_creds += [x.strip() for x in line.split(',') if x.strip()] gradio_auth_creds += [x.strip() for x in line.split(',') if x.strip()]
# this restores the missing /docs endpoint
if launch_api and not hasattr(FastAPI, 'original_setup'):
def fastapi_setup(self):
self.docs_url = "/docs"
self.redoc_url = "/redoc"
self.original_setup()
FastAPI.original_setup = FastAPI.setup
FastAPI.setup = fastapi_setup
app, local_url, share_url = shared.demo.launch( app, local_url, share_url = shared.demo.launch(
share=cmd_opts.share, share=cmd_opts.share,
server_name=server_name, server_name=server_name,
server_port=cmd_opts.port, server_port=cmd_opts.port,
ssl_keyfile=cmd_opts.tls_keyfile, ssl_keyfile=cmd_opts.tls_keyfile,
ssl_certfile=cmd_opts.tls_certfile, ssl_certfile=cmd_opts.tls_certfile,
ssl_verify=cmd_opts.disable_tls_verify,
debug=cmd_opts.gradio_debug, debug=cmd_opts.gradio_debug,
auth=[tuple(cred.split(':')) for cred in gradio_auth_creds] if gradio_auth_creds else None, auth=[tuple(cred.split(':')) for cred in gradio_auth_creds] if gradio_auth_creds else None,
inbrowser=cmd_opts.autolaunch, inbrowser=cmd_opts.autolaunch,
...@@ -290,6 +353,11 @@ def webui(): ...@@ -290,6 +353,11 @@ def webui():
print(f"Startup time: {startup_timer.summary()}.") print(f"Startup time: {startup_timer.summary()}.")
if cmd_opts.subpath:
redirector = FastAPI()
redirector.get("/")
mounted_app = gradio.mount_gradio_app(redirector, shared.demo, path=f"/{cmd_opts.subpath}")
wait_on_server(shared.demo) wait_on_server(shared.demo)
print('Restarting UI...') print('Restarting UI...')
...@@ -301,6 +369,19 @@ def webui(): ...@@ -301,6 +369,19 @@ def webui():
extensions.list_extensions() extensions.list_extensions()
startup_timer.record("list extensions") startup_timer.record("list extensions")
config_state_file = shared.opts.restore_config_state_file
shared.opts.restore_config_state_file = ""
shared.opts.save(shared.config_filename)
if os.path.isfile(config_state_file):
print(f"*** About to restore extension state from file: {config_state_file}")
with open(config_state_file, "r", encoding="utf-8") as f:
config_state = json.load(f)
config_states.restore_extension_config(config_state)
startup_timer.record("restore extension config")
elif config_state_file:
print(f"!!! Config state backup not found: {config_state_file}")
localization.list_localizations(cmd_opts.localizations_dir) localization.list_localizations(cmd_opts.localizations_dir)
modelloader.forbid_loaded_nonbuiltin_upscalers() modelloader.forbid_loaded_nonbuiltin_upscalers()
......
webui.sh
View file @ 73d95645
...@@ -23,7 +23,7 @@ fi ...@@ -23,7 +23,7 @@ fi
# Install directory without trailing slash # Install directory without trailing slash
if [[ -z "${install_dir}" ]] if [[ -z "${install_dir}" ]]
then then
install_dir="/home/$(whoami)" install_dir="$(pwd)"
fi fi
# Name of the subdirectory (defaults to stable-diffusion-webui) # Name of the subdirectory (defaults to stable-diffusion-webui)
...@@ -113,12 +113,13 @@ case "$gpu_info" in ...@@ -113,12 +113,13 @@ case "$gpu_info" in
printf "Experimental support for Renoir: make sure to have at least 4GB of VRAM and 10GB of RAM or enable cpu mode: --use-cpu all --no-half" printf "Experimental support for Renoir: make sure to have at least 4GB of VRAM and 10GB of RAM or enable cpu mode: --use-cpu all --no-half"
printf "\n%s\n" "${delimiter}" printf "\n%s\n" "${delimiter}"
;; ;;
*) *)
;; ;;
esac esac
if echo "$gpu_info" | grep -q "AMD" && [[ -z "${TORCH_COMMAND}" ]] if echo "$gpu_info" | grep -q "AMD" && [[ -z "${TORCH_COMMAND}" ]]
then then
export TORCH_COMMAND="pip install torch torchvision --extra-index-url https://download.pytorch.org/whl/rocm5.2" # AMD users will still use torch 1.13 because 2.0 does not seem to work.
export TORCH_COMMAND="pip install torch==1.13.1+rocm5.2 torchvision==0.14.1+rocm5.2 --index-url https://download.pytorch.org/whl/rocm5.2"
fi fi
for preq in "${GIT}" "${python_cmd}" for preq in "${GIT}" "${python_cmd}"
...@@ -152,35 +153,57 @@ else ...@@ -152,35 +153,57 @@ else
cd "${clone_dir}"/ || { printf "\e[1m\e[31mERROR: Can't cd to %s/%s/, aborting...\e[0m" "${install_dir}" "${clone_dir}"; exit 1; } cd "${clone_dir}"/ || { printf "\e[1m\e[31mERROR: Can't cd to %s/%s/, aborting...\e[0m" "${install_dir}" "${clone_dir}"; exit 1; }
fi fi
printf "\n%s\n" "${delimiter}" if [[ -z "${VIRTUAL_ENV}" ]];
printf "Create and activate python venv"
printf "\n%s\n" "${delimiter}"
cd "${install_dir}"/"${clone_dir}"/ || { printf "\e[1m\e[31mERROR: Can't cd to %s/%s/, aborting...\e[0m" "${install_dir}" "${clone_dir}"; exit 1; }
if [[ ! -d "${venv_dir}" ]]
then
"${python_cmd}" -m venv "${venv_dir}"
first_launch=1
fi
# shellcheck source=/dev/null
if [[ -f "${venv_dir}"/bin/activate ]]
then then
source "${venv_dir}"/bin/activate printf "\n%s\n" "${delimiter}"
printf "Create and activate python venv"
printf "\n%s\n" "${delimiter}"
cd "${install_dir}"/"${clone_dir}"/ || { printf "\e[1m\e[31mERROR: Can't cd to %s/%s/, aborting...\e[0m" "${install_dir}" "${clone_dir}"; exit 1; }
if [[ ! -d "${venv_dir}" ]]
then
"${python_cmd}" -m venv "${venv_dir}"
first_launch=1
fi
# shellcheck source=/dev/null
if [[ -f "${venv_dir}"/bin/activate ]]
then
source "${venv_dir}"/bin/activate
else
printf "\n%s\n" "${delimiter}"
printf "\e[1m\e[31mERROR: Cannot activate python venv, aborting...\e[0m"
printf "\n%s\n" "${delimiter}"
exit 1
fi
else else
printf "\n%s\n" "${delimiter}" printf "\n%s\n" "${delimiter}"
printf "\e[1m\e[31mERROR: Cannot activate python venv, aborting...\e[0m" printf "python venv already activate: ${VIRTUAL_ENV}"
printf "\n%s\n" "${delimiter}" printf "\n%s\n" "${delimiter}"
exit 1
fi fi
# Try using TCMalloc on Linux
prepare_tcmalloc() {
if [[ "${OSTYPE}" == "linux"* ]] && [[ -z "${NO_TCMALLOC}" ]] && [[ -z "${LD_PRELOAD}" ]]; then
TCMALLOC="$(ldconfig -p | grep -Po "libtcmalloc.so.\d" | head -n 1)"
if [[ ! -z "${TCMALLOC}" ]]; then
echo "Using TCMalloc: ${TCMALLOC}"
export LD_PRELOAD="${TCMALLOC}"
else
printf "\e[1m\e[31mCannot locate TCMalloc (improves CPU memory usage)\e[0m\n"
fi
fi
}
if [[ ! -z "${ACCELERATE}" ]] && [ ${ACCELERATE}="True" ] && [ -x "$(command -v accelerate)" ] if [[ ! -z "${ACCELERATE}" ]] && [ ${ACCELERATE}="True" ] && [ -x "$(command -v accelerate)" ]
then then
printf "\n%s\n" "${delimiter}" printf "\n%s\n" "${delimiter}"
printf "Accelerating launch.py..." printf "Accelerating launch.py..."
printf "\n%s\n" "${delimiter}" printf "\n%s\n" "${delimiter}"
prepare_tcmalloc
exec accelerate launch --num_cpu_threads_per_process=6 "${LAUNCH_SCRIPT}" "$@" exec accelerate launch --num_cpu_threads_per_process=6 "${LAUNCH_SCRIPT}" "$@"
else else
printf "\n%s\n" "${delimiter}" printf "\n%s\n" "${delimiter}"
printf "Launching launch.py..." printf "Launching launch.py..."
printf "\n%s\n" "${delimiter}" printf "\n%s\n" "${delimiter}"
prepare_tcmalloc
exec "${python_cmd}" "${LAUNCH_SCRIPT}" "$@" exec "${python_cmd}" "${LAUNCH_SCRIPT}" "$@"
fi fi
Markdown is supported
0% or
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment