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Merge branch 'master' into patch-1

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AUTOMATIC1111 2023-03-25 12:36:35 +03:00 committed by GitHub
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38 changed files with 748 additions and 797 deletions
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1
extensions-builtin/Lora/lora.py
View File

@ -178,6 +178,7 @@ def load_loras(names, multipliers=None):
def lora_forward(module, input, res):
input = devices.cond_cast_unet(input)
if len(loaded_loras) == 0:
return res

15
extensions-builtin/prompt-bracket-checker/javascript/prompt-bracket-checker.js
View File

@ -89,22 +89,15 @@ function checkBrackets(evt, textArea, counterElt) {
function setupBracketChecking(id_prompt, id_counter){
var textarea = gradioApp().querySelector("#" + id_prompt + " > label > textarea");
var counter = gradioApp().getElementById(id_counter)
textarea.addEventListener("input", function(evt){
checkBrackets(evt, textarea, counter)
});
}
var shadowRootLoaded = setInterval(function() {
var shadowRoot = document.querySelector('gradio-app').shadowRoot;
if(! shadowRoot) return false;
var shadowTextArea = shadowRoot.querySelectorAll('#txt2img_prompt > label > textarea');
if(shadowTextArea.length < 1) return false;
clearInterval(shadowRootLoaded);
onUiLoaded(function(){
setupBracketChecking('txt2img_prompt', 'txt2img_token_counter')
setupBracketChecking('txt2img_neg_prompt', 'txt2img_negative_token_counter')
setupBracketChecking('img2img_prompt', 'imgimg_token_counter')
setupBracketChecking('img2img_prompt', 'img2img_token_counter')
setupBracketChecking('img2img_neg_prompt', 'img2img_negative_token_counter')
}, 1000);
})

26
html/licenses.html
View File

@ -635,4 +635,30 @@ SOFTWARE.
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
</pre>
<h2><a href="https://github.com/explosion/curated-transformers/blob/main/LICENSE">Curated transformers</a></h2>
<small>The MPS workaround for nn.Linear on macOS 13.2.X is based on the MPS workaround for nn.Linear created by danieldk for Curated transformers</small>
<pre>
The MIT License (MIT)
Copyright (C) 2021 ExplosionAI GmbH
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in
all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
THE SOFTWARE.
</pre>

2
javascript/contextMenus.js
View File

@ -43,7 +43,7 @@ contextMenuInit = function(){
})
gradioApp().getRootNode().appendChild(contextMenu)
gradioApp().appendChild(contextMenu)
let menuWidth = contextMenu.offsetWidth + 4;
let menuHeight = contextMenu.offsetHeight + 4;

2
javascript/edit-attention.js
View File

@ -1,6 +1,6 @@
function keyupEditAttention(event){
let target = event.originalTarget || event.composedPath()[0];
if (!target.matches("[id*='_toprow'] textarea.gr-text-input[placeholder]")) return;
if (! target.matches("[id*='_toprow'] [id*='_prompt'] textarea")) return;
if (! (event.metaKey || event.ctrlKey)) return;
let isPlus = event.key == "ArrowUp"

38
javascript/extraNetworks.js
View File

@ -139,3 +139,41 @@ function extraNetworksShowMetadata(text){
popup(elem);
}
function requestGet(url, data, handler, errorHandler){
var xhr = new XMLHttpRequest();
var args = Object.keys(data).map(function(k){ return encodeURIComponent(k) + '=' + encodeURIComponent(data[k]) }).join('&')
xhr.open("GET", url + "?" + args, true);
xhr.onreadystatechange = function () {
if (xhr.readyState === 4) {
if (xhr.status === 200) {
try {
var js = JSON.parse(xhr.responseText);
handler(js)
} catch (error) {
console.error(error);
errorHandler()
}
} else{
errorHandler()
}
}
};
var js = JSON.stringify(data);
xhr.send(js);
}
function extraNetworksRequestMetadata(event, extraPage, cardName){
showError = function(){ extraNetworksShowMetadata("there was an error getting metadata"); }
requestGet("./sd_extra_networks/metadata", {"page": extraPage, "item": cardName}, function(data){
if(data && data.metadata){
extraNetworksShowMetadata(data.metadata)
} else{
showError()
}
}, showError)
event.stopPropagation()
}

11
javascript/hints.js
View File

@ -18,7 +18,7 @@ titles = {
"\u2199\ufe0f": "Read generation parameters from prompt or last generation if prompt is empty into user interface.",
"\u{1f4c2}": "Open images output directory",
"\u{1f4be}": "Save style",
"\u{1f5d1}": "Clear prompt",
"\u{1f5d1}\ufe0f": "Clear prompt",
"\u{1f4cb}": "Apply selected styles to current prompt",
"\u{1f4d2}": "Paste available values into the field",
"\u{1f3b4}": "Show extra networks",
@ -40,8 +40,7 @@ titles = {
"Inpaint at full resolution": "Upscale masked region to target resolution, do inpainting, downscale back and paste into original image",
"Denoising strength": "Determines how little respect the algorithm should have for image's content. At 0, nothing will change, and at 1 you'll get an unrelated image. With values below 1.0, processing will take less steps than the Sampling Steps slider specifies.",
"Denoising strength change factor": "In loopback mode, on each loop the denoising strength is multiplied by this value. <1 means decreasing variety so your sequence will converge on a fixed picture. >1 means increasing variety so your sequence will become more and more chaotic.",
"Skip": "Stop processing current image and continue processing.",
"Interrupt": "Stop processing images and return any results accumulated so far.",
"Save": "Write image to a directory (default - log/images) and generation parameters into csv file.",
@ -71,8 +70,10 @@ titles = {
"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.",
"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": "Process an image, use it as an input, repeat.",
"Loops": "How many times to repeat processing an image and using it as input for the next iteration",
"Loopback": "Performs img2img processing multiple times. Output images are used as input for the next loop.",
"Loops": "How many times to process an image. Each output is used as the input of the next loop. If set to 1, behavior will be as if this script were not used.",
"Final denoising strength": "The denoising strength for the final loop of each image in the batch.",
"Denoising strength curve": "The denoising curve controls the rate of denoising strength change each loop. Aggressive: Most of the change will happen towards the start of the loops. Linear: Change will be constant through all loops. Lazy: Most of the change will happen towards the end of the loops.",
"Style 1": "Style to apply; styles have components for both positive and negative prompts and apply to both",
"Style 2": "Style to apply; styles have components for both positive and negative prompts and apply to both",

62
javascript/imageviewer.js
View File

@ -50,7 +50,7 @@ function updateOnBackgroundChange() {
}
function modalImageSwitch(offset) {
var allgalleryButtons = gradioApp().querySelectorAll(".gallery-item.transition-all")
var allgalleryButtons = gradioApp().querySelectorAll(".gradio-gallery .thumbnail-item")
var galleryButtons = []
allgalleryButtons.forEach(function(elem) {
if (elem.parentElement.offsetParent) {
@ -59,7 +59,7 @@ function modalImageSwitch(offset) {
})
if (galleryButtons.length > 1) {
var allcurrentButtons = gradioApp().querySelectorAll(".gallery-item.transition-all.\\!ring-2")
var allcurrentButtons = gradioApp().querySelectorAll(".gradio-gallery .thumbnail-item.selected")
var currentButton = null
allcurrentButtons.forEach(function(elem) {
if (elem.parentElement.offsetParent) {
@ -136,37 +136,29 @@ function modalKeyHandler(event) {
}
}
function showGalleryImage() {
setTimeout(function() {
fullImg_preview = gradioApp().querySelectorAll('img.w-full.object-contain')
function setupImageForLightbox(e) {
if (e.dataset.modded)
return;
if (fullImg_preview != null) {
fullImg_preview.forEach(function function_name(e) {
if (e.dataset.modded)
return;
e.dataset.modded = true;
if(e && e.parentElement.tagName == 'DIV'){
e.style.cursor='pointer'
e.style.userSelect='none'
e.dataset.modded = true;
e.style.cursor='pointer'
e.style.userSelect='none'
var isFirefox = isFirefox = navigator.userAgent.toLowerCase().indexOf('firefox') > -1
var isFirefox = navigator.userAgent.toLowerCase().indexOf('firefox') > -1
// For Firefox, listening on click first switched to next image then shows the lightbox.
// If you know how to fix this without switching to mousedown event, please.
// For other browsers the event is click to make it possiblr to drag picture.
var event = isFirefox ? 'mousedown' : 'click'
// For Firefox, listening on click first switched to next image then shows the lightbox.
// If you know how to fix this without switching to mousedown event, please.
// For other browsers the event is click to make it possiblr to drag picture.
var event = isFirefox ? 'mousedown' : 'click'
e.addEventListener(event, function (evt) {
if(!opts.js_modal_lightbox || evt.button != 0) return;
modalZoomSet(gradioApp().getElementById('modalImage'), opts.js_modal_lightbox_initially_zoomed)
evt.preventDefault()
showModal(evt)
}, true);
}
});
}
e.addEventListener(event, function (evt) {
if(!opts.js_modal_lightbox || evt.button != 0) return;
modalZoomSet(gradioApp().getElementById('modalImage'), opts.js_modal_lightbox_initially_zoomed)
evt.preventDefault()
showModal(evt)
}, true);
}, 100);
}
function modalZoomSet(modalImage, enable) {
@ -199,21 +191,21 @@ function modalTileImageToggle(event) {
}
function galleryImageHandler(e) {
if (e && e.parentElement.tagName == 'BUTTON') {
//if (e && e.parentElement.tagName == 'BUTTON') {
e.onclick = showGalleryImage;
}
//}
}
onUiUpdate(function() {
fullImg_preview = gradioApp().querySelectorAll('img.w-full')
fullImg_preview = gradioApp().querySelectorAll('.gradio-gallery > div > img')
if (fullImg_preview != null) {
fullImg_preview.forEach(galleryImageHandler);
fullImg_preview.forEach(setupImageForLightbox);
}
updateOnBackgroundChange();
})
document.addEventListener("DOMContentLoaded", function() {
const modalFragment = document.createDocumentFragment();
//const modalFragment = document.createDocumentFragment();
const modal = document.createElement('div')
modal.onclick = closeModal;
modal.id = "lightboxModal";
@ -277,9 +269,9 @@ document.addEventListener("DOMContentLoaded", function() {
modal.appendChild(modalNext)
gradioApp().appendChild(modal)
gradioApp().getRootNode().appendChild(modal)
document.body.appendChild(modalFragment);
document.body.appendChild(modal);
});

67
javascript/progressbar.js
View File

@ -1,78 +1,13 @@
// code related to showing and updating progressbar shown as the image is being made
galleries = {}
storedGallerySelections = {}
galleryObservers = {}
function rememberGallerySelection(id_gallery){
storedGallerySelections[id_gallery] = getGallerySelectedIndex(id_gallery)
}
function getGallerySelectedIndex(id_gallery){
let galleryButtons = gradioApp().querySelectorAll('#'+id_gallery+' .gallery-item')
let galleryBtnSelected = gradioApp().querySelector('#'+id_gallery+' .gallery-item.\\!ring-2')
let currentlySelectedIndex = -1
galleryButtons.forEach(function(v, i){ if(v==galleryBtnSelected) { currentlySelectedIndex = i } })
return currentlySelectedIndex
}
// this is a workaround for https://github.com/gradio-app/gradio/issues/2984
function check_gallery(id_gallery){
let gallery = gradioApp().getElementById(id_gallery)
// if gallery has no change, no need to setting up observer again.
if (gallery && galleries[id_gallery] !== gallery){
galleries[id_gallery] = gallery;
if(galleryObservers[id_gallery]){
galleryObservers[id_gallery].disconnect();
}
storedGallerySelections[id_gallery] = -1
galleryObservers[id_gallery] = new MutationObserver(function (){
let galleryButtons = gradioApp().querySelectorAll('#'+id_gallery+' .gallery-item')
let galleryBtnSelected = gradioApp().querySelector('#'+id_gallery+' .gallery-item.\\!ring-2')
let currentlySelectedIndex = getGallerySelectedIndex(id_gallery)
prevSelectedIndex = storedGallerySelections[id_gallery]
storedGallerySelections[id_gallery] = -1
if (prevSelectedIndex !== -1 && galleryButtons.length>prevSelectedIndex && !galleryBtnSelected) {
// automatically re-open previously selected index (if exists)
activeElement = gradioApp().activeElement;
let scrollX = window.scrollX;
let scrollY = window.scrollY;
galleryButtons[prevSelectedIndex].click();
showGalleryImage();
// When the gallery button is clicked, it gains focus and scrolls itself into view
// We need to scroll back to the previous position
setTimeout(function (){
window.scrollTo(scrollX, scrollY);
}, 50);
if(activeElement){
// i fought this for about an hour; i don't know why the focus is lost or why this helps recover it
// if someone has a better solution please by all means
setTimeout(function (){
activeElement.focus({
preventScroll: true // Refocus the element that was focused before the gallery was opened without scrolling to it
})
}, 1);
}
}
})
galleryObservers[id_gallery].observe( gallery, { childList:true, subtree:false })
}
}
onUiUpdate(function(){
check_gallery('txt2img_gallery')
check_gallery('img2img_gallery')
})
function request(url, data, handler, errorHandler){
var xhr = new XMLHttpRequest();
var url = url;

3
javascript/ui.js
View File

@ -86,7 +86,7 @@ function get_tab_index(tabId){
var res = 0
gradioApp().getElementById(tabId).querySelector('div').querySelectorAll('button').forEach(function(button, i){
if(button.className.indexOf('bg-white') != -1)
if(button.className.indexOf('selected') != -1)
res = i
})
@ -255,7 +255,6 @@ onUiUpdate(function(){
}
prompt.parentElement.insertBefore(counter, prompt)
counter.classList.add("token-counter")
prompt.parentElement.style.position = "relative"
promptTokecountUpdateFuncs[id] = function(){ update_token_counter(id_button); }

6
launch.py
View File

@ -14,7 +14,7 @@ parser.add_argument("--data-dir", type=str, default=os.path.dirname(os.path.real
args, _ = parser.parse_known_args(sys.argv)
script_path = os.path.dirname(__file__)
data_path = os.getcwd()
data_path = args.data_dir
dir_repos = "repositories"
dir_extensions = "extensions"
@ -24,6 +24,8 @@ index_url = os.environ.get('INDEX_URL', "")
stored_commit_hash = None
skip_install = False
if 'GRADIO_ANALYTICS_ENABLED' not in os.environ:
os.environ['GRADIO_ANALYTICS_ENABLED'] = 'False'
def check_python_version():
is_windows = platform.system() == "Windows"
@ -231,7 +233,7 @@ def run_extensions_installers(settings_file):
return
for dirname_extension in list_extensions(settings_file):
run_extension_installer(os.path.join(dir_extensions, dirname_extension))
run_extension_installer(os.path.join(data_path, dir_extensions, dirname_extension))
def prepare_environment():

14
modules/api/api.py
View File

@ -18,7 +18,7 @@ from modules.textual_inversion.textual_inversion import create_embedding, train_
from modules.textual_inversion.preprocess import preprocess
from modules.hypernetworks.hypernetwork import create_hypernetwork, train_hypernetwork
from PIL import PngImagePlugin,Image
from modules.sd_models import checkpoints_list
from modules.sd_models import checkpoints_list, unload_model_weights, reload_model_weights
from modules.sd_models_config import find_checkpoint_config_near_filename
from modules.realesrgan_model import get_realesrgan_models
from modules import devices
@ -150,6 +150,8 @@ class Api:
self.add_api_route("/sdapi/v1/train/embedding", self.train_embedding, methods=["POST"], response_model=TrainResponse)
self.add_api_route("/sdapi/v1/train/hypernetwork", self.train_hypernetwork, methods=["POST"], response_model=TrainResponse)
self.add_api_route("/sdapi/v1/memory", self.get_memory, methods=["GET"], response_model=MemoryResponse)
self.add_api_route("/sdapi/v1/unload-checkpoint", self.unloadapi, methods=["POST"])
self.add_api_route("/sdapi/v1/reload-checkpoint", self.reloadapi, methods=["POST"])
self.add_api_route("/sdapi/v1/scripts", self.get_scripts_list, methods=["GET"], response_model=ScriptsList)
def add_api_route(self, path: str, endpoint, **kwargs):
@ -412,6 +414,16 @@ class Api:
return {}
def unloadapi(self):
unload_model_weights()
return {}
def reloadapi(self):
reload_model_weights()
return {}
def skip(self):
shared.state.skip()

7
modules/generation_parameters_copypaste.py
View File

@ -401,9 +401,14 @@ def connect_paste(button, paste_fields, input_comp, override_settings_component,
button.click(
fn=paste_func,
_js=f"recalculate_prompts_{tabname}",
inputs=[input_comp],
outputs=[x[0] for x in paste_fields],
)
button.click(
fn=None,
_js=f"recalculate_prompts_{tabname}",
inputs=[],
outputs=[],
)

4
modules/images.py
View File

@ -645,6 +645,8 @@ Steps: {json_info["steps"]}, Sampler: {sampler}, CFG scale: {json_info["scale"]}
def image_data(data):
import gradio as gr
try:
image = Image.open(io.BytesIO(data))
textinfo, _ = read_info_from_image(image)
@ -660,7 +662,7 @@ def image_data(data):
except Exception:
pass
return '', None
return gr.update(), None
def flatten(img, bgcolor):

9
modules/mac_specific.py
View File

@ -1,4 +1,5 @@
import torch
import platform
from modules import paths
from modules.sd_hijack_utils import CondFunc
from packaging import version
@ -32,6 +33,10 @@ if has_mps:
# MPS fix for randn in torchsde
CondFunc('torchsde._brownian.brownian_interval._randn', lambda _, size, dtype, device, seed: torch.randn(size, dtype=dtype, device=torch.device("cpu"), generator=torch.Generator(torch.device("cpu")).manual_seed(int(seed))).to(device), lambda _, size, dtype, device, seed: device.type == 'mps')
if platform.mac_ver()[0].startswith("13.2."):
# MPS workaround for https://github.com/pytorch/pytorch/issues/95188, thanks to danieldk (https://github.com/explosion/curated-transformers/pull/124)
CondFunc('torch.nn.functional.linear', lambda _, input, weight, bias: (torch.matmul(input, weight.t()) + bias) if bias is not None else torch.matmul(input, weight.t()), lambda _, input, weight, bias: input.numel() > 10485760)
if version.parse(torch.__version__) < version.parse("1.13"):
# PyTorch 1.13 doesn't need these fixes but unfortunately is slower and has regressions that prevent training from working
@ -49,4 +54,6 @@ if has_mps:
CondFunc('torch.cumsum', cumsum_fix_func, None)
CondFunc('torch.Tensor.cumsum', cumsum_fix_func, None)
CondFunc('torch.narrow', lambda orig_func, *args, **kwargs: orig_func(*args, **kwargs).clone(), None)
if version.parse(torch.__version__) == version.parse("2.0"):
# MPS workaround for https://github.com/pytorch/pytorch/issues/96113
CondFunc('torch.nn.functional.layer_norm', lambda orig_func, x, normalized_shape, weight, bias, eps, **kwargs: orig_func(x.float(), normalized_shape, weight.float() if weight is not None else None, bias.float() if bias is not None else bias, eps).to(x.dtype), lambda *args, **kwargs: len(args) == 6)

2
modules/modelloader.py
View File

@ -4,7 +4,6 @@ import shutil
import importlib
from urllib.parse import urlparse
from basicsr.utils.download_util import load_file_from_url
from modules import shared
from modules.upscaler import Upscaler, UpscalerLanczos, UpscalerNearest, UpscalerNone
from modules.paths import script_path, models_path
@ -59,6 +58,7 @@ def load_models(model_path: str, model_url: str = None, command_path: str = None
if model_url is not None and len(output) == 0:
if download_name is not None:
from basicsr.utils.download_util import load_file_from_url
dl = load_file_from_url(model_url, model_path, True, download_name)
output.append(dl)
else:

16
modules/processing.py
View File

@ -689,6 +689,22 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
image.info["parameters"] = text
output_images.append(image)
if hasattr(p, 'mask_for_overlay') and p.mask_for_overlay:
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')
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")
if opts.save_mask_composite:
images.save_image(image_mask_composite, p.outpath_samples, "", seeds[i], prompts[i], opts.samples_format, info=infotext(n, i), p=p, suffix="-mask-composite")
if opts.return_mask:
output_images.append(image_mask)
if opts.return_mask_composite:
output_images.append(image_mask_composite)
del x_samples_ddim
devices.torch_gc()

24
modules/scripts.py
View File

@ -239,7 +239,15 @@ def load_scripts():
elif issubclass(script_class, scripts_postprocessing.ScriptPostprocessing):
postprocessing_scripts_data.append(ScriptClassData(script_class, scriptfile.path, scriptfile.basedir, module))
for scriptfile in sorted(scripts_list):
def orderby(basedir):
# 1st webui, 2nd extensions-builtin, 3rd extensions
priority = {os.path.join(paths.script_path, "extensions-builtin"):1, paths.script_path:0}
for key in priority:
if basedir.startswith(key):
return priority[key]
return 9999
for scriptfile in sorted(scripts_list, key=lambda x: [orderby(x.basedir), x]):
try:
if scriptfile.basedir != paths.script_path:
sys.path = [scriptfile.basedir] + sys.path
@ -513,6 +521,18 @@ def reload_scripts():
scripts_postproc = scripts_postprocessing.ScriptPostprocessingRunner()
def add_classes_to_gradio_component(comp):
"""
this adds gradio-* to the component for css styling (ie gradio-button to gr.Button), as well as some others
"""
comp.elem_classes = ["gradio-" + comp.get_block_name(), *(comp.elem_classes or [])]
if getattr(comp, 'multiselect', False):
comp.elem_classes.append('multiselect')
def IOComponent_init(self, *args, **kwargs):
if scripts_current is not None:
scripts_current.before_component(self, **kwargs)
@ -521,6 +541,8 @@ def IOComponent_init(self, *args, **kwargs):
res = original_IOComponent_init(self, *args, **kwargs)
add_classes_to_gradio_component(self)
script_callbacks.after_component_callback(self, **kwargs)
if scripts_current is not None:

2
modules/scripts_postprocessing.py
View File

@ -109,7 +109,7 @@ class ScriptPostprocessingRunner:
inputs = []
for script in self.scripts_in_preferred_order():
with gr.Box() as group:
with gr.Row() as group:
self.create_script_ui(script, inputs)
script.group = group

4
modules/sd_hijack_optimizations.py
View File

@ -337,7 +337,7 @@ def xformers_attention_forward(self, x, context=None, mask=None):
dtype = q.dtype
if shared.opts.upcast_attn:
q, k = q.float(), k.float()
q, k, v = q.float(), k.float(), v.float()
out = xformers.ops.memory_efficient_attention(q, k, v, attn_bias=None, op=get_xformers_flash_attention_op(q, k, v))
@ -372,7 +372,7 @@ def scaled_dot_product_attention_forward(self, x, context=None, mask=None):
dtype = q.dtype
if shared.opts.upcast_attn:
q, k = q.float(), k.float()
q, k, v = q.float(), k.float(), v.float()
# the output of sdp = (batch, num_heads, seq_len, head_dim)
hidden_states = torch.nn.functional.scaled_dot_product_attention(

2
modules/sd_hijack_unet.py
View File

@ -67,7 +67,7 @@ def hijack_ddpm_edit():
unet_needs_upcast = lambda *args, **kwargs: devices.unet_needs_upcast
CondFunc('ldm.models.diffusion.ddpm.LatentDiffusion.apply_model', apply_model, unet_needs_upcast)
CondFunc('ldm.modules.diffusionmodules.openaimodel.timestep_embedding', lambda orig_func, timesteps, *args, **kwargs: orig_func(timesteps, *args, **kwargs).to(torch.float32 if timesteps.dtype == torch.int64 else devices.dtype_unet), unet_needs_upcast)
if version.parse(torch.__version__) <= version.parse("1.13.1"):
if version.parse(torch.__version__) <= version.parse("1.13.2") or torch.cuda.is_available():
CondFunc('ldm.modules.diffusionmodules.util.GroupNorm32.forward', lambda orig_func, self, *args, **kwargs: orig_func(self.float(), *args, **kwargs), unet_needs_upcast)
CondFunc('ldm.modules.attention.GEGLU.forward', lambda orig_func, self, x: orig_func(self.float(), x.float()).to(devices.dtype_unet), unet_needs_upcast)
CondFunc('open_clip.transformer.ResidualAttentionBlock.__init__', lambda orig_func, *args, **kwargs: kwargs.update({'act_layer': GELUHijack}) and False or orig_func(*args, **kwargs), lambda _, *args, **kwargs: kwargs.get('act_layer') is None or kwargs['act_layer'] == torch.nn.GELU)

26
modules/sd_models.py
View File

@ -178,7 +178,7 @@ def select_checkpoint():
return checkpoint_info
chckpoint_dict_replacements = {
checkpoint_dict_replacements = {
'cond_stage_model.transformer.embeddings.': 'cond_stage_model.transformer.text_model.embeddings.',
'cond_stage_model.transformer.encoder.': 'cond_stage_model.transformer.text_model.encoder.',
'cond_stage_model.transformer.final_layer_norm.': 'cond_stage_model.transformer.text_model.final_layer_norm.',
@ -186,7 +186,7 @@ chckpoint_dict_replacements = {
def transform_checkpoint_dict_key(k):
for text, replacement in chckpoint_dict_replacements.items():
for text, replacement in checkpoint_dict_replacements.items():
if k.startswith(text):
k = replacement + k[len(text):]
@ -494,7 +494,7 @@ def reload_model_weights(sd_model=None, info=None):
if sd_model is None or checkpoint_config != sd_model.used_config:
del sd_model
checkpoints_loaded.clear()
load_model(checkpoint_info, already_loaded_state_dict=state_dict, time_taken_to_load_state_dict=timer.records["load weights from disk"])
load_model(checkpoint_info, already_loaded_state_dict=state_dict)
return shared.sd_model
try:
@ -517,3 +517,23 @@ def reload_model_weights(sd_model=None, info=None):
print(f"Weights loaded in {timer.summary()}.")
return sd_model
def unload_model_weights(sd_model=None, info=None):
from modules import lowvram, devices, sd_hijack
timer = Timer()
if shared.sd_model:
# shared.sd_model.cond_stage_model.to(devices.cpu)
# shared.sd_model.first_stage_model.to(devices.cpu)
shared.sd_model.to(devices.cpu)
sd_hijack.model_hijack.undo_hijack(shared.sd_model)
shared.sd_model = None
sd_model = None
gc.collect()
devices.torch_gc()
torch.cuda.empty_cache()
print(f"Unloaded weights {timer.summary()}.")
return sd_model

7
modules/shared.py
View File

@ -107,7 +107,8 @@ parser.add_argument("--cors-allow-origins-regex", type=str, help="Allowed CORS o
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("--server-name", type=str, help="Sets hostname of server", default=None)
parser.add_argument("--gradio-queue", action='store_true', help="Uses gradio queue; experimental option; breaks restart UI button")
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("--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-download-sd-model", action='store_true', help="don't download SD1.5 model even if no model is found in --ckpt-dir", default=False)
@ -332,6 +333,8 @@ options_templates.update(options_section(('saving-images', "Saving images/grids"
"save_images_before_face_restoration": OptionInfo(False, "Save a copy of image before doing face restoration."),
"save_images_before_highres_fix": OptionInfo(False, "Save a copy of image before applying highres fix."),
"save_images_before_color_correction": OptionInfo(False, "Save a copy of image before applying color correction to img2img results"),
"save_mask": OptionInfo(False, "For inpainting, save a copy of the greyscale mask"),
"save_mask_composite": OptionInfo(False, "For inpainting, save a masked composite"),
"jpeg_quality": OptionInfo(80, "Quality for saved jpeg images", gr.Slider, {"minimum": 1, "maximum": 100, "step": 1}),
"webp_lossless": OptionInfo(False, "Use lossless compression for webp images"),
"export_for_4chan": OptionInfo(True, "If the saved image file size is above the limit, or its either width or height are above the limit, save a downscaled copy as JPG"),
@ -454,6 +457,8 @@ options_templates.update(options_section(('extra_networks', "Extra Networks"), {
options_templates.update(options_section(('ui', "User interface"), {
"return_grid": OptionInfo(True, "Show grid in results for web"),
"return_mask": OptionInfo(False, "For inpainting, include the greyscale mask in results for web"),
"return_mask_composite": OptionInfo(False, "For inpainting, include masked composite in results for web"),
"do_not_show_images": OptionInfo(False, "Do not show any images in results for web"),
"add_model_hash_to_info": OptionInfo(True, "Add model hash to generation information"),
"add_model_name_to_info": OptionInfo(True, "Add model name to generation information"),

6
modules/textual_inversion/textual_inversion.py
View File

@ -152,7 +152,11 @@ class EmbeddingDatabase:
name = data.get('name', name)
else:
data = extract_image_data_embed(embed_image)
name = data.get('name', name)
if data:
name = data.get('name', name)
else:
# if data is None, means this is not an embeding, just a preview image
return
elif ext in ['.BIN', '.PT']:
data = torch.load(path, map_location="cpu")
elif ext in ['.SAFETENSORS']:

71
modules/ui.py
View File

@ -20,7 +20,7 @@ from PIL import Image, PngImagePlugin
from modules.call_queue import wrap_gradio_gpu_call, wrap_queued_call, wrap_gradio_call
from modules import sd_hijack, sd_models, localization, script_callbacks, ui_extensions, deepbooru, sd_vae, extra_networks, postprocessing, ui_components, ui_common, ui_postprocessing
from modules.ui_components import FormRow, FormGroup, ToolButton, FormHTML
from modules.ui_components import FormRow, FormColumn, FormGroup, ToolButton, FormHTML
from modules.paths import script_path, data_path
from modules.shared import opts, cmd_opts, restricted_opts
@ -89,7 +89,7 @@ paste_symbol = '\u2199\ufe0f' # ↙
refresh_symbol = '\U0001f504' # 🔄
save_style_symbol = '\U0001f4be' # 💾
apply_style_symbol = '\U0001f4cb' # 📋
clear_prompt_symbol = '\U0001F5D1' # 🗑️
clear_prompt_symbol = '\U0001f5d1\ufe0f' # 🗑️
extra_networks_symbol = '\U0001F3B4' # 🎴
switch_values_symbol = '\U000021C5' # ⇅
@ -179,14 +179,13 @@ def interrogate_deepbooru(image):
def create_seed_inputs(target_interface):
with FormRow(elem_id=target_interface + '_seed_row'):
with FormRow(elem_id=target_interface + '_seed_row', variant="compact"):
seed = (gr.Textbox if cmd_opts.use_textbox_seed else gr.Number)(label='Seed', value=-1, elem_id=target_interface + '_seed')
seed.style(container=False)
random_seed = gr.Button(random_symbol, elem_id=target_interface + '_random_seed')
reuse_seed = gr.Button(reuse_symbol, elem_id=target_interface + '_reuse_seed')
random_seed = ToolButton(random_symbol, elem_id=target_interface + '_random_seed')
reuse_seed = ToolButton(reuse_symbol, elem_id=target_interface + '_reuse_seed')
with gr.Group(elem_id=target_interface + '_subseed_show_box'):
seed_checkbox = gr.Checkbox(label='Extra', elem_id=target_interface + '_subseed_show', value=False)
seed_checkbox = gr.Checkbox(label='Extra', elem_id=target_interface + '_subseed_show', value=False)
# Components to show/hide based on the 'Extra' checkbox
seed_extras = []
@ -195,8 +194,8 @@ def create_seed_inputs(target_interface):
seed_extras.append(seed_extra_row_1)
subseed = gr.Number(label='Variation seed', value=-1, elem_id=target_interface + '_subseed')
subseed.style(container=False)
random_subseed = gr.Button(random_symbol, elem_id=target_interface + '_random_subseed')
reuse_subseed = gr.Button(reuse_symbol, elem_id=target_interface + '_reuse_subseed')
random_subseed = ToolButton(random_symbol, elem_id=target_interface + '_random_subseed')
reuse_subseed = ToolButton(reuse_symbol, elem_id=target_interface + '_reuse_subseed')
subseed_strength = gr.Slider(label='Variation strength', value=0.0, minimum=0, maximum=1, step=0.01, elem_id=target_interface + '_subseed_strength')
with FormRow(visible=False) as seed_extra_row_2:
@ -291,19 +290,19 @@ def create_toprow(is_img2img):
with gr.Row():
with gr.Column(scale=80):
with gr.Row():
negative_prompt = gr.Textbox(label="Negative prompt", elem_id=f"{id_part}_neg_prompt", show_label=False, lines=2, placeholder="Negative prompt (press Ctrl+Enter or Alt+Enter to generate)")
negative_prompt = gr.Textbox(label="Negative prompt", elem_id=f"{id_part}_neg_prompt", show_label=False, lines=3, placeholder="Negative prompt (press Ctrl+Enter or Alt+Enter to generate)")
button_interrogate = None
button_deepbooru = None
if is_img2img:
with gr.Column(scale=1, elem_id="interrogate_col"):
with gr.Column(scale=1, elem_classes="interrogate-col"):
button_interrogate = gr.Button('Interrogate\nCLIP', elem_id="interrogate")
button_deepbooru = gr.Button('Interrogate\nDeepBooru', elem_id="deepbooru")
with gr.Column(scale=1, elem_id=f"{id_part}_actions_column"):
with gr.Row(elem_id=f"{id_part}_generate_box"):
interrupt = gr.Button('Interrupt', elem_id=f"{id_part}_interrupt")
skip = gr.Button('Skip', elem_id=f"{id_part}_skip")
with gr.Row(elem_id=f"{id_part}_generate_box", elem_classes="generate-box"):
interrupt = gr.Button('Interrupt', elem_id=f"{id_part}_interrupt", elem_classes="generate-box-interrupt")
skip = gr.Button('Skip', elem_id=f"{id_part}_skip", elem_classes="generate-box-skip")
submit = gr.Button('Generate', elem_id=f"{id_part}_generate", variant='primary')
skip.click(
@ -325,9 +324,9 @@ def create_toprow(is_img2img):
prompt_style_apply = ToolButton(value=apply_style_symbol, elem_id=f"{id_part}_style_apply")
save_style = ToolButton(value=save_style_symbol, elem_id=f"{id_part}_style_create")
token_counter = gr.HTML(value="<span></span>", elem_id=f"{id_part}_token_counter")
token_counter = gr.HTML(value="<span>0/75</span>", elem_id=f"{id_part}_token_counter", elem_classes=["token-counter"])
token_button = gr.Button(visible=False, elem_id=f"{id_part}_token_button")
negative_token_counter = gr.HTML(value="<span></span>", elem_id=f"{id_part}_negative_token_counter")
negative_token_counter = gr.HTML(value="<span>0/75</span>", elem_id=f"{id_part}_negative_token_counter", elem_classes=["token-counter"])
negative_token_button = gr.Button(visible=False, elem_id=f"{id_part}_negative_token_button")
clear_prompt_button.click(
@ -479,7 +478,9 @@ def create_ui():
width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="txt2img_width")
height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="txt2img_height")
res_switch_btn = ToolButton(value=switch_values_symbol, elem_id="txt2img_res_switch_btn")
with gr.Column(elem_id="txt2img_dimensions_row", scale=1, elem_classes="dimensions-tools"):
res_switch_btn = ToolButton(value=switch_values_symbol, elem_id="txt2img_res_switch_btn")
if opts.dimensions_and_batch_together:
with gr.Column(elem_id="txt2img_column_batch"):
batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1, elem_id="txt2img_batch_count")
@ -492,7 +493,7 @@ def create_ui():
seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox = create_seed_inputs('txt2img')
elif category == "checkboxes":
with FormRow(elem_id="txt2img_checkboxes", variant="compact"):
with FormRow(elem_classes="checkboxes-row", variant="compact"):
restore_faces = gr.Checkbox(label='Restore faces', value=False, visible=len(shared.face_restorers) > 1, elem_id="txt2img_restore_faces")
tiling = gr.Checkbox(label='Tiling', value=False, elem_id="txt2img_tiling")
enable_hr = gr.Checkbox(label='Hires. fix', value=False, elem_id="txt2img_enable_hr")
@ -586,7 +587,7 @@ def create_ui():
txt2img_prompt.submit(**txt2img_args)
submit.click(**txt2img_args)
res_switch_btn.click(lambda w, h: (h, w), inputs=[width, height], outputs=[width, height])
res_switch_btn.click(lambda w, h: (h, w), inputs=[width, height], outputs=[width, height], show_progress=False)
txt_prompt_img.change(
fn=modules.images.image_data,
@ -757,7 +758,9 @@ def create_ui():
width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="img2img_width")
height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="img2img_height")
res_switch_btn = ToolButton(value=switch_values_symbol, elem_id="img2img_res_switch_btn")
with gr.Column(elem_id="img2img_dimensions_row", scale=1, elem_classes="dimensions-tools"):
res_switch_btn = ToolButton(value=switch_values_symbol, elem_id="img2img_res_switch_btn")
if opts.dimensions_and_batch_together:
with gr.Column(elem_id="img2img_column_batch"):
batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1, elem_id="img2img_batch_count")
@ -774,7 +777,7 @@ def create_ui():
seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox = create_seed_inputs('img2img')
elif category == "checkboxes":
with FormRow(elem_id="img2img_checkboxes", variant="compact"):
with FormRow(elem_classes="checkboxes-row", variant="compact"):
restore_faces = gr.Checkbox(label='Restore faces', value=False, visible=len(shared.face_restorers) > 1, elem_id="img2img_restore_faces")
tiling = gr.Checkbox(label='Tiling', value=False, elem_id="img2img_tiling")
@ -904,7 +907,7 @@ def create_ui():
img2img_prompt.submit(**img2img_args)
submit.click(**img2img_args)
res_switch_btn.click(lambda w, h: (h, w), inputs=[width, height], outputs=[width, height])
res_switch_btn.click(lambda w, h: (h, w), inputs=[width, height], outputs=[width, height], show_progress=False)
img2img_interrogate.click(
fn=lambda *args: process_interrogate(interrogate, *args),
@ -1491,11 +1494,33 @@ def create_ui():
request_notifications = gr.Button(value='Request browser notifications', elem_id="request_notifications")
download_localization = gr.Button(value='Download localization template', elem_id="download_localization")
reload_script_bodies = gr.Button(value='Reload custom script bodies (No ui updates, No restart)', variant='secondary', elem_id="settings_reload_script_bodies")
with gr.Row():
unload_sd_model = gr.Button(value='Unload SD checkpoint to free VRAM', elem_id="sett_unload_sd_model")
reload_sd_model = gr.Button(value='Reload the last SD checkpoint back into VRAM', elem_id="sett_reload_sd_model")
with gr.TabItem("Licenses"):
gr.HTML(shared.html("licenses.html"), elem_id="licenses")
gr.Button(value="Show all pages", elem_id="settings_show_all_pages")
def unload_sd_weights():
modules.sd_models.unload_model_weights()
def reload_sd_weights():
modules.sd_models.reload_model_weights()
unload_sd_model.click(
fn=unload_sd_weights,
inputs=[],
outputs=[]
)
reload_sd_model.click(
fn=reload_sd_weights,
inputs=[],
outputs=[]
)
request_notifications.click(
fn=lambda: None,
@ -1598,11 +1623,13 @@ def create_ui():
for i, k, item in quicksettings_list:
component = component_dict[k]
info = opts.data_labels[k]
component.change(
fn=lambda value, k=k: run_settings_single(value, key=k),
inputs=[component],
outputs=[component, text_settings],
show_progress=info.refresh is not None,
)
text_settings.change(

5
modules/ui_common.py
View File

@ -129,8 +129,8 @@ Requested path was: {f}
generation_info = None
with gr.Column():
with gr.Row(elem_id=f"image_buttons_{tabname}"):
open_folder_button = gr.Button(folder_symbol, elem_id="hidden_element" if shared.cmd_opts.hide_ui_dir_config else f'open_folder_{tabname}')
with gr.Row(elem_id=f"image_buttons_{tabname}", elem_classes="image-buttons"):
open_folder_button = gr.Button(folder_symbol, visible=not shared.cmd_opts.hide_ui_dir_config)
if tabname != "extras":
save = gr.Button('Save', elem_id=f'save_{tabname}')
@ -160,6 +160,7 @@ Requested path was: {f}
_js="function(x, y, z){ return [x, y, selected_gallery_index()] }",
inputs=[generation_info, html_info, html_info],
outputs=[html_info, html_info],
show_progress=False,
)
save.click(

42
modules/ui_components.py
View File

@ -1,55 +1,61 @@
import gradio as gr
class ToolButton(gr.Button, gr.components.FormComponent):
class FormComponent:
def get_expected_parent(self):
return gr.components.Form
gr.Dropdown.get_expected_parent = FormComponent.get_expected_parent
class ToolButton(FormComponent, gr.Button):
"""Small button with single emoji as text, fits inside gradio forms"""
def __init__(self, **kwargs):
super().__init__(variant="tool", **kwargs)
def __init__(self, *args, **kwargs):
classes = kwargs.pop("elem_classes", [])
super().__init__(*args, elem_classes=["tool", *classes], **kwargs)
def get_block_name(self):
return "button"
class ToolButtonTop(gr.Button, gr.components.FormComponent):
"""Small button with single emoji as text, with extra margin at top, fits inside gradio forms"""
def __init__(self, **kwargs):
super().__init__(variant="tool-top", **kwargs)
def get_block_name(self):
return "button"
class FormRow(gr.Row, gr.components.FormComponent):
class FormRow(FormComponent, gr.Row):
"""Same as gr.Row but fits inside gradio forms"""
def get_block_name(self):
return "row"
class FormGroup(gr.Group, gr.components.FormComponent):
class FormColumn(FormComponent, gr.Column):
"""Same as gr.Column but fits inside gradio forms"""
def get_block_name(self):
return "column"
class FormGroup(FormComponent, gr.Group):
"""Same as gr.Row but fits inside gradio forms"""
def get_block_name(self):
return "group"
class FormHTML(gr.HTML, gr.components.FormComponent):
class FormHTML(FormComponent, gr.HTML):
"""Same as gr.HTML but fits inside gradio forms"""
def get_block_name(self):
return "html"
class FormColorPicker(gr.ColorPicker, gr.components.FormComponent):
class FormColorPicker(FormComponent, gr.ColorPicker):
"""Same as gr.ColorPicker but fits inside gradio forms"""
def get_block_name(self):
return "colorpicker"
class DropdownMulti(gr.Dropdown):
class DropdownMulti(FormComponent, gr.Dropdown):
"""Same as gr.Dropdown but always multiselect"""
def __init__(self, **kwargs):
super().__init__(multiselect=True, **kwargs)

15
modules/ui_extensions.py
View File

@ -1,6 +1,5 @@
import json
import os.path
import shutil
import sys
import time
import traceback
@ -141,22 +140,20 @@ def install_extension_from_url(dirname, url):
try:
shutil.rmtree(tmpdir, True)
repo = git.Repo.clone_from(url, tmpdir)
repo.remote().fetch()
with git.Repo.clone_from(url, tmpdir) as repo:
repo.remote().fetch()
for submodule in repo.submodules:
submodule.update()
try:
os.rename(tmpdir, target_dir)
except OSError as err:
# TODO what does this do on windows? I think it'll be a different error code but I don't have a system to check it
# Shouldn't cause any new issues at least but we probably want to handle it there too.
if err.errno == errno.EXDEV:
# Cross device link, typical in docker or when tmp/ and extensions/ are on different file systems
# Since we can't use a rename, do the slower but more versitile shutil.move()
shutil.move(tmpdir, target_dir)
else:
# Something else, not enough free space, permissions, etc. rethrow it so that it gets handled.
raise(err)
raise err
import launch
launch.run_extension_installer(target_dir)
@ -244,7 +241,7 @@ def refresh_available_extensions_from_data(hide_tags, sort_column):
hidden += 1
continue
install_code = f"""<input onclick="install_extension_from_index(this, '{html.escape(url)}')" type="button" value="{"Install" if not existing else "Installed"}" {"disabled=disabled" if existing else ""} class="gr-button gr-button-lg gr-button-secondary">"""
install_code = f"""<button onclick="install_extension_from_index(this, '{html.escape(url)}')" {"disabled=disabled" if existing else ""} class="lg secondary gradio-button custom-button">{"Install" if not existing else "Installed"}</button>"""
tags_text = ", ".join([f"<span class='extension-tag' title='{tags.get(x, '')}'>{x}</span>" for x in extension_tags])

55
modules/ui_extra_networks.py
View File

@ -22,21 +22,37 @@ def register_page(page):
allowed_dirs.update(set(sum([x.allowed_directories_for_previews() for x in extra_pages], [])))
def fetch_file(filename: str = ""):
from starlette.responses import FileResponse
if not any([Path(x).absolute() in Path(filename).absolute().parents for x in allowed_dirs]):
raise ValueError(f"File cannot be fetched: {filename}. Must be in one of directories registered by extra pages.")
ext = os.path.splitext(filename)[1].lower()
if ext not in (".png", ".jpg", ".webp"):
raise ValueError(f"File cannot be fetched: {filename}. Only png and jpg and webp.")
# would profit from returning 304
return FileResponse(filename, headers={"Accept-Ranges": "bytes"})
def get_metadata(page: str = "", item: str = ""):
from starlette.responses import JSONResponse
page = next(iter([x for x in extra_pages if x.name == page]), None)
if page is None:
return JSONResponse({})
metadata = page.metadata.get(item)
if metadata is None:
return JSONResponse({})
return JSONResponse({"metadata": metadata})
def add_pages_to_demo(app):
def fetch_file(filename: str = ""):
from starlette.responses import FileResponse
if not any([Path(x).absolute() in Path(filename).absolute().parents for x in allowed_dirs]):
raise ValueError(f"File cannot be fetched: {filename}. Must be in one of directories registered by extra pages.")
ext = os.path.splitext(filename)[1].lower()
if ext not in (".png", ".jpg", ".webp"):
raise ValueError(f"File cannot be fetched: {filename}. Only png and jpg and webp.")
# would profit from returning 304
return FileResponse(filename, headers={"Accept-Ranges": "bytes"})
app.add_api_route("/sd_extra_networks/thumb", fetch_file, methods=["GET"])
app.add_api_route("/sd_extra_networks/metadata", get_metadata, methods=["GET"])
class ExtraNetworksPage:
@ -45,6 +61,7 @@ class ExtraNetworksPage:
self.name = title.lower()
self.card_page = shared.html("extra-networks-card.html")
self.allow_negative_prompt = False
self.metadata = {}
def refresh(self):
pass
@ -66,6 +83,8 @@ class ExtraNetworksPage:
view = shared.opts.extra_networks_default_view
items_html = ''
self.metadata = {}
subdirs = {}
for parentdir in [os.path.abspath(x) for x in self.allowed_directories_for_previews()]:
for x in glob.glob(os.path.join(parentdir, '**/*'), recursive=True):
@ -86,12 +105,16 @@ class ExtraNetworksPage:
subdirs = {"": 1, **subdirs}
subdirs_html = "".join([f"""
<button class='gr-button gr-button-lg gr-button-secondary{" search-all" if subdir=="" else ""}' onclick='extraNetworksSearchButton("{tabname}_extra_tabs", event)'>
<button class='lg secondary gradio-button custom-button{" search-all" if subdir=="" else ""}' onclick='extraNetworksSearchButton("{tabname}_extra_tabs", event)'>
{html.escape(subdir if subdir!="" else "all")}
</button>
""" for subdir in subdirs])
for item in self.list_items():
metadata = item.get("metadata")
if metadata:
self.metadata[item["name"]] = metadata
items_html += self.create_html_for_item(item, tabname)
if items_html == '':
@ -127,8 +150,7 @@ class ExtraNetworksPage:
metadata_button = ""
metadata = item.get("metadata")
if metadata:
metadata_onclick = '"' + html.escape(f"""extraNetworksShowMetadata({json.dumps(metadata)}); return false;""") + '"'
metadata_button = f"<div class='metadata-button' title='Show metadata' onclick={metadata_onclick}></div>"
metadata_button = f"<div class='metadata-button' title='Show metadata' onclick='extraNetworksRequestMetadata(event, {json.dumps(self.name)}, {json.dumps(item['name'])})'></div>"
args = {
"preview_html": "style='background-image: url(\"" + html.escape(preview) + "\")'" if preview else '',
@ -215,6 +237,7 @@ def create_ui(container, button, tabname):
with gr.Tabs(elem_id=tabname+"_extra_tabs") as tabs:
for page in ui.stored_extra_pages:
with gr.Tab(page.title):
page_elem = gr.HTML(page.create_html(ui.tabname))
ui.pages.append(page_elem)

2
requirements.txt
View File

@ -4,7 +4,7 @@ basicsr
fonts
font-roboto
gfpgan
gradio==3.16.2
gradio==3.23
invisible-watermark
numpy
omegaconf

2
requirements_versions.txt
View File

@ -3,7 +3,7 @@ transformers==4.25.1
accelerate==0.12.0
basicsr==1.4.2
gfpgan==1.3.8
gradio==3.16.2
gradio==3.23
numpy==1.23.3
Pillow==9.4.0
realesrgan==0.3.0

6
script.js
View File

@ -1,7 +1,9 @@
function gradioApp() {
const elems = document.getElementsByTagName('gradio-app')
const gradioShadowRoot = elems.length == 0 ? null : elems[0].shadowRoot
return !!gradioShadowRoot ? gradioShadowRoot : document;
const elem = elems.length == 0 ? document : elems[0]
elem.getElementById = function(id){ return document.getElementById(id) }
return elem.shadowRoot ? elem.shadowRoot : elem
}
function get_uiCurrentTab() {

30
scripts/img2imgalt.py
View File

@ -6,23 +6,21 @@ from tqdm import trange
import modules.scripts as scripts
import gradio as gr
from modules import processing, shared, sd_samplers, prompt_parser, sd_samplers_common
from modules.processing import Processed
from modules.shared import opts, cmd_opts, state
from modules import processing, shared, sd_samplers, sd_samplers_common
import torch
import k_diffusion as K
from PIL import Image
from torch import autocast
from einops import rearrange, repeat
def find_noise_for_image(p, cond, uncond, cfg_scale, steps):
x = p.init_latent
s_in = x.new_ones([x.shape[0]])
dnw = K.external.CompVisDenoiser(shared.sd_model)
if shared.sd_model.parameterization == "v":
dnw = K.external.CompVisVDenoiser(shared.sd_model)
skip = 1
else:
dnw = K.external.CompVisDenoiser(shared.sd_model)
skip = 0
sigmas = dnw.get_sigmas(steps).flip(0)
shared.state.sampling_steps = steps
@ -37,7 +35,7 @@ def find_noise_for_image(p, cond, uncond, cfg_scale, steps):
image_conditioning = torch.cat([p.image_conditioning] * 2)
cond_in = {"c_concat": [image_conditioning], "c_crossattn": [cond_in]}
c_out, c_in = [K.utils.append_dims(k, x_in.ndim) for k in dnw.get_scalings(sigma_in)]
c_out, c_in = [K.utils.append_dims(k, x_in.ndim) for k in dnw.get_scalings(sigma_in)[skip:]]
t = dnw.sigma_to_t(sigma_in)
eps = shared.sd_model.apply_model(x_in * c_in, t, cond=cond_in)
@ -69,7 +67,12 @@ def find_noise_for_image_sigma_adjustment(p, cond, uncond, cfg_scale, steps):
x = p.init_latent
s_in = x.new_ones([x.shape[0]])
dnw = K.external.CompVisDenoiser(shared.sd_model)
if shared.sd_model.parameterization == "v":
dnw = K.external.CompVisVDenoiser(shared.sd_model)
skip = 1
else:
dnw = K.external.CompVisDenoiser(shared.sd_model)
skip = 0
sigmas = dnw.get_sigmas(steps).flip(0)
shared.state.sampling_steps = steps
@ -84,7 +87,7 @@ def find_noise_for_image_sigma_adjustment(p, cond, uncond, cfg_scale, steps):
image_conditioning = torch.cat([p.image_conditioning] * 2)
cond_in = {"c_concat": [image_conditioning], "c_crossattn": [cond_in]}
c_out, c_in = [K.utils.append_dims(k, x_in.ndim) for k in dnw.get_scalings(sigma_in)]
c_out, c_in = [K.utils.append_dims(k, x_in.ndim) for k in dnw.get_scalings(sigma_in)[skip:]]
if i == 1:
t = dnw.sigma_to_t(torch.cat([sigmas[i] * s_in] * 2))
@ -125,7 +128,7 @@ class Script(scripts.Script):
def show(self, is_img2img):
return is_img2img
def ui(self, is_img2img):
def ui(self, is_img2img):
info = gr.Markdown('''
* `CFG Scale` should be 2 or lower.
''')
@ -213,4 +216,3 @@ class Script(scripts.Script):
processed = processing.process_images(p)
return processed

95
scripts/loopback.py
View File

@ -1,14 +1,10 @@
import numpy as np
from tqdm import trange
import math
import modules.scripts as scripts
import gradio as gr
from modules import processing, shared, sd_samplers, images
import modules.scripts as scripts
from modules import deepbooru, images, processing, shared
from modules.processing import Processed
from modules.sd_samplers import samplers
from modules.shared import opts, cmd_opts, state
from modules import deepbooru
from modules.shared import opts, state
class Script(scripts.Script):
@ -20,39 +16,68 @@ class Script(scripts.Script):
def ui(self, is_img2img):
loops = gr.Slider(minimum=1, maximum=32, step=1, label='Loops', value=4, elem_id=self.elem_id("loops"))
denoising_strength_change_factor = gr.Slider(minimum=0.9, maximum=1.1, step=0.01, label='Denoising strength change factor', value=1, elem_id=self.elem_id("denoising_strength_change_factor"))
final_denoising_strength = gr.Slider(minimum=0, maximum=1, step=0.01, label='Final denoising strength', value=0.5, elem_id=self.elem_id("final_denoising_strength"))
denoising_curve = gr.Dropdown(label="Denoising strength curve", choices=["Aggressive", "Linear", "Lazy"], value="Linear")
append_interrogation = gr.Dropdown(label="Append interrogated prompt at each iteration", choices=["None", "CLIP", "DeepBooru"], value="None")
return [loops, denoising_strength_change_factor, append_interrogation]
return [loops, final_denoising_strength, denoising_curve, append_interrogation]
def run(self, p, loops, denoising_strength_change_factor, append_interrogation):
def run(self, p, loops, final_denoising_strength, denoising_curve, append_interrogation):
processing.fix_seed(p)
batch_count = p.n_iter
p.extra_generation_params = {
"Denoising strength change factor": denoising_strength_change_factor,
"Final denoising strength": final_denoising_strength,
"Denoising curve": denoising_curve
}
p.batch_size = 1
p.n_iter = 1
output_images, info = None, None
info = None
initial_seed = None
initial_info = None
initial_denoising_strength = p.denoising_strength
grids = []
all_images = []
original_init_image = p.init_images
original_prompt = p.prompt
original_inpainting_fill = p.inpainting_fill
state.job_count = loops * batch_count
initial_color_corrections = [processing.setup_color_correction(p.init_images[0])]
for n in range(batch_count):
history = []
def calculate_denoising_strength(loop):
strength = initial_denoising_strength
if loops == 1:
return strength
progress = loop / (loops - 1)
match denoising_curve:
case "Aggressive":
strength = math.sin((progress) * math.pi * 0.5)
case "Lazy":
strength = 1 - math.cos((progress) * math.pi * 0.5)
case _:
strength = progress
change = (final_denoising_strength - initial_denoising_strength) * strength
return initial_denoising_strength + change
history = []
for n in range(batch_count):
# Reset to original init image at the start of each batch
p.init_images = original_init_image
# Reset to original denoising strength
p.denoising_strength = initial_denoising_strength
last_image = None
for i in range(loops):
p.n_iter = 1
p.batch_size = 1
@ -72,26 +97,46 @@ class Script(scripts.Script):
processed = processing.process_images(p)
# Generation cancelled.
if state.interrupted:
break
if initial_seed is None:
initial_seed = processed.seed
initial_info = processed.info
init_img = processed.images[0]
p.init_images = [init_img]
p.seed = processed.seed + 1
p.denoising_strength = min(max(p.denoising_strength * denoising_strength_change_factor, 0.1), 1)
history.append(processed.images[0])
p.denoising_strength = calculate_denoising_strength(i + 1)
if state.skipped:
break
last_image = processed.images[0]
p.init_images = [last_image]
p.inpainting_fill = 1 # Set "masked content" to "original" for next loop.
if batch_count == 1:
history.append(last_image)
all_images.append(last_image)
if batch_count > 1 and not state.skipped and not state.interrupted:
history.append(last_image)
all_images.append(last_image)
p.inpainting_fill = original_inpainting_fill
if state.interrupted:
break
if len(history) > 1:
grid = images.image_grid(history, rows=1)
if opts.grid_save:
images.save_image(grid, p.outpath_grids, "grid", initial_seed, p.prompt, opts.grid_format, info=info, short_filename=not opts.grid_extended_filename, grid=True, p=p)
grids.append(grid)
all_images += history
if opts.return_grid:
all_images = grids + all_images
if opts.return_grid:
grids.append(grid)
all_images = grids + all_images
processed = Processed(p, all_images, initial_seed, initial_info)

28
scripts/postprocessing_upscale.py
View File

@ -17,22 +17,24 @@ class ScriptPostprocessingUpscale(scripts_postprocessing.ScriptPostprocessing):
def ui(self):
selected_tab = gr.State(value=0)
with gr.Tabs(elem_id="extras_resize_mode"):
with gr.TabItem('Scale by', elem_id="extras_scale_by_tab") as tab_scale_by:
upscaling_resize = gr.Slider(minimum=1.0, maximum=8.0, step=0.05, label="Resize", value=4, elem_id="extras_upscaling_resize")
with gr.Column():
with FormRow():
with gr.Tabs(elem_id="extras_resize_mode"):
with gr.TabItem('Scale by', elem_id="extras_scale_by_tab") as tab_scale_by:
upscaling_resize = gr.Slider(minimum=1.0, maximum=8.0, step=0.05, label="Resize", value=4, elem_id="extras_upscaling_resize")
with gr.TabItem('Scale to', elem_id="extras_scale_to_tab") as tab_scale_to:
with FormRow():
upscaling_resize_w = gr.Number(label="Width", value=512, precision=0, elem_id="extras_upscaling_resize_w")
upscaling_resize_h = gr.Number(label="Height", value=512, precision=0, elem_id="extras_upscaling_resize_h")
upscaling_crop = gr.Checkbox(label='Crop to fit', value=True, elem_id="extras_upscaling_crop")
with gr.TabItem('Scale to', elem_id="extras_scale_to_tab") as tab_scale_to:
with FormRow():
upscaling_resize_w = gr.Number(label="Width", value=512, precision=0, elem_id="extras_upscaling_resize_w")
upscaling_resize_h = gr.Number(label="Height", value=512, precision=0, elem_id="extras_upscaling_resize_h")
upscaling_crop = gr.Checkbox(label='Crop to fit', value=True, elem_id="extras_upscaling_crop")
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)
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)
with FormRow():
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")
with FormRow():
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")
tab_scale_by.select(fn=lambda: 0, inputs=[], outputs=[selected_tab])
tab_scale_to.select(fn=lambda: 1, inputs=[], outputs=[selected_tab])

21
scripts/xyz_grid.py
View File

@ -247,7 +247,7 @@ def draw_xyz_grid(p, xs, ys, zs, x_labels, y_labels, z_labels, cell, draw_legend
state.job = f"{index(ix, iy, iz) + 1} out of {list_size}"
processed: Processed = cell(x, y, z)
processed: Processed = cell(x, y, z, ix, iy, iz)
if processed_result is None:
# Use our first processed result object as a template container to hold our full results
@ -558,8 +558,6 @@ class Script(scripts.Script):
print(f"X/Y/Z plot will create {len(xs) * len(ys) * len(zs) * image_cell_count} images on {len(zs)} {len(xs)}x{len(ys)} grid{plural_s}{cell_console_text}. (Total steps to process: {total_steps})")
shared.total_tqdm.updateTotal(total_steps)
grid_infotext = [None]
state.xyz_plot_x = AxisInfo(x_opt, xs)
state.xyz_plot_y = AxisInfo(y_opt, ys)
state.xyz_plot_z = AxisInfo(z_opt, zs)
@ -588,7 +586,9 @@ class Script(scripts.Script):
else:
second_axes_processed = 'y'
def cell(x, y, z):
grid_infotext = [None] * (1 + len(zs))
def cell(x, y, z, ix, iy, iz):
if shared.state.interrupted:
return Processed(p, [], p.seed, "")
@ -600,7 +600,9 @@ class Script(scripts.Script):
res = process_images(pc)
if grid_infotext[0] is None:
# Sets subgrid infotexts
subgrid_index = 1 + iz
if grid_infotext[subgrid_index] is None and ix == 0 and iy == 0:
pc.extra_generation_params = copy(pc.extra_generation_params)
pc.extra_generation_params['Script'] = self.title()
@ -616,6 +618,12 @@ class Script(scripts.Script):
if y_opt.label in ["Seed", "Var. seed"] and not no_fixed_seeds:
pc.extra_generation_params["Fixed Y Values"] = ", ".join([str(y) for y in ys])
grid_infotext[subgrid_index] = processing.create_infotext(pc, pc.all_prompts, pc.all_seeds, pc.all_subseeds)
# Sets main grid infotext
if grid_infotext[0] is None and ix == 0 and iy == 0 and iz == 0:
pc.extra_generation_params = copy(pc.extra_generation_params)
if z_opt.label != 'Nothing':
pc.extra_generation_params["Z Type"] = z_opt.label
pc.extra_generation_params["Z Values"] = z_values
@ -650,6 +658,9 @@ class Script(scripts.Script):
z_count = len(zs)
# Set the grid infotexts to the real ones with extra_generation_params (1 main grid + z_count sub-grids)
processed.infotexts[:1+z_count] = grid_infotext[:1+z_count]
if not include_lone_images:
# Don't need sub-images anymore, drop from list:
processed.images = processed.images[:z_count+1]

812
style.css
View File

@ -1,51 +1,196 @@
.container {
max-width: 100%;
/* general gradio fixes */
:root, .dark{
--checkbox-label-gap: 0.25em 0.1em;
--section-header-text-size: 12pt;
--block-background-fill: transparent;
}
.token-counter{
.block.padded{
padding: 0 !important;
}
div.gradio-container{
max-width: unset !important;
}
.hidden{
display: none;
}
.compact{
background: transparent !important;
padding: 0 !important;
}
div.form{
border-width: 0;
box-shadow: none;
background: transparent;
overflow: visible;
gap: 0.5em;
}
.block.gradio-dropdown,
.block.gradio-slider,
.block.gradio-checkbox,
.block.gradio-textbox,
.block.gradio-radio,
.block.gradio-checkboxgroup,
.block.gradio-number,
.block.gradio-colorpicker
{
border-width: 0 !important;
box-shadow: none !important;
}
.gap.compact{
padding: 0;
gap: 0.2em 0;
}
div.compact{
gap: 1em;
}
.gradio-dropdown ul.options{
z-index: 3000;
}
.gradio-dropdown label span:not(.has-info),
.gradio-textbox label span:not(.has-info),
.gradio-number label span:not(.has-info)
{
margin-bottom: 0;
}
.gradio-dropdown div.wrap.wrap.wrap.wrap{
box-shadow: 0 1px 2px 0 rgba(0, 0, 0, 0.05);
}
.gradio-dropdown .wrap-inner.wrap-inner.wrap-inner{
flex-wrap: unset;
}
.gradio-dropdown .single-select{
white-space: nowrap;
overflow: hidden;
}
.gradio-dropdown .token-remove.remove-all.remove-all{
display: none;
}
.gradio-dropdown.multiselect .token-remove.remove-all.remove-all{
display: flex;
}
.gradio-slider input[type="number"]{
width: 6em;
}
.block.gradio-checkbox {
margin: 0.75em 1.5em 0 0;
}
.gradio-html div.wrap{
height: 100%;
}
div.gradio-html.min{
min-height: 0;
}
.block.gradio-gallery{
background: var(--input-background-fill);
}
.gradio-container .prose a, .gradio-container .prose a:visited{
color: unset;
text-decoration: none;
}
/* general styled components */
.gradio-button.tool{
max-width: 2.2em;
min-width: 2.2em !important;
height: 2.4em;
align-self: end;
line-height: 1em;
border-radius: 0.5em;
}
.checkboxes-row{
margin-bottom: 0.5em;
margin-left: 0em;
}
.checkboxes-row > div{
flex: 0;
white-space: nowrap;
min-width: auto;
}
button.custom-button{
border-radius: var(--button-large-radius);
padding: var(--button-large-padding);
font-weight: var(--button-large-text-weight);
border: var(--button-border-width) solid var(--button-secondary-border-color);
background: var(--button-secondary-background-fill);
color: var(--button-secondary-text-color);
font-size: var(--button-large-text-size);
display: inline-flex;
justify-content: center;
align-items: center;
transition: var(--button-transition);
box-shadow: var(--button-shadow);
text-align: center;
}
/* txt2img/img2img specific */
.block.token-counter{
position: absolute;
display: inline-block;
right: 2em;
right: 1em;
min-width: 0 !important;
width: auto;
z-index: 100;
top: -0.75em;
}
.token-counter.error span{
.block.token-counter span{
background: var(--input-background-fill) !important;
box-shadow: 0 0 0.0 0.3em rgba(192,192,192,0.15), inset 0 0 0.6em rgba(192,192,192,0.075);
border: 2px solid rgba(192,192,192,0.4) !important;
border-radius: 0.4em;
}
.block.token-counter.error span{
box-shadow: 0 0 0.0 0.3em rgba(255,0,0,0.15), inset 0 0 0.6em rgba(255,0,0,0.075);
border: 2px solid rgba(255,0,0,0.4) !important;
}
.token-counter div{
.block.token-counter div{
display: inline;
}
.token-counter span{
.block.token-counter span{
padding: 0.1em 0.75em;
}
#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;
[id$=_subseed_show]{
min-width: auto !important;
flex-grow: 0 !important;
display: flex;
}
.output-html p {
margin: 0 0.5em;
overflow-wrap: break-word;
}
.row > *,
.row > .gr-form > * {
min-width: min(120px, 100%);
flex: 1 1 0%;
[id$=_subseed_show] label{
margin-bottom: 0.5em;
align-self: end;
}
.performance {
@ -78,196 +223,94 @@
object-fit: scale-down;
}
#txt2img_actions_column, #img2img_actions_column {
margin: 0.35rem 0.75rem 0.35rem 0;
gap: 0.5em;
}
#script_list {
padding: .625rem .75rem 0 .625rem;
}
.justify-center.overflow-x-scroll {
justify-content: left;
}
.justify-center.overflow-x-scroll button:first-of-type {
margin-left: auto;
}
.justify-center.overflow-x-scroll button:last-of-type {
margin-right: auto;
}
[id$=_random_seed], [id$=_random_subseed], [id$=_reuse_seed], [id$=_reuse_subseed], #open_folder{
min-width: 2.3em;
height: 2.5em;
flex-grow: 0;
padding-left: 0.25em;
padding-right: 0.25em;
}
#hidden_element{
display: none;
}
[id$=_seed_row], [id$=_subseed_row]{
gap: 0.5rem;
padding: 0.6em;
}
[id$=_subseed_show_box]{
min-width: auto;
flex-grow: 0;
}
[id$=_subseed_show_box] > div{
border: 0;
height: 100%;
}
[id$=_subseed_show]{
min-width: auto;
flex-grow: 0;
padding: 0;
}
[id$=_subseed_show] label{
height: 100%;
}
#txt2img_actions_column, #img2img_actions_column{
gap: 0;
margin-right: .75rem;
}
#txt2img_tools, #img2img_tools{
gap: 0.4em;
}
#interrogate_col{
.interrogate-col{
min-width: 0 !important;
max-width: 8em !important;
margin-right: 1em;
gap: 0;
max-width: fit-content;
gap: 0.5em;
}
#interrogate, #deepbooru{
margin: 0em 0.25em 0.5em 0.25em;
min-width: 8em;
max-width: 8em;
.interrogate-col > button{
flex: 1;
}
#style_pos_col, #style_neg_col{
min-width: 8em !important;
.generate-box{
position: relative;
}
#txt2img_styles_row, #img2img_styles_row{
gap: 0.25em;
margin-top: 0.3em;
}
#txt2img_styles_row > button, #img2img_styles_row > button{
margin: 0;
}
#txt2img_styles, #img2img_styles{
padding: 0;
}
#txt2img_styles > label > div, #img2img_styles > label > div{
min-height: 3.2em;
}
ul.list-none{
max-height: 35em;
z-index: 2000;
}
.gr-form{
background: transparent;
}
.my-4{
margin-top: 0;
margin-bottom: 0;
}
#resize_mode{
flex: 1.5;
}
button{
align-self: stretch !important;
}
.overflow-hidden, .gr-panel{
overflow: visible !important;
}
#x_type, #y_type{
max-width: 10em;
}
#txt2img_preview, #img2img_preview, #ti_preview{
.gradio-button.generate-box-skip, .gradio-button.generate-box-interrupt{
position: absolute;
width: 320px;
left: 0;
right: 0;
margin-left: auto;
margin-right: auto;
margin-top: 34px;
z-index: 100;
border: none;
border-top-left-radius: 0;
border-top-right-radius: 0;
}
@media screen and (min-width: 768px) {
#txt2img_preview, #img2img_preview, #ti_preview {
position: absolute;
}
}
@media screen and (max-width: 767px) {
#txt2img_preview, #img2img_preview, #ti_preview {
position: relative;
}
}
#txt2img_preview div.left-0.top-0, #img2img_preview div.left-0.top-0, #ti_preview div.left-0.top-0{
width: 50%;
height: 100%;
display: none;
background: #b4c0cc;
}
.gradio-button.generate-box-skip:hover, .gradio-button.generate-box-interrupt:hover{
background: #c2cfdb;
}
.gradio-button.generate-box-interrupt{
left: 0;
border-radius: 0.5rem 0 0 0.5rem;
}
.gradio-button.generate-box-skip{
right: 0;
border-radius: 0 0.5rem 0.5rem 0;
}
fieldset span.text-gray-500, .gr-block.gr-box span.text-gray-500, label.block span{
position: absolute;
top: -0.7em;
line-height: 1.2em;
padding: 0;
margin: 0 0.5em;
background-color: white;
box-shadow: 6px 0 6px 0px white, -6px 0 6px 0px white;
z-index: 300;
#txtimg_hr_finalres{
min-height: 0 !important;
padding: .625rem .75rem;
margin-left: -0.75em
}
.dark fieldset span.text-gray-500, .dark .gr-block.gr-box span.text-gray-500, .dark label.block span{
background-color: rgb(31, 41, 55);
box-shadow: none;
border: 1px solid rgba(128, 128, 128, 0.1);
border-radius: 6px;
padding: 0.1em 0.5em;
#txtimg_hr_finalres .resolution{
font-weight: bold;
}
#txt2img_column_batch, #img2img_column_batch{
.inactive{
opacity: 0.5;
}
[id$=_column_batch]{
min-width: min(13.5em, 100%) !important;
}
#settings fieldset span.text-gray-500, #settings .gr-block.gr-box span.text-gray-500, #settings label.block span{
position: relative;
border: none;
margin-right: 8em;
div.dimensions-tools{
min-width: 0 !important;
max-width: fit-content;
flex-direction: row;
align-content: center;
}
#settings .gr-panel div.flex-col div.justify-between div{
position: relative;
z-index: 200;
#mode_img2img .gradio-image > div.fixed-height, #mode_img2img .gradio-image > div.fixed-height img{
height: 480px !important;
max-height: 480px !important;
min-height: 480px !important;
}
.image-buttons button{
min-width: auto;
}
.output-html p {
overflow-wrap: break-word;
}
/* settings */
#quicksettings {
width: fit-content;
}
#quicksettings > div, #quicksettings > fieldset{
max-width: 24em;
min-width: 24em;
padding: 0;
border: none;
box-shadow: none;
background: none;
}
#settings{
@ -279,17 +322,18 @@ fieldset span.text-gray-500, .gr-block.gr-box span.text-gray-500, label.block s
margin-left: 10em;
}
#settings > div.flex-wrap{
#settings > div.tab-nav{
float: left;
display: block;
margin-left: 0;
width: 10em;
}
#settings > div.flex-wrap button{
#settings > div.tab-nav button{
display: block;
border: none;
text-align: left;
white-space: initial;
}
#settings_result{
@ -297,29 +341,8 @@ fieldset span.text-gray-500, .gr-block.gr-box span.text-gray-500, label.block s
margin: 0 1.2em;
}
input[type="range"]{
margin: 0.5em 0 -0.3em 0;
}
#mask_bug_info {
text-align: center;
display: block;
margin-top: -0.75em;
margin-bottom: -0.75em;
}
#txt2img_negative_prompt, #img2img_negative_prompt{
}
/* gradio 3.8 adds opacity to progressbar which makes it blink; disable it here */
.transition.opacity-20 {
opacity: 1 !important;
}
/* more gradio's garbage cleanup */
.min-h-\[4rem\] { min-height: unset !important; }
.min-h-\[6rem\] { min-height: unset !important; }
/* live preview */
.progressDiv{
position: relative;
height: 20px;
@ -365,6 +388,8 @@ input[type="range"]{
height: 100%;
}
/* fullscreen popup (ie in Lora's (i) button) */
.popup-metadata{
color: black;
background: white;
@ -405,87 +430,54 @@ input[type="range"]{
padding: 2em;
}
/* fullpage image viewer */
#lightboxModal{
display: none;
position: fixed;
z-index: 1001;
padding-top: 100px;
left: 0;
top: 0;
width: 100%;
height: 100%;
overflow: auto;
background-color: rgba(20, 20, 20, 0.95);
user-select: none;
-webkit-user-select: none;
display: none;
position: fixed;
z-index: 1001;
left: 0;
top: 0;
width: 100%;
height: 100%;
overflow: auto;
background-color: rgba(20, 20, 20, 0.95);
user-select: none;
-webkit-user-select: none;
flex-direction: column;
}
.modalControls {
display: grid;
grid-template-columns: 32px 32px 32px 1fr 32px;
grid-template-areas: "zoom tile save space close";
position: absolute;
top: 0;
left: 0;
right: 0;
padding: 16px;
gap: 16px;
display: flex;
gap: 1em;
padding: 1em;
background-color: rgba(0,0,0,0.2);
}
.modalClose {
grid-area: close;
margin-left: auto;
}
.modalZoom {
grid-area: zoom;
}
.modalSave {
grid-area: save;
}
.modalTileImage {
grid-area: tile;
}
.modalClose,
.modalZoom,
.modalTileImage {
color: white;
font-size: 35px;
font-weight: bold;
cursor: pointer;
}
.modalSave {
.modalControls span{
color: white;
font-size: 28px;
margin-top: 8px;
font-size: 35px;
font-weight: bold;
cursor: pointer;
width: 1em;
}
.modalClose:hover,
.modalClose:focus,
.modalSave:hover,
.modalSave:focus,
.modalZoom:hover,
.modalZoom:focus {
color: #999;
text-decoration: none;
cursor: pointer;
.modalControls span:hover, .modalControls span:focus{
color: #999;
text-decoration: none;
}
#modalImage {
#lightboxModal > img {
display: block;
margin: auto;
width: auto;
}
.modalImageFullscreen {
#lightboxModal > img.modalImageFullscreen{
object-fit: contain;
height: 90%;
height: 100%;
}
.modalPrev,
@ -515,45 +507,7 @@ input[type="range"]{
background-color: rgba(0, 0, 0, 0.8);
}
#imageARPreview{
position:absolute;
top:0px;
left:0px;
border:2px solid red;
background:rgba(255, 0, 0, 0.3);
z-index: 900;
pointer-events:none;
display:none
}
#txt2img_generate_box, #img2img_generate_box{
position: relative;
}
#txt2img_interrupt, #img2img_interrupt, #txt2img_skip, #img2img_skip{
position: absolute;
width: 50%;
height: 100%;
background: #b4c0cc;
display: none;
}
#txt2img_interrupt, #img2img_interrupt{
left: 0;
border-radius: 0.5rem 0 0 0.5rem;
}
#txt2img_skip, #img2img_skip{
right: 0;
border-radius: 0 0.5rem 0.5rem 0;
}
.red {
color: red;
}
.gallery-item {
--tw-bg-opacity: 0 !important;
}
/* context menu (ie for the generate button) */
#context-menu{
z-index:9999;
@ -582,61 +536,8 @@ input[type="range"]{
background: #a55000;
}
#quicksettings {
width: fit-content;
}
#quicksettings > div, #quicksettings > fieldset{
max-width: 24em;
min-width: 24em;
padding: 0;
border: none;
box-shadow: none;
background: none;
margin-right: 10px;
}
#quicksettings > div > div > div > label > span {
position: relative;
margin-right: 9em;
margin-bottom: -1em;
}
canvas[key="mask"] {
z-index: 12 !important;
filter: invert();
mix-blend-mode: multiply;
pointer-events: none;
}
/* gradio 3.4.1 stuff for editable scrollbar values */
.gr-box > div > div > input.gr-text-input{
position: absolute;
right: 0.5em;
top: -0.6em;
z-index: 400;
width: 6em;
}
#quicksettings .gr-box > div > div > input.gr-text-input {
top: -1.12em;
}
.row.gr-compact{
overflow: visible;
}
#img2img_image, #img2img_image > .h-60, #img2img_image > .h-60 > div, #img2img_image > .h-60 > div > img,
#img2img_sketch, #img2img_sketch > .h-60, #img2img_sketch > .h-60 > div, #img2img_sketch > .h-60 > div > img,
#img2maskimg, #img2maskimg > .h-60, #img2maskimg > .h-60 > div, #img2maskimg > .h-60 > div > img,
#inpaint_sketch, #inpaint_sketch > .h-60, #inpaint_sketch > .h-60 > div, #inpaint_sketch > .h-60 > div > img
{
height: 480px !important;
max-height: 480px !important;
min-height: 480px !important;
}
/* Extensions */
/* extensions */
#tab_extensions table{
border-collapse: collapse;
@ -649,6 +550,7 @@ canvas[key="mask"] {
#tab_extensions table input[type="checkbox"]{
margin-right: 0.5em;
appearance: checkbox;
}
#tab_extensions button{
@ -673,74 +575,7 @@ canvas[key="mask"] {
font-size: 90%;
}
#image_buttons_txt2img button, #image_buttons_img2img button, #image_buttons_extras button{
min-width: auto;
padding-left: 0.5em;
padding-right: 0.5em;
}
.gr-form{
background-color: white;
}
.dark .gr-form{
background-color: rgb(31 41 55 / var(--tw-bg-opacity));
}
.gr-button-tool, .gr-button-tool-top{
max-width: 2.5em;
min-width: 2.5em !important;
height: 2.4em;
}
.gr-button-tool{
margin: 0.6em 0em 0.55em 0;
}
.gr-button-tool-top, #settings .gr-button-tool{
margin: 1.6em 0.7em 0.55em 0;
}
#modelmerger_results_container{
margin-top: 1em;
overflow: visible;
}
#modelmerger_models{
gap: 0;
}
#quicksettings .gr-button-tool{
margin: 0;
border-color: unset;
background-color: unset;
}
#modelmerger_interp_description>p {
margin: 0!important;
text-align: center;
}
#modelmerger_interp_description {
margin: 0.35rem 0.75rem 1.23rem;
}
#img2img_settings > div.gr-form, #txt2img_settings > div.gr-form {
padding-top: 0.9em;
padding-bottom: 0.9em;
}
#txt2img_settings {
padding-top: 1.16em;
padding-bottom: 0.9em;
}
#img2img_settings {
padding-bottom: 0.9em;
}
#img2img_settings div.gr-form .gr-form, #txt2img_settings div.gr-form .gr-form, #train_tabs div.gr-form .gr-form{
border: none;
padding-bottom: 0.5em;
}
/* replace original footer with ours */
footer {
display: none !important;
@ -759,90 +594,7 @@ footer {
opacity: 0.85;
}
#txtimg_hr_finalres{
min-height: 0 !important;
padding: .625rem .75rem;
margin-left: -0.75em
}
#txtimg_hr_finalres .resolution{
font-weight: bold;
}
#txt2img_checkboxes, #img2img_checkboxes{
margin-bottom: 0.5em;
margin-left: 0em;
}
#txt2img_checkboxes > div, #img2img_checkboxes > div{
flex: 0;
white-space: nowrap;
min-width: auto;
}
#img2img_copy_to_img2img, #img2img_copy_to_sketch, #img2img_copy_to_inpaint, #img2img_copy_to_inpaint_sketch{
margin-left: 0em;
}
#axis_options {
margin-left: 0em;
}
.inactive{
opacity: 0.5;
}
[id*='_prompt_container']{
gap: 0;
}
[id*='_prompt_container'] > div{
margin: -0.4em 0 0 0;
}
.gr-compact {
border: none;
}
.dark .gr-compact{
background-color: rgb(31 41 55 / var(--tw-bg-opacity));
margin-left: 0;
}
.gr-compact{
overflow: visible;
}
.gr-compact > *{
}
.gr-compact .gr-block, .gr-compact .gr-form{
border: none;
box-shadow: none;
}
.gr-compact .gr-box{
border-radius: .5rem !important;
border-width: 1px !important;
}
#mode_img2img > div > div{
gap: 0 !important;
}
[id*='img2img_copy_to_'] {
border: none;
}
[id*='img2img_copy_to_'] > button {
}
[id*='img2img_label_copy_to_'] {
font-size: 1.0em;
font-weight: bold;
text-align: center;
line-height: 2.4em;
}
/* extra networks UI */
.extra-networks > div > [id *= '_extra_']{
margin: 0.3em;
@ -855,12 +607,12 @@ footer {
.extra-network-subdirs button{
margin: 0 0.15em;
}
#txt2img_extra_networks .search, #img2img_extra_networks .search{
.extra-networks .tab-nav .search{
display: inline-block;
max-width: 16em;
margin: 0.3em;
align-self: center;
width: 16em;
}
#txt2img_extra_view, #img2img_extra_view {
@ -892,6 +644,7 @@ footer {
text-shadow: 2px 2px 3px black;
padding: 0.25em;
font-size: 22pt;
width: 1.5em;
}
.extra-network-cards .card:hover .metadata-button, .extra-network-thumbs .card:hover .metadata-button{
display: inline-block;
@ -985,12 +738,15 @@ footer {
left: 0;
right: 0;
padding: 0.5em;
color: white;
background: rgba(0,0,0,0.5);
box-shadow: 0 0 0.25em 0.25em rgba(0,0,0,0.5);
text-shadow: 0 0 0.2em black;
}
.extra-network-cards .card .actions *{
color: white;
}
.extra-network-cards .card .actions:hover{
box-shadow: 0 0 0.75em 0.75em rgba(0,0,0,0.5) !important;
}
@ -1028,7 +784,3 @@ footer {
.extra-network-cards .card ul a:hover{
color: red;
}
[id*='_prompt_container'] > div {
margin: 0!important;
}

5
webui.py
View File

@ -240,7 +240,7 @@ def webui():
shared.demo = modules.ui.create_ui()
startup_timer.record("create ui")
if cmd_opts.gradio_queue:
if not cmd_opts.no_gradio_queue:
shared.demo.queue(64)
gradio_auth_creds = []
@ -262,6 +262,9 @@ def webui():
inbrowser=cmd_opts.autolaunch,
prevent_thread_lock=True
)
for dep in shared.demo.dependencies:
dep['show_progress'] = False # disable gradio css animation on component update
# after initial launch, disable --autolaunch for subsequent restarts
cmd_opts.autolaunch = False