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