Unverified Commit 25de9df3 authored by papuSpartan's avatar papuSpartan Committed by GitHub

Merge branch 'AUTOMATIC1111:master' into master

parents ce428794 5c9b3625
......@@ -44,7 +44,7 @@ body:
id: commit
attributes:
label: Commit where the problem happens
description: Which commit are you running ? (copy the **Commit hash** shown in the cmd/terminal when you launch the UI)
description: Which commit are you running ? (Do not write *Latest version/repo/commit*, as this means nothing and will have changed by the time we read your issue. Rather, copy the **Commit hash** shown in the cmd/terminal when you launch the UI)
validations:
required: true
- type: dropdown
......
......@@ -27,4 +27,7 @@ __pycache__
notification.mp3
/SwinIR
/textual_inversion
.vscode
\ No newline at end of file
.vscode
/extensions
/test/stdout.txt
/test/stderr.txt
* @AUTOMATIC1111
/localizations/ar_AR.json @xmodar @blackneoo
/localizations/de_DE.json @LunixWasTaken
/localizations/es_ES.json @innovaciones
/localizations/fr_FR.json @tumbly
/localizations/it_IT.json @EugenioBuffo
/localizations/ja_JP.json @yuuki76
/localizations/ko_KR.json @36DB
/localizations/pt_BR.json @M-art-ucci
/localizations/ru_RU.json @kabachuha
/localizations/tr_TR.json @camenduru
/localizations/zh_CN.json @dtlnor @bgluminous
/localizations/zh_TW.json @benlisquare
......@@ -72,7 +72,7 @@ Check the [custom scripts](https://github.com/AUTOMATIC1111/stable-diffusion-web
- No token limit for prompts (original stable diffusion lets you use up to 75 tokens)
- DeepDanbooru integration, creates danbooru style tags for anime prompts (add --deepdanbooru to commandline args)
- [xformers](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Xformers), major speed increase for select cards: (add --xformers to commandline args)
- History tab: view, direct and delete images conveniently within the UI
- via extension: [History tab](https://github.com/yfszzx/stable-diffusion-webui-images-browser): view, direct and delete images conveniently within the UI
- Generate forever option
- Training tab
- hypernetworks and embeddings options
......@@ -83,8 +83,27 @@ Check the [custom scripts](https://github.com/AUTOMATIC1111/stable-diffusion-web
- Estimated completion time in progress bar
- API
- Support for dedicated [inpainting model](https://github.com/runwayml/stable-diffusion#inpainting-with-stable-diffusion) by RunwayML.
- Aesthetic Gradients, a way to generate images with a specific aesthetic by using clip images embds (implementation of [https://github.com/vicgalle/stable-diffusion-aesthetic-gradients](https://github.com/vicgalle/stable-diffusion-aesthetic-gradients))
- via extension: [Aesthetic Gradients](https://github.com/AUTOMATIC1111/stable-diffusion-webui-aesthetic-gradients), a way to generate images with a specific aesthetic by using clip images embds (implementation of [https://github.com/vicgalle/stable-diffusion-aesthetic-gradients](https://github.com/vicgalle/stable-diffusion-aesthetic-gradients))
## Where are Aesthetic Gradients?!?!
Aesthetic Gradients are now an extension. You can install it using git:
```commandline
git clone https://github.com/AUTOMATIC1111/stable-diffusion-webui-aesthetic-gradients extensions/aesthetic-gradients
```
After running this command, make sure that you have `aesthetic-gradients` dir in webui's `extensions` directory and restart
the UI. The interface for Aesthetic Gradients should appear exactly the same as it was.
## Where is History/Image browser?!?!
Image browser is now an extension. You can install it using git:
```commandline
git clone https://github.com/yfszzx/stable-diffusion-webui-images-browser extensions/images-browser
```
After running this command, make sure that you have `images-browser` dir in webui's `extensions` directory and restart
the UI. The interface for Image browser should appear exactly the same as it was.
## Installation and Running
Make sure the required [dependencies](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Dependencies) are met and follow the instructions available for both [NVidia](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Install-and-Run-on-NVidia-GPUs) (recommended) and [AMD](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Install-and-Run-on-AMD-GPUs) GPUs.
......
function extensions_apply(_, _){
disable = []
update = []
gradioApp().querySelectorAll('#extensions input[type="checkbox"]').forEach(function(x){
if(x.name.startsWith("enable_") && ! x.checked)
disable.push(x.name.substr(7))
if(x.name.startsWith("update_") && x.checked)
update.push(x.name.substr(7))
})
restart_reload()
return [JSON.stringify(disable), JSON.stringify(update)]
}
function extensions_check(){
gradioApp().querySelectorAll('#extensions .extension_status').forEach(function(x){
x.innerHTML = "Loading..."
})
return []
}
\ No newline at end of file
......@@ -63,8 +63,8 @@ titles = {
"Interrogate": "Reconstruct prompt from existing image and put it into the prompt field.",
"Images filename pattern": "Use following tags to define how filenames for images are chosen: [steps], [cfg], [prompt], [prompt_no_styles], [prompt_spaces], [width], [height], [styles], [sampler], [seed], [model_hash], [prompt_words], [date], [datetime], [job_timestamp]; leave empty for default.",
"Directory name pattern": "Use following tags to define how subdirectories for images and grids are chosen: [steps], [cfg], [prompt], [prompt_no_styles], [prompt_spaces], [width], [height], [styles], [sampler], [seed], [model_hash], [prompt_words], [date], [datetime], [job_timestamp]; leave empty for default.",
"Images filename pattern": "Use following tags to define how filenames for images are chosen: [steps], [cfg], [prompt], [prompt_no_styles], [prompt_spaces], [width], [height], [styles], [sampler], [seed], [model_hash], [prompt_words], [date], [datetime], [datetime<Format>], [datetime<Format><Time Zone>], [job_timestamp]; leave empty for default.",
"Directory name pattern": "Use following tags to define how subdirectories for images and grids are chosen: [steps], [cfg], [prompt], [prompt_no_styles], [prompt_spaces], [width], [height], [styles], [sampler], [seed], [model_hash], [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.",
......@@ -76,6 +76,7 @@ titles = {
"Create style": "Save current prompts as a style. If you add the token {prompt} to the text, the style use that as placeholder for your prompt when you use the style in the future.",
"Checkpoint name": "Loads weights from checkpoint before making images. You can either use hash or a part of filename (as seen in settings) for checkpoint name. Recommended to use with Y axis for less switching.",
"Inpainting conditioning mask strength": "Only applies to inpainting models. Determines how strongly to mask off the original image for inpainting and img2img. 1.0 means fully masked, which is the default behaviour. 0.0 means a fully unmasked conditioning. Lower values will help preserve the overall composition of the image, but will struggle with large changes.",
"vram": "Torch active: Peak amount of VRAM used by Torch during generation, excluding cached data.\nTorch reserved: Peak amount of VRAM allocated by Torch, including all active and cached data.\nSys VRAM: Peak amount of VRAM allocation across all applications / total GPU VRAM (peak utilization%).",
......
var images_history_click_image = function(){
if (!this.classList.contains("transform")){
var gallery = images_history_get_parent_by_class(this, "images_history_cantainor");
var buttons = gallery.querySelectorAll(".gallery-item");
var i = 0;
var hidden_list = [];
buttons.forEach(function(e){
if (e.style.display == "none"){
hidden_list.push(i);
}
i += 1;
})
if (hidden_list.length > 0){
setTimeout(images_history_hide_buttons, 10, hidden_list, gallery);
}
}
images_history_set_image_info(this);
}
var images_history_click_tab = function(){
var tabs_box = gradioApp().getElementById("images_history_tab");
if (!tabs_box.classList.contains(this.getAttribute("tabname"))) {
gradioApp().getElementById(this.getAttribute("tabname") + "_images_history_renew_page").click();
tabs_box.classList.add(this.getAttribute("tabname"))
}
}
function images_history_disabled_del(){
gradioApp().querySelectorAll(".images_history_del_button").forEach(function(btn){
btn.setAttribute('disabled','disabled');
});
}
function images_history_get_parent_by_class(item, class_name){
var parent = item.parentElement;
while(!parent.classList.contains(class_name)){
parent = parent.parentElement;
}
return parent;
}
function images_history_get_parent_by_tagname(item, tagname){
var parent = item.parentElement;
tagname = tagname.toUpperCase()
while(parent.tagName != tagname){
console.log(parent.tagName, tagname)
parent = parent.parentElement;
}
return parent;
}
function images_history_hide_buttons(hidden_list, gallery){
var buttons = gallery.querySelectorAll(".gallery-item");
var num = 0;
buttons.forEach(function(e){
if (e.style.display == "none"){
num += 1;
}
});
if (num == hidden_list.length){
setTimeout(images_history_hide_buttons, 10, hidden_list, gallery);
}
for( i in hidden_list){
buttons[hidden_list[i]].style.display = "none";
}
}
function images_history_set_image_info(button){
var buttons = images_history_get_parent_by_tagname(button, "DIV").querySelectorAll(".gallery-item");
var index = -1;
var i = 0;
buttons.forEach(function(e){
if(e == button){
index = i;
}
if(e.style.display != "none"){
i += 1;
}
});
var gallery = images_history_get_parent_by_class(button, "images_history_cantainor");
var set_btn = gallery.querySelector(".images_history_set_index");
var curr_idx = set_btn.getAttribute("img_index", index);
if (curr_idx != index) {
set_btn.setAttribute("img_index", index);
images_history_disabled_del();
}
set_btn.click();
}
function images_history_get_current_img(tabname, image_path, files){
return [
gradioApp().getElementById(tabname + '_images_history_set_index').getAttribute("img_index"),
image_path,
files
];
}
function images_history_delete(del_num, tabname, img_path, img_file_name, page_index, filenames, image_index){
image_index = parseInt(image_index);
var tab = gradioApp().getElementById(tabname + '_images_history');
var set_btn = tab.querySelector(".images_history_set_index");
var buttons = [];
tab.querySelectorAll(".gallery-item").forEach(function(e){
if (e.style.display != 'none'){
buttons.push(e);
}
});
var img_num = buttons.length / 2;
if (img_num <= del_num){
setTimeout(function(tabname){
gradioApp().getElementById(tabname + '_images_history_renew_page').click();
}, 30, tabname);
} else {
var next_img
for (var i = 0; i < del_num; i++){
if (image_index + i < image_index + img_num){
buttons[image_index + i].style.display = 'none';
buttons[image_index + img_num + 1].style.display = 'none';
next_img = image_index + i + 1
}
}
var bnt;
if (next_img >= img_num){
btn = buttons[image_index - del_num];
} else {
btn = buttons[next_img];
}
setTimeout(function(btn){btn.click()}, 30, btn);
}
images_history_disabled_del();
return [del_num, tabname, img_path, img_file_name, page_index, filenames, image_index];
}
function images_history_turnpage(img_path, page_index, image_index, tabname){
var buttons = gradioApp().getElementById(tabname + '_images_history').querySelectorAll(".gallery-item");
buttons.forEach(function(elem) {
elem.style.display = 'block';
})
return [img_path, page_index, image_index, tabname];
}
function images_history_enable_del_buttons(){
gradioApp().querySelectorAll(".images_history_del_button").forEach(function(btn){
btn.removeAttribute('disabled');
})
}
function images_history_init(){
var load_txt2img_button = gradioApp().getElementById('txt2img_images_history_renew_page')
if (load_txt2img_button){
for (var i in images_history_tab_list ){
tab = images_history_tab_list[i];
gradioApp().getElementById(tab + '_images_history').classList.add("images_history_cantainor");
gradioApp().getElementById(tab + '_images_history_set_index').classList.add("images_history_set_index");
gradioApp().getElementById(tab + '_images_history_del_button').classList.add("images_history_del_button");
gradioApp().getElementById(tab + '_images_history_gallery').classList.add("images_history_gallery");
}
var tabs_box = gradioApp().getElementById("tab_images_history").querySelector("div").querySelector("div").querySelector("div");
tabs_box.setAttribute("id", "images_history_tab");
var tab_btns = tabs_box.querySelectorAll("button");
for (var i in images_history_tab_list){
var tabname = images_history_tab_list[i]
tab_btns[i].setAttribute("tabname", tabname);
// this refreshes history upon tab switch
// until the history is known to work well, which is not the case now, we do not do this at startup
//tab_btns[i].addEventListener('click', images_history_click_tab);
}
tabs_box.classList.add(images_history_tab_list[0]);
// same as above, at page load
//load_txt2img_button.click();
} else {
setTimeout(images_history_init, 500);
}
}
var images_history_tab_list = ["txt2img", "img2img", "extras"];
setTimeout(images_history_init, 500);
document.addEventListener("DOMContentLoaded", function() {
var mutationObserver = new MutationObserver(function(m){
for (var i in images_history_tab_list ){
let tabname = images_history_tab_list[i]
var buttons = gradioApp().querySelectorAll('#' + tabname + '_images_history .gallery-item');
buttons.forEach(function(bnt){
bnt.addEventListener('click', images_history_click_image, true);
});
// same as load_txt2img_button.click() above
/*
var cls_btn = gradioApp().getElementById(tabname + '_images_history_gallery').querySelector("svg");
if (cls_btn){
cls_btn.addEventListener('click', function(){
gradioApp().getElementById(tabname + '_images_history_renew_page').click();
}, false);
}*/
}
});
mutationObserver.observe( gradioApp(), { childList:true, subtree:true });
});
......@@ -13,6 +13,15 @@ function showModal(event) {
}
lb.style.display = "block";
lb.focus()
const tabTxt2Img = gradioApp().getElementById("tab_txt2img")
const tabImg2Img = gradioApp().getElementById("tab_img2img")
// show the save button in modal only on txt2img or img2img tabs
if (tabTxt2Img.style.display != "none" || tabImg2Img.style.display != "none") {
gradioApp().getElementById("modal_save").style.display = "inline"
} else {
gradioApp().getElementById("modal_save").style.display = "none"
}
event.stopPropagation()
}
......@@ -81,6 +90,25 @@ function modalImageSwitch(offset) {
}
}
function saveImage(){
const tabTxt2Img = gradioApp().getElementById("tab_txt2img")
const tabImg2Img = gradioApp().getElementById("tab_img2img")
const saveTxt2Img = "save_txt2img"
const saveImg2Img = "save_img2img"
if (tabTxt2Img.style.display != "none") {
gradioApp().getElementById(saveTxt2Img).click()
} else if (tabImg2Img.style.display != "none") {
gradioApp().getElementById(saveImg2Img).click()
} else {
console.error("missing implementation for saving modal of this type")
}
}
function modalSaveImage(event) {
saveImage()
event.stopPropagation()
}
function modalNextImage(event) {
modalImageSwitch(1)
event.stopPropagation()
......@@ -93,6 +121,9 @@ function modalPrevImage(event) {
function modalKeyHandler(event) {
switch (event.key) {
case "s":
saveImage()
break;
case "ArrowLeft":
modalPrevImage(event)
break;
......@@ -198,6 +229,14 @@ document.addEventListener("DOMContentLoaded", function() {
modalTileImage.title = "Preview tiling";
modalControls.appendChild(modalTileImage)
const modalSave = document.createElement("span")
modalSave.className = "modalSave cursor"
modalSave.id = "modal_save"
modalSave.innerHTML = "&#x1F5AB;"
modalSave.addEventListener("click", modalSaveImage, true)
modalSave.title = "Save Image(s)"
modalControls.appendChild(modalSave)
const modalClose = document.createElement('span')
modalClose.className = 'modalClose cursor';
modalClose.innerHTML = '&times;'
......
......@@ -108,6 +108,9 @@ function processNode(node){
function dumpTranslations(){
dumped = {}
if (localization.rtl) {
dumped.rtl = true
}
Object.keys(original_lines).forEach(function(text){
if(dumped[text] !== undefined) return
......@@ -129,6 +132,24 @@ onUiUpdate(function(m){
document.addEventListener("DOMContentLoaded", function() {
processNode(gradioApp())
if (localization.rtl) { // if the language is from right to left,
(new MutationObserver((mutations, observer) => { // wait for the style to load
mutations.forEach(mutation => {
mutation.addedNodes.forEach(node => {
if (node.tagName === 'STYLE') {
observer.disconnect();
for (const x of node.sheet.rules) { // find all rtl media rules
if (Array.from(x.media || []).includes('rtl')) {
x.media.appendMedium('all'); // enable them
}
}
}
})
});
})).observe(gradioApp(), { childList: true });
}
})
function download_localization() {
......
......@@ -45,14 +45,14 @@ function switch_to_txt2img(){
return args_to_array(arguments);
}
function switch_to_img2img_img2img(){
function switch_to_img2img(){
gradioApp().querySelector('#tabs').querySelectorAll('button')[1].click();
gradioApp().getElementById('mode_img2img').querySelectorAll('button')[0].click();
return args_to_array(arguments);
}
function switch_to_img2img_inpaint(){
function switch_to_inpaint(){
gradioApp().querySelector('#tabs').querySelectorAll('button')[1].click();
gradioApp().getElementById('mode_img2img').querySelectorAll('button')[1].click();
......@@ -65,26 +65,6 @@ function switch_to_extras(){
return args_to_array(arguments);
}
function extract_image_from_gallery_txt2img(gallery){
switch_to_txt2img()
return extract_image_from_gallery(gallery);
}
function extract_image_from_gallery_img2img(gallery){
switch_to_img2img_img2img()
return extract_image_from_gallery(gallery);
}
function extract_image_from_gallery_inpaint(gallery){
switch_to_img2img_inpaint()
return extract_image_from_gallery(gallery);
}
function extract_image_from_gallery_extras(gallery){
switch_to_extras()
return extract_image_from_gallery(gallery);
}
function get_tab_index(tabId){
var res = 0
......
......@@ -111,7 +111,7 @@ def prepare_enviroment():
gfpgan_package = os.environ.get('GFPGAN_PACKAGE', "git+https://github.com/TencentARC/GFPGAN.git@8d2447a2d918f8eba5a4a01463fd48e45126a379")
clip_package = os.environ.get('CLIP_PACKAGE', "git+https://github.com/openai/CLIP.git@d50d76daa670286dd6cacf3bcd80b5e4823fc8e1")
deepdanbooru_package = os.environ.get('DEEPDANBOORU_PACKAGE', "git+https://github.com/KichangKim/DeepDanbooru.git@edf73df4cdaeea2cf00e9ac08bd8a9026b7a7b26")
deepdanbooru_package = os.environ.get('DEEPDANBOORU_PACKAGE', "git+https://github.com/KichangKim/DeepDanbooru.git@d91a2963bf87c6a770d74894667e9ffa9f6de7ff")
xformers_windows_package = os.environ.get('XFORMERS_WINDOWS_PACKAGE', 'https://github.com/C43H66N12O12S2/stable-diffusion-webui/releases/download/f/xformers-0.0.14.dev0-cp310-cp310-win_amd64.whl')
......@@ -128,10 +128,12 @@ def prepare_enviroment():
blip_commit_hash = os.environ.get('BLIP_COMMIT_HASH', "48211a1594f1321b00f14c9f7a5b4813144b2fb9")
sys.argv += shlex.split(commandline_args)
test_argv = [x for x in sys.argv if x != '--tests']
sys.argv, skip_torch_cuda_test = extract_arg(sys.argv, '--skip-torch-cuda-test')
sys.argv, reinstall_xformers = extract_arg(sys.argv, '--reinstall-xformers')
sys.argv, update_check = extract_arg(sys.argv, '--update-check')
sys.argv, run_tests = extract_arg(sys.argv, '--tests')
xformers = '--xformers' in sys.argv
deepdanbooru = '--deepdanbooru' in sys.argv
ngrok = '--ngrok' in sys.argv
......@@ -194,6 +196,26 @@ def prepare_enviroment():
print("Exiting because of --exit argument")
exit(0)
if run_tests:
tests(test_argv)
exit(0)
def tests(argv):
if "--api" not in argv:
argv.append("--api")
print(f"Launching Web UI in another process for testing with arguments: {' '.join(argv[1:])}")
with open('test/stdout.txt', "w", encoding="utf8") as stdout, open('test/stderr.txt', "w", encoding="utf8") as stderr:
proc = subprocess.Popen([sys.executable, *argv], stdout=stdout, stderr=stderr)
import test.server_poll
test.server_poll.run_tests()
print(f"Stopping Web UI process with id {proc.pid}")
proc.kill()
def start_webui():
print(f"Launching Web UI with arguments: {' '.join(sys.argv[1:])}")
......
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import os.path
import sys
import traceback
import PIL.Image
import numpy as np
import torch
from basicsr.utils.download_util import load_file_from_url
import modules.upscaler
from modules import devices, modelloader
from modules.bsrgan_model_arch import RRDBNet
class UpscalerBSRGAN(modules.upscaler.Upscaler):
def __init__(self, dirname):
self.name = "BSRGAN"
self.model_name = "BSRGAN 4x"
self.model_url = "https://github.com/cszn/KAIR/releases/download/v1.0/BSRGAN.pth"
self.user_path = dirname
super().__init__()
model_paths = self.find_models(ext_filter=[".pt", ".pth"])
scalers = []
if len(model_paths) == 0:
scaler_data = modules.upscaler.UpscalerData(self.model_name, self.model_url, self, 4)
scalers.append(scaler_data)
for file in model_paths:
if "http" in file:
name = self.model_name
else:
name = modelloader.friendly_name(file)
try:
scaler_data = modules.upscaler.UpscalerData(name, file, self, 4)
scalers.append(scaler_data)
except Exception:
print(f"Error loading BSRGAN model: {file}", file=sys.stderr)
print(traceback.format_exc(), file=sys.stderr)
self.scalers = scalers
def do_upscale(self, img: PIL.Image, selected_file):
torch.cuda.empty_cache()
model = self.load_model(selected_file)
if model is None:
return img
model.to(devices.device_bsrgan)
torch.cuda.empty_cache()
img = np.array(img)
img = img[:, :, ::-1]
img = np.moveaxis(img, 2, 0) / 255
img = torch.from_numpy(img).float()
img = img.unsqueeze(0).to(devices.device_bsrgan)
with torch.no_grad():
output = model(img)
output = output.squeeze().float().cpu().clamp_(0, 1).numpy()
output = 255. * np.moveaxis(output, 0, 2)
output = output.astype(np.uint8)
output = output[:, :, ::-1]
torch.cuda.empty_cache()
return PIL.Image.fromarray(output, 'RGB')
def load_model(self, path: str):
if "http" in path:
filename = load_file_from_url(url=self.model_url, model_dir=self.model_path, file_name="%s.pth" % self.name,
progress=True)
else:
filename = path
if not os.path.exists(filename) or filename is None:
print(f"BSRGAN: Unable to load model from {filename}", file=sys.stderr)
return None
model = RRDBNet(in_nc=3, out_nc=3, nf=64, nb=23, gc=32, sf=4) # define network
model.load_state_dict(torch.load(filename), strict=True)
model.eval()
for k, v in model.named_parameters():
v.requires_grad = False
return model
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......@@ -50,11 +50,12 @@ def create_deepbooru_process(threshold, deepbooru_opts):
the tags.
"""
from modules import shared # prevents circular reference
shared.deepbooru_process_manager = multiprocessing.Manager()
context = multiprocessing.get_context("spawn")
shared.deepbooru_process_manager = context.Manager()
shared.deepbooru_process_queue = shared.deepbooru_process_manager.Queue()
shared.deepbooru_process_return = shared.deepbooru_process_manager.dict()
shared.deepbooru_process_return["value"] = -1
shared.deepbooru_process = multiprocessing.Process(target=deepbooru_process, args=(shared.deepbooru_process_queue, shared.deepbooru_process_return, threshold, deepbooru_opts))
shared.deepbooru_process = context.Process(target=deepbooru_process, args=(shared.deepbooru_process_queue, shared.deepbooru_process_return, threshold, deepbooru_opts))
shared.deepbooru_process.start()
......
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......@@ -54,9 +54,8 @@ class UpscalerScuNET(modules.upscaler.Upscaler):
img = img[:, :, ::-1]
img = np.moveaxis(img, 2, 0) / 255
img = torch.from_numpy(img).float()
img = img.unsqueeze(0).to(device)
img = devices.mps_contiguous_to(img.unsqueeze(0), device)
img = img.to(device)
with torch.no_grad():
output = model(img)
output = output.squeeze().float().cpu().clamp_(0, 1).numpy()
......
......@@ -332,7 +332,6 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module):
multipliers.append([1.0] * 75)
z1 = self.process_tokens(tokens, multipliers)
z1 = shared.aesthetic_clip(z1, remade_batch_tokens)
z = z1 if z is None else torch.cat((z, z1), axis=-2)
remade_batch_tokens = rem_tokens
......
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......@@ -23,3 +23,4 @@ torchdiffeq==0.2.3
kornia==0.6.7
lark==1.1.2
inflection==0.5.1
GitPython==3.1.27
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