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Stable Diffusion Webui
Commit 2267498a authored by Bruno Seoane's avatar Bruno Seoane
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Merge remote-tracking branch 'upstream/master'

parents 595dca85 5587ab7e
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.gitignore
View file @ 2267498a
......@@ -29,3 +29,4 @@ notification.mp3
/textual_inversion
.vscode
/extensions
javascript/images_history.js deleted 100644 → 0
View file @ 595dca85
var images_history_click_image = function(){
if (!this.classList.contains("transform")){
var gallery = images_history_get_parent_by_class(this, "images_history_cantainor");
var buttons = gallery.querySelectorAll(".gallery-item");
var i = 0;
var hidden_list = [];
buttons.forEach(function(e){
if (e.style.display == "none"){
hidden_list.push(i);
}
i += 1;
})
if (hidden_list.length > 0){
setTimeout(images_history_hide_buttons, 10, hidden_list, gallery);
}
}
images_history_set_image_info(this);
}
function images_history_disabled_del(){
gradioApp().querySelectorAll(".images_history_del_button").forEach(function(btn){
btn.setAttribute('disabled','disabled');
});
}
function images_history_get_parent_by_class(item, class_name){
var parent = item.parentElement;
while(!parent.classList.contains(class_name)){
parent = parent.parentElement;
}
return parent;
}
function images_history_get_parent_by_tagname(item, tagname){
var parent = item.parentElement;
tagname = tagname.toUpperCase()
while(parent.tagName != tagname){
parent = parent.parentElement;
}
return parent;
}
function images_history_hide_buttons(hidden_list, gallery){
var buttons = gallery.querySelectorAll(".gallery-item");
var num = 0;
buttons.forEach(function(e){
if (e.style.display == "none"){
num += 1;
}
});
if (num == hidden_list.length){
setTimeout(images_history_hide_buttons, 10, hidden_list, gallery);
}
for( i in hidden_list){
buttons[hidden_list[i]].style.display = "none";
}
}
function images_history_set_image_info(button){
var buttons = images_history_get_parent_by_tagname(button, "DIV").querySelectorAll(".gallery-item");
var index = -1;
var i = 0;
buttons.forEach(function(e){
if(e == button){
index = i;
}
if(e.style.display != "none"){
i += 1;
}
});
var gallery = images_history_get_parent_by_class(button, "images_history_cantainor");
var set_btn = gallery.querySelector(".images_history_set_index");
var curr_idx = set_btn.getAttribute("img_index", index);
if (curr_idx != index) {
set_btn.setAttribute("img_index", index);
images_history_disabled_del();
}
set_btn.click();
}
function images_history_get_current_img(tabname, img_index, files){
return [
tabname,
gradioApp().getElementById(tabname + '_images_history_set_index').getAttribute("img_index"),
files
];
}
function images_history_delete(del_num, tabname, image_index){
image_index = parseInt(image_index);
var tab = gradioApp().getElementById(tabname + '_images_history');
var set_btn = tab.querySelector(".images_history_set_index");
var buttons = [];
tab.querySelectorAll(".gallery-item").forEach(function(e){
if (e.style.display != 'none'){
buttons.push(e);
}
});
var img_num = buttons.length / 2;
del_num = Math.min(img_num - image_index, del_num)
if (img_num <= del_num){
setTimeout(function(tabname){
gradioApp().getElementById(tabname + '_images_history_renew_page').click();
}, 30, tabname);
} else {
var next_img
for (var i = 0; i < del_num; i++){
buttons[image_index + i].style.display = 'none';
buttons[image_index + i + img_num].style.display = 'none';
next_img = image_index + i + 1
}
var bnt;
if (next_img >= img_num){
btn = buttons[image_index - 1];
} else {
btn = buttons[next_img];
}
setTimeout(function(btn){btn.click()}, 30, btn);
}
images_history_disabled_del();
}
function images_history_turnpage(tabname){
gradioApp().getElementById(tabname + '_images_history_del_button').setAttribute('disabled','disabled');
var buttons = gradioApp().getElementById(tabname + '_images_history').querySelectorAll(".gallery-item");
buttons.forEach(function(elem) {
elem.style.display = 'block';
})
}
function images_history_enable_del_buttons(){
gradioApp().querySelectorAll(".images_history_del_button").forEach(function(btn){
btn.removeAttribute('disabled');
})
}
function images_history_init(){
var tabnames = gradioApp().getElementById("images_history_tabnames_list")
if (tabnames){
images_history_tab_list = tabnames.querySelector("textarea").value.split(",")
for (var i in images_history_tab_list ){
var tab = images_history_tab_list[i];
gradioApp().getElementById(tab + '_images_history').classList.add("images_history_cantainor");
gradioApp().getElementById(tab + '_images_history_set_index').classList.add("images_history_set_index");
gradioApp().getElementById(tab + '_images_history_del_button').classList.add("images_history_del_button");
gradioApp().getElementById(tab + '_images_history_gallery').classList.add("images_history_gallery");
gradioApp().getElementById(tab + "_images_history_start").setAttribute("style","padding:20px;font-size:25px");
}
//preload
if (gradioApp().getElementById("images_history_preload").querySelector("input").checked ){
var tabs_box = gradioApp().getElementById("tab_images_history").querySelector("div").querySelector("div").querySelector("div");
tabs_box.setAttribute("id", "images_history_tab");
var tab_btns = tabs_box.querySelectorAll("button");
for (var i in images_history_tab_list){
var tabname = images_history_tab_list[i]
tab_btns[i].setAttribute("tabname", tabname);
tab_btns[i].addEventListener('click', function(){
var tabs_box = gradioApp().getElementById("images_history_tab");
if (!tabs_box.classList.contains(this.getAttribute("tabname"))) {
gradioApp().getElementById(this.getAttribute("tabname") + "_images_history_start").click();
tabs_box.classList.add(this.getAttribute("tabname"))
}
});
}
tab_btns[0].click()
}
} else {
setTimeout(images_history_init, 500);
}
}
var images_history_tab_list = "";
setTimeout(images_history_init, 500);
document.addEventListener("DOMContentLoaded", function() {
var mutationObserver = new MutationObserver(function(m){
if (images_history_tab_list != ""){
for (var i in images_history_tab_list ){
let tabname = images_history_tab_list[i]
var buttons = gradioApp().querySelectorAll('#' + tabname + '_images_history .gallery-item');
buttons.forEach(function(bnt){
bnt.addEventListener('click', images_history_click_image, true);
});
var cls_btn = gradioApp().getElementById(tabname + '_images_history_gallery').querySelector("svg");
if (cls_btn){
cls_btn.addEventListener('click', function(){
gradioApp().getElementById(tabname + '_images_history_renew_page').click();
}, false);
}
}
}
});
mutationObserver.observe(gradioApp(), { childList:true, subtree:true });
});
launch.py
View file @ 2267498a
......@@ -111,7 +111,7 @@ def prepare_enviroment():
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")
deepdanbooru_package = os.environ.get('DEEPDANBOORU_PACKAGE', "git+https://github.com/KichangKim/DeepDanbooru.git@edf73df4cdaeea2cf00e9ac08bd8a9026b7a7b26")
deepdanbooru_package = os.environ.get('DEEPDANBOORU_PACKAGE', "git+https://github.com/KichangKim/DeepDanbooru.git@d91a2963bf87c6a770d74894667e9ffa9f6de7ff")
xformers_windows_package = os.environ.get('XFORMERS_WINDOWS_PACKAGE', 'https://github.com/C43H66N12O12S2/stable-diffusion-webui/releases/download/f/xformers-0.0.14.dev0-cp310-cp310-win_amd64.whl')
......
localizations/ar_AR.json 0 → 100644
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localizations/ja_JP.json
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localizations/ko_KR.json 0 → 100644
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modules/api/models.py
View file @ 2267498a
import inspect
from pydantic import BaseModel, Field, Json, create_model
from pydantic import BaseModel, Field, create_model
from typing import Any, Optional
from typing_extensions import Literal
from inflection import underscore
......
modules/hypernetworks/hypernetwork.py
View file @ 2267498a
......@@ -16,6 +16,7 @@ from modules.textual_inversion import textual_inversion
from modules.textual_inversion.learn_schedule import LearnRateScheduler
from torch import einsum
from collections import defaultdict, deque
from statistics import stdev, mean
class HypernetworkModule(torch.nn.Module):
......@@ -269,19 +270,18 @@ def stack_conds(conds):
return torch.stack(conds)
def log_statistics(loss_info:dict, key, value):
if key not in loss_info:
loss_info[key] = [value]
else:
loss_info[key].append(value)
if len(loss_info) > 1024:
loss_info.pop(0)
def statistics(data):
total_information = f"loss:{mean(data):.3f}"+u"\u00B1"+f"({stdev(data)/ (len(data)**0.5):.3f})"
if len(data) < 2:
std = 0
else:
std = stdev(data)
total_information = f"loss:{mean(data):.3f}" + u"\u00B1" + f"({std/ (len(data) ** 0.5):.3f})"
recent_data = data[-32:]
recent_information = f"recent 32 loss:{mean(recent_data):.3f}"+u"\u00B1"+f"({stdev(recent_data)/ (len(recent_data)**0.5):.3f})"
if len(recent_data) < 2:
std = 0
else:
std = stdev(recent_data)
recent_information = f"recent 32 loss:{mean(recent_data):.3f}" + u"\u00B1" + f"({std / (len(recent_data) ** 0.5):.3f})"
return total_information, recent_information
......@@ -290,7 +290,7 @@ def report_statistics(loss_info:dict):
for key in keys:
try:
print("Loss statistics for file " + key)
info, recent = statistics(loss_info[key])
info, recent = statistics(list(loss_info[key]))
print(info)
print(recent)
except Exception as e:
......@@ -341,8 +341,9 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, data_root, log
weight.requires_grad = True
size = len(ds.indexes)
loss_dict = {}
loss_dict = defaultdict(lambda : deque(maxlen = 1024))
losses = torch.zeros((size,))
previous_mean_losses = [0]
previous_mean_loss = 0
print("Mean loss of {} elements".format(size))
......@@ -364,7 +365,8 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, data_root, log
for i, entries in pbar:
hypernetwork.step = i + ititial_step
if len(loss_dict) > 0:
previous_mean_loss = sum(i[-1] for i in loss_dict.values()) / len(loss_dict)
previous_mean_losses = [i[-1] for i in loss_dict.values()]
previous_mean_loss = mean(previous_mean_losses)
scheduler.apply(optimizer, hypernetwork.step)
if scheduler.finished:
......@@ -383,7 +385,7 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, data_root, log
losses[hypernetwork.step % losses.shape[0]] = loss.item()
for entry in entries:
log_statistics(loss_dict, entry.filename, loss.item())
loss_dict[entry.filename].append(loss.item())
optimizer.zero_grad()
weights[0].grad = None
......@@ -399,7 +401,13 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, data_root, log
if torch.isnan(losses[hypernetwork.step % losses.shape[0]]):
raise RuntimeError("Loss diverged.")
pbar.set_description(f"dataset loss: {previous_mean_loss:.7f}")
if len(previous_mean_losses) > 1:
std = stdev(previous_mean_losses)
else:
std = 0
dataset_loss_info = f"dataset loss:{mean(previous_mean_losses):.3f}" + u"\u00B1" + f"({std / (len(previous_mean_losses) ** 0.5):.3f})"
pbar.set_description(dataset_loss_info)
if hypernetwork.step > 0 and hypernetwork_dir is not None and hypernetwork.step % save_hypernetwork_every == 0:
# Before saving, change name to match current checkpoint.
......
modules/images.py
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modules/images_history.py deleted 100644 → 0
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modules/processing.py
View file @ 2267498a
......@@ -47,6 +47,25 @@ def apply_color_correction(correction, image):
return image
def apply_overlay(image, paste_loc, index, overlays):
if overlays is None or index >= len(overlays):
return image
overlay = overlays[index]
if paste_loc is not None:
x, y, w, h = paste_loc
base_image = Image.new('RGBA', (overlay.width, overlay.height))
image = images.resize_image(1, image, w, h)
base_image.paste(image, (x, y))
image = base_image
image = image.convert('RGBA')
image.alpha_composite(overlay)
image = image.convert('RGB')
return image
def get_correct_sampler(p):
if isinstance(p, modules.processing.StableDiffusionProcessingTxt2Img):
return sd_samplers.samplers
......@@ -449,22 +468,11 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
if p.color_corrections is not None and i < len(p.color_corrections):
if opts.save and not p.do_not_save_samples and opts.save_images_before_color_correction:
images.save_image(image, p.outpath_samples, "", seeds[i], prompts[i], opts.samples_format, info=infotext(n, i), p=p, suffix="-before-color-correction")
image_without_cc = apply_overlay(image, p.paste_to, i, p.overlay_images)
images.save_image(image_without_cc, p.outpath_samples, "", seeds[i], prompts[i], opts.samples_format, info=infotext(n, i), p=p, suffix="-before-color-correction")
image = apply_color_correction(p.color_corrections[i], image)
if p.overlay_images is not None and i < len(p.overlay_images):
overlay = p.overlay_images[i]
if p.paste_to is not None:
x, y, w, h = p.paste_to
base_image = Image.new('RGBA', (overlay.width, overlay.height))
image = images.resize_image(1, image, w, h)
base_image.paste(image, (x, y))
image = base_image
image = image.convert('RGBA')
image.alpha_composite(overlay)
image = image.convert('RGB')
image = apply_overlay(image, p.paste_to, i, p.overlay_images)
if opts.samples_save and not p.do_not_save_samples:
images.save_image(image, p.outpath_samples, "", seeds[i], prompts[i], opts.samples_format, info=infotext(n, i), p=p)
......
modules/script_callbacks.py
View file @ 2267498a
......@@ -16,7 +16,7 @@ def model_loaded_callback(sd_model):
def ui_tabs_callback():
res = []
for callback in callbacks_ui_tabs:
res += callback() or []
......
modules/shared.py
View file @ 2267498a
......@@ -80,12 +80,13 @@ parser.add_argument('--vae-path', type=str, help='Path to Variational Autoencode
parser.add_argument("--disable-safe-unpickle", action='store_true', help="disable checking pytorch models for malicious code", default=False)
parser.add_argument("--api", action='store_true', help="use api=True to launch the api with the webui")
parser.add_argument("--nowebui", action='store_true', help="use api=True to launch the api instead of the webui")
parser.add_argument("--ui-debug-mode", action='store_true', help="Don't load model to quickly launch UI")
parser.add_argument("--device-id", type=str, help="Select the default CUDA device to use (export CUDA_VISIBLE_DEVICES=0,1,etc might be needed before)", default=None)
parser.add_argument("--browse-all-images", action='store_true', help="Allow browsing all images by Image Browser", default=False)
cmd_opts = parser.parse_args()
restricted_opts = [
"samples_filename_pattern",
"directories_filename_pattern",
"outdir_samples",
"outdir_txt2img_samples",
"outdir_img2img_samples",
......@@ -190,7 +191,8 @@ options_templates = {}
options_templates.update(options_section(('saving-images', "Saving images/grids"), {
"samples_save": OptionInfo(True, "Always save all generated images"),
"samples_format": OptionInfo('png', 'File format for images'),
"samples_filename_pattern": OptionInfo("", "Images filename pattern"),
"samples_filename_pattern": OptionInfo("", "Images filename pattern", component_args=hide_dirs),
"save_images_add_number": OptionInfo(True, "Add number to filename when saving", component_args=hide_dirs),
"grid_save": OptionInfo(True, "Always save all generated image grids"),
"grid_format": OptionInfo('png', 'File format for grids'),
......@@ -225,8 +227,8 @@ options_templates.update(options_section(('saving-to-dirs', "Saving to a directo
"save_to_dirs": OptionInfo(False, "Save images to a subdirectory"),
"grid_save_to_dirs": OptionInfo(False, "Save grids to a subdirectory"),
"use_save_to_dirs_for_ui": OptionInfo(False, "When using \"Save\" button, save images to a subdirectory"),
"directories_filename_pattern": OptionInfo("", "Directory name pattern"),
"directories_max_prompt_words": OptionInfo(8, "Max prompt words for [prompt_words] pattern", gr.Slider, {"minimum": 1, "maximum": 20, "step": 1}),
"directories_filename_pattern": OptionInfo("", "Directory name pattern", component_args=hide_dirs),
"directories_max_prompt_words": OptionInfo(8, "Max prompt words for [prompt_words] pattern", gr.Slider, {"minimum": 1, "maximum": 20, "step": 1, **hide_dirs}),
}))
options_templates.update(options_section(('upscaling', "Upscaling"), {
......@@ -320,15 +322,6 @@ options_templates.update(options_section(('sampler-params', "Sampler parameters"
'eta_noise_seed_delta': OptionInfo(0, "Eta noise seed delta", gr.Number, {"precision": 0}),
}))
options_templates.update(options_section(('images-history', "Images Browser"), {
#"images_history_reconstruct_directory": OptionInfo(False, "Reconstruct output directory structure.This can greatly improve the speed of loading , but will change the original output directory structure"),
"images_history_preload": OptionInfo(False, "Preload images at startup"),
"images_history_num_per_page": OptionInfo(36, "Number of pictures displayed on each page"),
"images_history_pages_num": OptionInfo(6, "Minimum number of pages per load "),
"images_history_grid_num": OptionInfo(6, "Number of grids in each row"),
}))
class Options:
data = None
......@@ -357,7 +350,7 @@ class Options:
def save(self, filename):
with open(filename, "w", encoding="utf8") as file:
json.dump(self.data, file)
json.dump(self.data, file, indent=4)
def same_type(self, x, y):
if x is None or y is None:
......
modules/ui.py
View file @ 2267498a
......@@ -38,7 +38,6 @@ import modules.codeformer_model
import modules.generation_parameters_copypaste
import modules.gfpgan_model
import modules.hypernetworks.ui
import modules.images_history as img_his
import modules.ldsr_model
import modules.scripts
import modules.shared as shared
......@@ -51,12 +50,11 @@ from modules.sd_samplers import samplers, samplers_for_img2img
import modules.textual_inversion.ui
import modules.hypernetworks.ui
import modules.images_history as img_his
# this is a fix for Windows users. Without it, javascript files will be served with text/html content-type and the browser will not show any UI
mimetypes.init()
mimetypes.add_type('application/javascript', '.js')
txt2img_paste_fields = []
img2img_paste_fields = []
if not cmd_opts.share and not cmd_opts.listen:
......@@ -786,6 +784,7 @@ def create_ui(wrap_gradio_gpu_call):
]
)
global txt2img_paste_fields
txt2img_paste_fields = [
(txt2img_prompt, "Prompt"),
(txt2img_negative_prompt, "Negative prompt"),
......@@ -1056,6 +1055,7 @@ def create_ui(wrap_gradio_gpu_call):
outputs=[prompt, negative_prompt, style1, style2],
)
global img2img_paste_fields
img2img_paste_fields = [
(img2img_prompt, "Prompt"),
(img2img_negative_prompt, "Negative prompt"),
......@@ -1104,9 +1104,9 @@ def create_ui(wrap_gradio_gpu_call):
upscaling_resize_w = gr.Number(label="Width", value=512, precision=0)
upscaling_resize_h = gr.Number(label="Height", value=512, precision=0)
upscaling_crop = gr.Checkbox(label='Crop to fit', value=True)
with gr.Group():
extras_upscaler_1 = gr.Radio(label='Upscaler 1', elem_id="extras_upscaler_1", choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name, type="index")
extras_upscaler_1 = gr.Radio(label='Upscaler 1', elem_id="extras_upscaler_1", choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name, type="index")
with gr.Group():
extras_upscaler_2 = gr.Radio(label='Upscaler 2', elem_id="extras_upscaler_2", choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name, type="index")
......@@ -1193,15 +1193,7 @@ def create_ui(wrap_gradio_gpu_call):
inputs=[image],
outputs=[html, generation_info, html2],
)
#images history
images_history_switch_dict = {
"fn": modules.generation_parameters_copypaste.connect_paste,
"t2i": txt2img_paste_fields,
"i2i": img2img_paste_fields
}
images_history = img_his.create_history_tabs(gr, opts, cmd_opts, wrap_gradio_call(modules.extras.run_pnginfo), images_history_switch_dict)
with gr.Blocks() as modelmerger_interface:
with gr.Row().style(equal_height=False):
with gr.Column(variant='panel'):
......@@ -1650,7 +1642,6 @@ Requested path was: {f}
(img2img_interface, "img2img", "img2img"),
(extras_interface, "Extras", "extras"),
(pnginfo_interface, "PNG Info", "pnginfo"),
(images_history, "Image Browser", "images_history"),
(modelmerger_interface, "Checkpoint Merger", "modelmerger"),
(train_interface, "Train", "ti"),
]
......@@ -1894,6 +1885,7 @@ def load_javascript(raw_response):
javascript = f'<script>{jsfile.read()}</script>'
scripts_list = modules.scripts.list_scripts("javascript", ".js")
for basedir, filename, path in scripts_list:
with open(path, "r", encoding="utf8") as jsfile:
javascript += f"\n<!-- {filename} --><script>{jsfile.read()}</script>"
......
webui.py
View file @ 2267498a
......@@ -9,7 +9,7 @@ from fastapi.middleware.gzip import GZipMiddleware
from modules.paths import script_path
from modules import devices, sd_samplers
from modules import devices, sd_samplers, upscaler
import modules.codeformer_model as codeformer
import modules.extras
import modules.face_restoration
......@@ -73,6 +73,11 @@ def wrap_gradio_gpu_call(func, extra_outputs=None):
def initialize():
if cmd_opts.ui_debug_mode:
shared.sd_upscalers = upscaler.UpscalerLanczos().scalers
modules.scripts.load_scripts()
return
modelloader.cleanup_models()
modules.sd_models.setup_model()
codeformer.setup_model(cmd_opts.codeformer_models_path)
......
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