Merge branch 'master' of https://github.com/yfszzx/stable-diffusion-webui-plus
This commit is contained in:
yfszzx
commit
511ca57e37
|
|
@ -2,7 +2,7 @@
|
|||
name: Feature request
|
||||
about: Suggest an idea for this project
|
||||
title: ''
|
||||
labels: ''
|
||||
labels: 'suggestion'
|
||||
assignees: ''
|
||||
|
||||
---
|
||||
|
|
|
|||
|
|
@ -16,7 +16,7 @@ contextMenuInit = function(){
|
|||
oldMenu.remove()
|
||||
}
|
||||
|
||||
let tabButton = gradioApp().querySelector('button')
|
||||
let tabButton = uiCurrentTab
|
||||
let baseStyle = window.getComputedStyle(tabButton)
|
||||
|
||||
const contextMenu = document.createElement('nav')
|
||||
|
|
@ -123,44 +123,53 @@ contextMenuInit = function(){
|
|||
return [appendContextMenuOption, removeContextMenuOption, addContextMenuEventListener]
|
||||
}
|
||||
|
||||
initResponse = contextMenuInit()
|
||||
appendContextMenuOption = initResponse[0]
|
||||
removeContextMenuOption = initResponse[1]
|
||||
addContextMenuEventListener = initResponse[2]
|
||||
initResponse = contextMenuInit();
|
||||
appendContextMenuOption = initResponse[0];
|
||||
removeContextMenuOption = initResponse[1];
|
||||
addContextMenuEventListener = initResponse[2];
|
||||
|
||||
|
||||
//Start example Context Menu Items
|
||||
generateOnRepeatId = appendContextMenuOption('#txt2img_generate','Generate forever',function(){
|
||||
let genbutton = gradioApp().querySelector('#txt2img_generate');
|
||||
let interruptbutton = gradioApp().querySelector('#txt2img_interrupt');
|
||||
if(!interruptbutton.offsetParent){
|
||||
genbutton.click();
|
||||
}
|
||||
clearInterval(window.generateOnRepeatInterval)
|
||||
window.generateOnRepeatInterval = setInterval(function(){
|
||||
(function(){
|
||||
//Start example Context Menu Items
|
||||
let generateOnRepeat = function(genbuttonid,interruptbuttonid){
|
||||
let genbutton = gradioApp().querySelector(genbuttonid);
|
||||
let interruptbutton = gradioApp().querySelector(interruptbuttonid);
|
||||
if(!interruptbutton.offsetParent){
|
||||
genbutton.click();
|
||||
}
|
||||
},
|
||||
500)}
|
||||
)
|
||||
|
||||
cancelGenerateForever = function(){
|
||||
clearInterval(window.generateOnRepeatInterval)
|
||||
}
|
||||
|
||||
appendContextMenuOption('#txt2img_interrupt','Cancel generate forever',cancelGenerateForever)
|
||||
appendContextMenuOption('#txt2img_generate', 'Cancel generate forever',cancelGenerateForever)
|
||||
|
||||
|
||||
appendContextMenuOption('#roll','Roll three',
|
||||
function(){
|
||||
let rollbutton = gradioApp().querySelector('#roll');
|
||||
setTimeout(function(){rollbutton.click()},100)
|
||||
setTimeout(function(){rollbutton.click()},200)
|
||||
setTimeout(function(){rollbutton.click()},300)
|
||||
clearInterval(window.generateOnRepeatInterval)
|
||||
window.generateOnRepeatInterval = setInterval(function(){
|
||||
if(!interruptbutton.offsetParent){
|
||||
genbutton.click();
|
||||
}
|
||||
},
|
||||
500)
|
||||
}
|
||||
)
|
||||
|
||||
appendContextMenuOption('#txt2img_generate','Generate forever',function(){
|
||||
generateOnRepeat('#txt2img_generate','#txt2img_interrupt');
|
||||
})
|
||||
appendContextMenuOption('#img2img_generate','Generate forever',function(){
|
||||
generateOnRepeat('#img2img_generate','#img2img_interrupt');
|
||||
})
|
||||
|
||||
let cancelGenerateForever = function(){
|
||||
clearInterval(window.generateOnRepeatInterval)
|
||||
}
|
||||
|
||||
appendContextMenuOption('#txt2img_interrupt','Cancel generate forever',cancelGenerateForever)
|
||||
appendContextMenuOption('#txt2img_generate', 'Cancel generate forever',cancelGenerateForever)
|
||||
appendContextMenuOption('#img2img_interrupt','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
|
||||
|
||||
onUiUpdate(function(){
|
||||
|
|
|
|||
|
|
@ -104,6 +104,7 @@ def prepare_enviroment():
|
|||
args, skip_torch_cuda_test = extract_arg(args, '--skip-torch-cuda-test')
|
||||
xformers = '--xformers' in args
|
||||
deepdanbooru = '--deepdanbooru' in args
|
||||
ngrok = '--ngrok' in args
|
||||
|
||||
try:
|
||||
commit = run(f"{git} rev-parse HEAD").strip()
|
||||
|
|
@ -134,6 +135,9 @@ def prepare_enviroment():
|
|||
if not is_installed("deepdanbooru") and deepdanbooru:
|
||||
run_pip("install git+https://github.com/KichangKim/DeepDanbooru.git@edf73df4cdaeea2cf00e9ac08bd8a9026b7a7b26#egg=deepdanbooru[tensorflow] tensorflow==2.10.0 tensorflow-io==0.27.0", "deepdanbooru")
|
||||
|
||||
if not is_installed("pyngrok") and ngrok:
|
||||
run_pip("install pyngrok", "ngrok")
|
||||
|
||||
os.makedirs(dir_repos, exist_ok=True)
|
||||
|
||||
git_clone("https://github.com/CompVis/stable-diffusion.git", repo_dir('stable-diffusion'), "Stable Diffusion", stable_diffusion_commit_hash)
|
||||
|
|
|
|||
|
|
@ -6,14 +6,14 @@ import gradio as gr
|
|||
import modules.textual_inversion.textual_inversion
|
||||
import modules.textual_inversion.preprocess
|
||||
from modules import sd_hijack, shared
|
||||
from modules.hypernetwork import hypernetwork
|
||||
from modules.hypernetworks import hypernetwork
|
||||
|
||||
|
||||
def create_hypernetwork(name):
|
||||
fn = os.path.join(shared.cmd_opts.hypernetwork_dir, f"{name}.pt")
|
||||
assert not os.path.exists(fn), f"file {fn} already exists"
|
||||
|
||||
hypernet = modules.hypernetwork.hypernetwork.Hypernetwork(name=name)
|
||||
hypernet = modules.hypernetworks.hypernetwork.Hypernetwork(name=name)
|
||||
hypernet.save(fn)
|
||||
|
||||
shared.reload_hypernetworks()
|
||||
|
|
@ -28,7 +28,7 @@ def train_hypernetwork(*args):
|
|||
try:
|
||||
sd_hijack.undo_optimizations()
|
||||
|
||||
hypernetwork, filename = modules.hypernetwork.hypernetwork.train_hypernetwork(*args)
|
||||
hypernetwork, filename = modules.hypernetworks.hypernetwork.train_hypernetwork(*args)
|
||||
|
||||
res = f"""
|
||||
Training {'interrupted' if shared.state.interrupted else 'finished'} at {hypernetwork.step} steps.
|
||||
|
|
@ -0,0 +1,15 @@
|
|||
from pyngrok import ngrok, conf, exception
|
||||
|
||||
|
||||
def connect(token, port):
|
||||
if token == None:
|
||||
token = 'None'
|
||||
conf.get_default().auth_token = token
|
||||
try:
|
||||
public_url = ngrok.connect(port).public_url
|
||||
except exception.PyngrokNgrokError:
|
||||
print(f'Invalid ngrok authtoken, ngrok connection aborted.\n'
|
||||
f'Your token: {token}, get the right one on https://dashboard.ngrok.com/get-started/your-authtoken')
|
||||
else:
|
||||
print(f'ngrok connected to localhost:{port}! URL: {public_url}\n'
|
||||
'You can use this link after the launch is complete.')
|
||||
|
|
@ -37,7 +37,7 @@ def apply_optimizations():
|
|||
|
||||
|
||||
def undo_optimizations():
|
||||
from modules.hypernetwork import hypernetwork
|
||||
from modules.hypernetworks import hypernetwork
|
||||
|
||||
ldm.modules.attention.CrossAttention.forward = hypernetwork.attention_CrossAttention_forward
|
||||
ldm.modules.diffusionmodules.model.nonlinearity = diffusionmodules_model_nonlinearity
|
||||
|
|
|
|||
|
|
@ -9,7 +9,7 @@ from ldm.util import default
|
|||
from einops import rearrange
|
||||
|
||||
from modules import shared
|
||||
from modules.hypernetwork import hypernetwork
|
||||
from modules.hypernetworks import hypernetwork
|
||||
|
||||
|
||||
if shared.cmd_opts.xformers or shared.cmd_opts.force_enable_xformers:
|
||||
|
|
|
|||
|
|
@ -57,7 +57,7 @@ def set_samplers():
|
|||
global samplers, samplers_for_img2img
|
||||
|
||||
hidden = set(opts.hide_samplers)
|
||||
hidden_img2img = set(opts.hide_samplers + ['PLMS', 'DPM fast', 'DPM adaptive'])
|
||||
hidden_img2img = set(opts.hide_samplers + ['PLMS'])
|
||||
|
||||
samplers = [x for x in all_samplers if x.name not in hidden]
|
||||
samplers_for_img2img = [x for x in all_samplers if x.name not in hidden_img2img]
|
||||
|
|
@ -365,16 +365,26 @@ class KDiffusionSampler:
|
|||
else:
|
||||
sigmas = self.model_wrap.get_sigmas(steps)
|
||||
|
||||
noise = noise * sigmas[steps - t_enc - 1]
|
||||
xi = x + noise
|
||||
|
||||
extra_params_kwargs = self.initialize(p)
|
||||
|
||||
sigma_sched = sigmas[steps - t_enc - 1:]
|
||||
xi = x + noise * sigma_sched[0]
|
||||
|
||||
extra_params_kwargs = self.initialize(p)
|
||||
if 'sigma_min' in inspect.signature(self.func).parameters:
|
||||
## last sigma is zero which isn't allowed by DPM Fast & Adaptive so taking value before last
|
||||
extra_params_kwargs['sigma_min'] = sigma_sched[-2]
|
||||
if 'sigma_max' in inspect.signature(self.func).parameters:
|
||||
extra_params_kwargs['sigma_max'] = sigma_sched[0]
|
||||
if 'n' in inspect.signature(self.func).parameters:
|
||||
extra_params_kwargs['n'] = len(sigma_sched) - 1
|
||||
if 'sigma_sched' in inspect.signature(self.func).parameters:
|
||||
extra_params_kwargs['sigma_sched'] = sigma_sched
|
||||
if 'sigmas' in inspect.signature(self.func).parameters:
|
||||
extra_params_kwargs['sigmas'] = sigma_sched
|
||||
|
||||
self.model_wrap_cfg.init_latent = x
|
||||
|
||||
return self.func(self.model_wrap_cfg, xi, sigma_sched, extra_args={'cond': conditioning, 'uncond': unconditional_conditioning, 'cond_scale': p.cfg_scale}, disable=False, callback=self.callback_state, **extra_params_kwargs)
|
||||
return self.func(self.model_wrap_cfg, xi, extra_args={'cond': conditioning, 'uncond': unconditional_conditioning, 'cond_scale': p.cfg_scale}, disable=False, callback=self.callback_state, **extra_params_kwargs)
|
||||
|
||||
|
||||
def sample(self, p, x, conditioning, unconditional_conditioning, steps=None):
|
||||
steps = steps or p.steps
|
||||
|
|
|
|||
|
|
@ -14,7 +14,7 @@ import modules.sd_models
|
|||
import modules.styles
|
||||
import modules.devices as devices
|
||||
from modules import sd_samplers
|
||||
from modules.hypernetwork import hypernetwork
|
||||
from modules.hypernetworks import hypernetwork
|
||||
from modules.paths import models_path, script_path, sd_path
|
||||
|
||||
sd_model_file = os.path.join(script_path, 'model.ckpt')
|
||||
|
|
@ -38,6 +38,7 @@ parser.add_argument("--always-batch-cond-uncond", action='store_true', help="dis
|
|||
parser.add_argument("--unload-gfpgan", action='store_true', help="does not do anything.")
|
||||
parser.add_argument("--precision", type=str, help="evaluate at this precision", choices=["full", "autocast"], default="autocast")
|
||||
parser.add_argument("--share", action='store_true', help="use share=True for gradio and make the UI accessible through their site (doesn't work for me but you might have better luck)")
|
||||
parser.add_argument("--ngrok", type=str, help="ngrok authtoken, alternative to gradio --share", default=None)
|
||||
parser.add_argument("--codeformer-models-path", type=str, help="Path to directory with codeformer model file(s).", default=os.path.join(models_path, 'Codeformer'))
|
||||
parser.add_argument("--gfpgan-models-path", type=str, help="Path to directory with GFPGAN model file(s).", default=os.path.join(models_path, 'GFPGAN'))
|
||||
parser.add_argument("--esrgan-models-path", type=str, help="Path to directory with ESRGAN model file(s).", default=os.path.join(models_path, 'ESRGAN'))
|
||||
|
|
|
|||
|
|
@ -52,6 +52,11 @@ if not cmd_opts.share and not cmd_opts.listen:
|
|||
gradio.utils.version_check = lambda: None
|
||||
gradio.utils.get_local_ip_address = lambda: '127.0.0.1'
|
||||
|
||||
if cmd_opts.ngrok != None:
|
||||
import modules.ngrok as ngrok
|
||||
print('ngrok authtoken detected, trying to connect...')
|
||||
ngrok.connect(cmd_opts.ngrok, cmd_opts.port if cmd_opts.port != None else 7860)
|
||||
|
||||
|
||||
def gr_show(visible=True):
|
||||
return {"visible": visible, "__type__": "update"}
|
||||
|
|
@ -430,7 +435,10 @@ def create_toprow(is_img2img):
|
|||
|
||||
with gr.Row():
|
||||
with gr.Column(scale=8):
|
||||
negative_prompt = gr.Textbox(label="Negative prompt", elem_id="negative_prompt", show_label=False, placeholder="Negative prompt", lines=2)
|
||||
with gr.Row():
|
||||
negative_prompt = gr.Textbox(label="Negative prompt", elem_id="negative_prompt", show_label=False, placeholder="Negative prompt", lines=2)
|
||||
with gr.Column(scale=1, elem_id="roll_col"):
|
||||
sh = gr.Button(elem_id="sh", visible=True)
|
||||
|
||||
with gr.Column(scale=1, elem_id="style_neg_col"):
|
||||
prompt_style2 = gr.Dropdown(label="Style 2", elem_id=f"{id_part}_style2_index", choices=[k for k, v in shared.prompt_styles.styles.items()], value=next(iter(shared.prompt_styles.styles.keys())), visible=len(shared.prompt_styles.styles) > 1)
|
||||
|
|
@ -550,16 +558,15 @@ def create_ui(wrap_gradio_gpu_call):
|
|||
button_id = "hidden_element" if shared.cmd_opts.hide_ui_dir_config else 'open_folder'
|
||||
open_txt2img_folder = gr.Button(folder_symbol, elem_id=button_id)
|
||||
|
||||
with gr.Row():
|
||||
do_make_zip = gr.Checkbox(label="Make Zip when Save?", value=False)
|
||||
with gr.Row():
|
||||
do_make_zip = gr.Checkbox(label="Make Zip when Save?", value=False)
|
||||
|
||||
with gr.Row():
|
||||
download_files = gr.File(None, file_count="multiple", interactive=False, show_label=False, visible=False)
|
||||
with gr.Row():
|
||||
download_files = gr.File(None, file_count="multiple", interactive=False, show_label=False, visible=False)
|
||||
|
||||
with gr.Group():
|
||||
html_info = gr.HTML()
|
||||
generation_info = gr.Textbox(visible=False)
|
||||
|
||||
|
||||
connect_reuse_seed(seed, reuse_seed, generation_info, dummy_component, is_subseed=False)
|
||||
connect_reuse_seed(subseed, reuse_subseed, generation_info, dummy_component, is_subseed=True)
|
||||
|
|
@ -740,17 +747,16 @@ def create_ui(wrap_gradio_gpu_call):
|
|||
button_id = "hidden_element" if shared.cmd_opts.hide_ui_dir_config else 'open_folder'
|
||||
open_img2img_folder = gr.Button(folder_symbol, elem_id=button_id)
|
||||
|
||||
with gr.Row():
|
||||
do_make_zip = gr.Checkbox(label="Make Zip when Save?", value=False)
|
||||
with gr.Row():
|
||||
do_make_zip = gr.Checkbox(label="Make Zip when Save?", value=False)
|
||||
|
||||
with gr.Row():
|
||||
download_files = gr.File(None, file_count="multiple", interactive=False, show_label=False, visible=False)
|
||||
with gr.Row():
|
||||
download_files = gr.File(None, file_count="multiple", interactive=False, show_label=False, visible=False)
|
||||
|
||||
with gr.Group():
|
||||
html_info = gr.HTML()
|
||||
generation_info = gr.Textbox(visible=False)
|
||||
|
||||
|
||||
connect_reuse_seed(seed, reuse_seed, generation_info, dummy_component, is_subseed=False)
|
||||
connect_reuse_seed(subseed, reuse_subseed, generation_info, dummy_component, is_subseed=True)
|
||||
|
||||
|
|
@ -1106,7 +1112,7 @@ def create_ui(wrap_gradio_gpu_call):
|
|||
)
|
||||
|
||||
create_hypernetwork.click(
|
||||
fn=modules.hypernetwork.ui.create_hypernetwork,
|
||||
fn=modules.hypernetworks.ui.create_hypernetwork,
|
||||
inputs=[
|
||||
new_hypernetwork_name,
|
||||
],
|
||||
|
|
@ -1159,7 +1165,7 @@ def create_ui(wrap_gradio_gpu_call):
|
|||
)
|
||||
|
||||
train_hypernetwork.click(
|
||||
fn=wrap_gradio_gpu_call(modules.hypernetwork.ui.train_hypernetwork, extra_outputs=[gr.update()]),
|
||||
fn=wrap_gradio_gpu_call(modules.hypernetworks.ui.train_hypernetwork, extra_outputs=[gr.update()]),
|
||||
_js="start_training_textual_inversion",
|
||||
inputs=[
|
||||
train_hypernetwork_name,
|
||||
|
|
|
|||
|
|
@ -11,7 +11,7 @@ import modules.scripts as scripts
|
|||
import gradio as gr
|
||||
|
||||
from modules import images
|
||||
from modules.hypernetwork import hypernetwork
|
||||
from modules.hypernetworks import hypernetwork
|
||||
from modules.processing import process_images, Processed, get_correct_sampler
|
||||
from modules.shared import opts, cmd_opts, state
|
||||
import modules.shared as shared
|
||||
|
|
|
|||
21
style.css
21
style.css
|
|
@ -2,6 +2,27 @@
|
|||
max-width: 100%;
|
||||
}
|
||||
|
||||
#txt2img_token_counter {
|
||||
height: 0px;
|
||||
}
|
||||
|
||||
#img2img_token_counter {
|
||||
height: 0px;
|
||||
}
|
||||
|
||||
#sh{
|
||||
min-width: 2em;
|
||||
min-height: 2em;
|
||||
max-width: 2em;
|
||||
max-height: 2em;
|
||||
flex-grow: 0;
|
||||
padding-left: 0.25em;
|
||||
padding-right: 0.25em;
|
||||
margin: 0.1em 0;
|
||||
opacity: 0%;
|
||||
cursor: default;
|
||||
}
|
||||
|
||||
.output-html p {margin: 0 0.5em;}
|
||||
|
||||
.row > *,
|
||||
|
|
|
|||
4
webui.py
4
webui.py
|
|
@ -29,7 +29,7 @@ from modules import devices
|
|||
from modules import modelloader
|
||||
from modules.paths import script_path
|
||||
from modules.shared import cmd_opts
|
||||
import modules.hypernetwork.hypernetwork
|
||||
import modules.hypernetworks.hypernetwork
|
||||
|
||||
modelloader.cleanup_models()
|
||||
modules.sd_models.setup_model()
|
||||
|
|
@ -83,7 +83,7 @@ modules.scripts.load_scripts(os.path.join(script_path, "scripts"))
|
|||
shared.sd_model = modules.sd_models.load_model()
|
||||
shared.opts.onchange("sd_model_checkpoint", wrap_queued_call(lambda: modules.sd_models.reload_model_weights(shared.sd_model)))
|
||||
|
||||
shared.opts.onchange("sd_hypernetwork", wrap_queued_call(lambda: modules.hypernetwork.hypernetwork.load_hypernetwork(shared.opts.sd_hypernetwork)))
|
||||
shared.opts.onchange("sd_hypernetwork", wrap_queued_call(lambda: modules.hypernetworks.hypernetwork.load_hypernetwork(shared.opts.sd_hypernetwork)))
|
||||
|
||||
|
||||
def webui():
|
||||
|
|
|
|||
Loading…
Reference in New Issue