Unverified Commit c9a2cfdf authored by AUTOMATIC1111's avatar AUTOMATIC1111 Committed by GitHub

Merge branch 'master' into racecond_fix

parents 39541d77 5cd5a672
name: Run basic features tests on CPU with empty SD model
on:
- push
- pull_request
jobs:
test:
runs-on: ubuntu-latest
steps:
- name: Checkout Code
uses: actions/checkout@v3
- name: Set up Python 3.10
uses: actions/setup-python@v4
with:
python-version: 3.10.6
- uses: actions/cache@v3
with:
path: ~/.cache/pip
key: ${{ runner.os }}-pip-${{ hashFiles('**/requirements.txt') }}
restore-keys: ${{ runner.os }}-pip-
- name: Run tests
run: python launch.py --tests basic_features --no-half --disable-opt-split-attention --use-cpu all --skip-torch-cuda-test
- name: Upload main app stdout-stderr
uses: actions/upload-artifact@v3
if: always()
with:
name: stdout-stderr
path: |
test/stdout.txt
test/stderr.txt
__pycache__ __pycache__
*.ckpt *.ckpt
*.safetensors
*.pth *.pth
/ESRGAN/* /ESRGAN/*
/SwinIR/* /SwinIR/*
......
* @AUTOMATIC1111 * @AUTOMATIC1111
/localizations/ar_AR.json @xmodar @blackneoo
/localizations/de_DE.json @LunixWasTaken # if you were managing a localization and were removed from this file, this is because
/localizations/es_ES.json @innovaciones # the intended way to do localizations now is via extensions. See:
/localizations/fr_FR.json @tumbly # https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Developing-extensions
/localizations/it_IT.json @EugenioBuffo # Make a repo with your localization and since you are still listed as a collaborator
/localizations/ja_JP.json @yuuki76 # you can add it to the wiki page yourself. This change is because some people complained
/localizations/ko_KR.json @36DB # the git commit log is cluttered with things unrelated to almost everyone and
/localizations/pt_BR.json @M-art-ucci # because I believe this is the best overall for the project to handle localizations almost
/localizations/ru_RU.json @kabachuha # entirely without my oversight.
/localizations/tr_TR.json @camenduru
/localizations/zh_CN.json @dtlnor @bgluminous
/localizations/zh_TW.json @benlisquare
...@@ -70,7 +70,7 @@ Check the [custom scripts](https://github.com/AUTOMATIC1111/stable-diffusion-web ...@@ -70,7 +70,7 @@ Check the [custom scripts](https://github.com/AUTOMATIC1111/stable-diffusion-web
- separate prompts using uppercase `AND` - separate prompts using uppercase `AND`
- also supports weights for prompts: `a cat :1.2 AND a dog AND a penguin :2.2` - also supports weights for prompts: `a cat :1.2 AND a dog AND a penguin :2.2`
- No token limit for prompts (original stable diffusion lets you use up to 75 tokens) - 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) - DeepDanbooru integration, creates danbooru style tags for anime prompts
- [xformers](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Xformers), major speed increase for select cards: (add --xformers to commandline args) - [xformers](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Xformers), major speed increase for select cards: (add --xformers to commandline args)
- via extension: [History tab](https://github.com/yfszzx/stable-diffusion-webui-images-browser): 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 - Generate forever option
...@@ -84,26 +84,7 @@ Check the [custom scripts](https://github.com/AUTOMATIC1111/stable-diffusion-web ...@@ -84,26 +84,7 @@ Check the [custom scripts](https://github.com/AUTOMATIC1111/stable-diffusion-web
- API - API
- Support for dedicated [inpainting model](https://github.com/runwayml/stable-diffusion#inpainting-with-stable-diffusion) by RunwayML. - Support for dedicated [inpainting model](https://github.com/runwayml/stable-diffusion#inpainting-with-stable-diffusion) by RunwayML.
- 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)) - 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))
- [Stable Diffusion 2.0](https://github.com/Stability-AI/stablediffusion) support - see [wiki](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Features#stable-diffusion-20) for instructions
## 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 ## 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. 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.
...@@ -155,14 +136,15 @@ The documentation was moved from this README over to the project's [wiki](https: ...@@ -155,14 +136,15 @@ The documentation was moved from this README over to the project's [wiki](https:
- Swin2SR - https://github.com/mv-lab/swin2sr - Swin2SR - https://github.com/mv-lab/swin2sr
- LDSR - https://github.com/Hafiidz/latent-diffusion - LDSR - https://github.com/Hafiidz/latent-diffusion
- Ideas for optimizations - https://github.com/basujindal/stable-diffusion - Ideas for optimizations - https://github.com/basujindal/stable-diffusion
- Doggettx - Cross Attention layer optimization - https://github.com/Doggettx/stable-diffusion, original idea for prompt editing. - Cross Attention layer optimization - Doggettx - https://github.com/Doggettx/stable-diffusion, original idea for prompt editing.
- InvokeAI, lstein - Cross Attention layer optimization - https://github.com/invoke-ai/InvokeAI (originally http://github.com/lstein/stable-diffusion) - Cross Attention layer optimization - InvokeAI, lstein - https://github.com/invoke-ai/InvokeAI (originally http://github.com/lstein/stable-diffusion)
- Rinon Gal - Textual Inversion - https://github.com/rinongal/textual_inversion (we're not using his code, but we are using his ideas). - Textual Inversion - Rinon Gal - https://github.com/rinongal/textual_inversion (we're not using his code, but we are using his ideas).
- Idea for SD upscale - https://github.com/jquesnelle/txt2imghd - Idea for SD upscale - https://github.com/jquesnelle/txt2imghd
- Noise generation for outpainting mk2 - https://github.com/parlance-zz/g-diffuser-bot - Noise generation for outpainting mk2 - https://github.com/parlance-zz/g-diffuser-bot
- CLIP interrogator idea and borrowing some code - https://github.com/pharmapsychotic/clip-interrogator - CLIP interrogator idea and borrowing some code - https://github.com/pharmapsychotic/clip-interrogator
- Idea for Composable Diffusion - https://github.com/energy-based-model/Compositional-Visual-Generation-with-Composable-Diffusion-Models-PyTorch - Idea for Composable Diffusion - https://github.com/energy-based-model/Compositional-Visual-Generation-with-Composable-Diffusion-Models-PyTorch
- xformers - https://github.com/facebookresearch/xformers - xformers - https://github.com/facebookresearch/xformers
- DeepDanbooru - interrogator for anime diffusers https://github.com/KichangKim/DeepDanbooru - DeepDanbooru - interrogator for anime diffusers https://github.com/KichangKim/DeepDanbooru
- Security advice - RyotaK
- Initial Gradio script - posted on 4chan by an Anonymous user. Thank you Anonymous user. - Initial Gradio script - posted on 4chan by an Anonymous user. Thank you Anonymous user.
- (You) - (You)
addEventListener('keydown', (event) => { addEventListener('keydown', (event) => {
let target = event.originalTarget || event.composedPath()[0]; let target = event.originalTarget || event.composedPath()[0];
if (!target.hasAttribute("placeholder")) return; if (!target.matches("#toprow textarea.gr-text-input[placeholder]")) return;
if (!target.placeholder.toLowerCase().includes("prompt")) return;
if (! (event.metaKey || event.ctrlKey)) return; if (! (event.metaKey || event.ctrlKey)) return;
......
// attaches listeners to the txt2img and img2img galleries to update displayed generation param text when the image changes
let txt2img_gallery, img2img_gallery, modal = undefined;
onUiUpdate(function(){
if (!txt2img_gallery) {
txt2img_gallery = attachGalleryListeners("txt2img")
}
if (!img2img_gallery) {
img2img_gallery = attachGalleryListeners("img2img")
}
if (!modal) {
modal = gradioApp().getElementById('lightboxModal')
modalObserver.observe(modal, { attributes : true, attributeFilter : ['style'] });
}
});
let modalObserver = new MutationObserver(function(mutations) {
mutations.forEach(function(mutationRecord) {
let selectedTab = gradioApp().querySelector('#tabs div button.bg-white')?.innerText
if (mutationRecord.target.style.display === 'none' && selectedTab === 'txt2img' || selectedTab === 'img2img')
gradioApp().getElementById(selectedTab+"_generation_info_button").click()
});
});
function attachGalleryListeners(tab_name) {
gallery = gradioApp().querySelector('#'+tab_name+'_gallery')
gallery?.addEventListener('click', () => gradioApp().getElementById(tab_name+"_generation_info_button").click());
gallery?.addEventListener('keydown', (e) => {
if (e.keyCode == 37 || e.keyCode == 39) // left or right arrow
gradioApp().getElementById(tab_name+"_generation_info_button").click()
});
return gallery;
}
...@@ -62,8 +62,8 @@ titles = { ...@@ -62,8 +62,8 @@ titles = {
"Interrogate": "Reconstruct prompt from existing image and put it into the prompt field.", "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], [datetime<Format>], [datetime<Format><Time Zone>], [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], [model_name], [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.", "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], [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", "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.", "Loopback": "Process an image, use it as an input, repeat.",
...@@ -94,6 +94,8 @@ titles = { ...@@ -94,6 +94,8 @@ titles = {
"Add difference": "Result = A + (B - C) * M", "Add difference": "Result = A + (B - C) * M",
"Learning rate": "how fast should the training go. Low values will take longer to train, high values may fail to converge (not generate accurate results) and/or may break the embedding (This has happened if you see Loss: nan in the training info textbox. If this happens, you need to manually restore your embedding from an older not-broken backup).\n\nYou can set a single numeric value, or multiple learning rates using the syntax:\n\n rate_1:max_steps_1, rate_2:max_steps_2, ...\n\nEG: 0.005:100, 1e-3:1000, 1e-5\n\nWill train with rate of 0.005 for first 100 steps, then 1e-3 until 1000 steps, then 1e-5 for all remaining steps.", "Learning rate": "how fast should the training go. Low values will take longer to train, high values may fail to converge (not generate accurate results) and/or may break the embedding (This has happened if you see Loss: nan in the training info textbox. If this happens, you need to manually restore your embedding from an older not-broken backup).\n\nYou can set a single numeric value, or multiple learning rates using the syntax:\n\n rate_1:max_steps_1, rate_2:max_steps_2, ...\n\nEG: 0.005:100, 1e-3:1000, 1e-5\n\nWill train with rate of 0.005 for first 100 steps, then 1e-3 until 1000 steps, then 1e-5 for all remaining steps.",
"Clip skip": "Early stopping parameter for CLIP model; 1 is stop at last layer as usual, 2 is stop at penultimate layer, etc."
} }
......
...@@ -23,7 +23,7 @@ function check_progressbar(id_part, id_progressbar, id_progressbar_span, id_skip ...@@ -23,7 +23,7 @@ function check_progressbar(id_part, id_progressbar, id_progressbar_span, id_skip
if(opts.show_progress_in_title && progressbar && progressbar.offsetParent){ if(opts.show_progress_in_title && progressbar && progressbar.offsetParent){
if(progressbar.innerText){ if(progressbar.innerText){
let newtitle = 'Stable Diffusion - ' + progressbar.innerText let newtitle = '[' + progressbar.innerText.trim() + '] Stable Diffusion';
if(document.title != newtitle){ if(document.title != newtitle){
document.title = newtitle; document.title = newtitle;
} }
......
...@@ -8,8 +8,8 @@ function set_theme(theme){ ...@@ -8,8 +8,8 @@ function set_theme(theme){
} }
function selected_gallery_index(){ function selected_gallery_index(){
var buttons = gradioApp().querySelectorAll('[style="display: block;"].tabitem .gallery-item') var buttons = gradioApp().querySelectorAll('[style="display: block;"].tabitem div[id$=_gallery] .gallery-item')
var button = gradioApp().querySelector('[style="display: block;"].tabitem .gallery-item.\\!ring-2') var button = gradioApp().querySelector('[style="display: block;"].tabitem div[id$=_gallery] .gallery-item.\\!ring-2')
var result = -1 var result = -1
buttons.forEach(function(v, i){ if(v==button) { result = i } }) buttons.forEach(function(v, i){ if(v==button) { result = i } })
...@@ -208,4 +208,6 @@ function update_token_counter(button_id) { ...@@ -208,4 +208,6 @@ function update_token_counter(button_id) {
function restart_reload(){ function restart_reload(){
document.body.innerHTML='<h1 style="font-family:monospace;margin-top:20%;color:lightgray;text-align:center;">Reloading...</h1>'; document.body.innerHTML='<h1 style="font-family:monospace;margin-top:20%;color:lightgray;text-align:center;">Reloading...</h1>';
setTimeout(function(){location.reload()},2000) setTimeout(function(){location.reload()},2000)
return []
} }
...@@ -5,6 +5,8 @@ import sys ...@@ -5,6 +5,8 @@ import sys
import importlib.util import importlib.util
import shlex import shlex
import platform import platform
import argparse
import json
dir_repos = "repositories" dir_repos = "repositories"
dir_extensions = "extensions" dir_extensions = "extensions"
...@@ -17,6 +19,19 @@ def extract_arg(args, name): ...@@ -17,6 +19,19 @@ def extract_arg(args, name):
return [x for x in args if x != name], name in args return [x for x in args if x != name], name in args
def extract_opt(args, name):
opt = None
is_present = False
if name in args:
is_present = True
idx = args.index(name)
del args[idx]
if idx < len(args) and args[idx][0] != "-":
opt = args[idx]
del args[idx]
return args, is_present, opt
def run(command, desc=None, errdesc=None, custom_env=None): def run(command, desc=None, errdesc=None, custom_env=None):
if desc is not None: if desc is not None:
print(desc) print(desc)
...@@ -105,22 +120,41 @@ def version_check(commit): ...@@ -105,22 +120,41 @@ def version_check(commit):
print("version check failed", e) print("version check failed", e)
def run_extensions_installers(): def run_extension_installer(extension_dir):
if not os.path.isdir(dir_extensions): path_installer = os.path.join(extension_dir, "install.py")
if not os.path.isfile(path_installer):
return return
for dirname_extension in os.listdir(dir_extensions): try:
path_installer = os.path.join(dir_extensions, dirname_extension, "install.py") env = os.environ.copy()
if not os.path.isfile(path_installer): env['PYTHONPATH'] = os.path.abspath(".")
continue
print(run(f'"{python}" "{path_installer}"', errdesc=f"Error running install.py for extension {extension_dir}", custom_env=env))
except Exception as e:
print(e, file=sys.stderr)
def list_extensions(settings_file):
settings = {}
try:
if os.path.isfile(settings_file):
with open(settings_file, "r", encoding="utf8") as file:
settings = json.load(file)
except Exception as e:
print(e, file=sys.stderr)
disabled_extensions = set(settings.get('disabled_extensions', []))
return [x for x in os.listdir(dir_extensions) if x not in disabled_extensions]
try:
env = os.environ.copy()
env['PYTHONPATH'] = os.path.abspath(".")
print(run(f'"{python}" "{path_installer}"', errdesc=f"Error running install.py for extension {dirname_extension}", custom_env=env)) def run_extensions_installers(settings_file):
except Exception as e: if not os.path.isdir(dir_extensions):
print(e, file=sys.stderr) return
for dirname_extension in list_extensions(settings_file):
run_extension_installer(os.path.join(dir_extensions, dirname_extension))
def prepare_enviroment(): def prepare_enviroment():
...@@ -130,31 +164,33 @@ def prepare_enviroment(): ...@@ -130,31 +164,33 @@ def prepare_enviroment():
gfpgan_package = os.environ.get('GFPGAN_PACKAGE', "git+https://github.com/TencentARC/GFPGAN.git@8d2447a2d918f8eba5a4a01463fd48e45126a379") 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") 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@d91a2963bf87c6a770d74894667e9ffa9f6de7ff") openclip_package = os.environ.get('OPENCLIP_PACKAGE', "git+https://github.com/mlfoundations/open_clip.git@bb6e834e9c70d9c27d0dc3ecedeebeaeb1ffad6b")
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') 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')
stable_diffusion_repo = os.environ.get('STABLE_DIFFUSION_REPO', "https://github.com/CompVis/stable-diffusion.git") stable_diffusion_repo = os.environ.get('STABLE_DIFFUSION_REPO', "https://github.com/Stability-AI/stablediffusion.git")
taming_transformers_repo = os.environ.get('TAMING_REANSFORMERS_REPO', "https://github.com/CompVis/taming-transformers.git") taming_transformers_repo = os.environ.get('TAMING_TRANSFORMERS_REPO', "https://github.com/CompVis/taming-transformers.git")
k_diffusion_repo = os.environ.get('K_DIFFUSION_REPO', 'https://github.com/crowsonkb/k-diffusion.git') k_diffusion_repo = os.environ.get('K_DIFFUSION_REPO', 'https://github.com/crowsonkb/k-diffusion.git')
codeformer_repo = os.environ.get('CODEFORMET_REPO', 'https://github.com/sczhou/CodeFormer.git') codeformer_repo = os.environ.get('CODEFORMER_REPO', 'https://github.com/sczhou/CodeFormer.git')
blip_repo = os.environ.get('BLIP_REPO', 'https://github.com/salesforce/BLIP.git') blip_repo = os.environ.get('BLIP_REPO', 'https://github.com/salesforce/BLIP.git')
stable_diffusion_commit_hash = os.environ.get('STABLE_DIFFUSION_COMMIT_HASH', "69ae4b35e0a0f6ee1af8bb9a5d0016ccb27e36dc") stable_diffusion_commit_hash = os.environ.get('STABLE_DIFFUSION_COMMIT_HASH', "47b6b607fdd31875c9279cd2f4f16b92e4ea958e")
taming_transformers_commit_hash = os.environ.get('TAMING_TRANSFORMERS_COMMIT_HASH', "24268930bf1dce879235a7fddd0b2355b84d7ea6") taming_transformers_commit_hash = os.environ.get('TAMING_TRANSFORMERS_COMMIT_HASH', "24268930bf1dce879235a7fddd0b2355b84d7ea6")
k_diffusion_commit_hash = os.environ.get('K_DIFFUSION_COMMIT_HASH', "f4e99857772fc3a126ba886aadf795a332774878") k_diffusion_commit_hash = os.environ.get('K_DIFFUSION_COMMIT_HASH', "5b3af030dd83e0297272d861c19477735d0317ec")
codeformer_commit_hash = os.environ.get('CODEFORMER_COMMIT_HASH', "c5b4593074ba6214284d6acd5f1719b6c5d739af") codeformer_commit_hash = os.environ.get('CODEFORMER_COMMIT_HASH', "c5b4593074ba6214284d6acd5f1719b6c5d739af")
blip_commit_hash = os.environ.get('BLIP_COMMIT_HASH', "48211a1594f1321b00f14c9f7a5b4813144b2fb9") blip_commit_hash = os.environ.get('BLIP_COMMIT_HASH', "48211a1594f1321b00f14c9f7a5b4813144b2fb9")
sys.argv += shlex.split(commandline_args) sys.argv += shlex.split(commandline_args)
test_argv = [x for x in sys.argv if x != '--tests']
parser = argparse.ArgumentParser()
parser.add_argument("--ui-settings-file", type=str, help="filename to use for ui settings", default='config.json')
args, _ = parser.parse_known_args(sys.argv)
sys.argv, skip_torch_cuda_test = extract_arg(sys.argv, '--skip-torch-cuda-test') 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, reinstall_xformers = extract_arg(sys.argv, '--reinstall-xformers')
sys.argv, update_check = extract_arg(sys.argv, '--update-check') sys.argv, update_check = extract_arg(sys.argv, '--update-check')
sys.argv, run_tests = extract_arg(sys.argv, '--tests') sys.argv, run_tests, test_dir = extract_opt(sys.argv, '--tests')
xformers = '--xformers' in sys.argv xformers = '--xformers' in sys.argv
deepdanbooru = '--deepdanbooru' in sys.argv
ngrok = '--ngrok' in sys.argv ngrok = '--ngrok' in sys.argv
try: try:
...@@ -177,6 +213,9 @@ def prepare_enviroment(): ...@@ -177,6 +213,9 @@ def prepare_enviroment():
if not is_installed("clip"): if not is_installed("clip"):
run_pip(f"install {clip_package}", "clip") run_pip(f"install {clip_package}", "clip")
if not is_installed("open_clip"):
run_pip(f"install {openclip_package}", "open_clip")
if (not is_installed("xformers") or reinstall_xformers) and xformers: if (not is_installed("xformers") or reinstall_xformers) and xformers:
if platform.system() == "Windows": if platform.system() == "Windows":
if platform.python_version().startswith("3.10"): if platform.python_version().startswith("3.10"):
...@@ -189,15 +228,12 @@ def prepare_enviroment(): ...@@ -189,15 +228,12 @@ def prepare_enviroment():
elif platform.system() == "Linux": elif platform.system() == "Linux":
run_pip("install xformers", "xformers") run_pip("install xformers", "xformers")
if not is_installed("deepdanbooru") and deepdanbooru:
run_pip(f"install {deepdanbooru_package}#egg=deepdanbooru[tensorflow] tensorflow==2.10.0 tensorflow-io==0.27.0", "deepdanbooru")
if not is_installed("pyngrok") and ngrok: if not is_installed("pyngrok") and ngrok:
run_pip("install pyngrok", "ngrok") run_pip("install pyngrok", "ngrok")
os.makedirs(dir_repos, exist_ok=True) os.makedirs(dir_repos, exist_ok=True)
git_clone(stable_diffusion_repo, repo_dir('stable-diffusion'), "Stable Diffusion", stable_diffusion_commit_hash) git_clone(stable_diffusion_repo, repo_dir('stable-diffusion-stability-ai'), "Stable Diffusion", stable_diffusion_commit_hash)
git_clone(taming_transformers_repo, repo_dir('taming-transformers'), "Taming Transformers", taming_transformers_commit_hash) git_clone(taming_transformers_repo, repo_dir('taming-transformers'), "Taming Transformers", taming_transformers_commit_hash)
git_clone(k_diffusion_repo, repo_dir('k-diffusion'), "K-diffusion", k_diffusion_commit_hash) git_clone(k_diffusion_repo, repo_dir('k-diffusion'), "K-diffusion", k_diffusion_commit_hash)
git_clone(codeformer_repo, repo_dir('CodeFormer'), "CodeFormer", codeformer_commit_hash) git_clone(codeformer_repo, repo_dir('CodeFormer'), "CodeFormer", codeformer_commit_hash)
...@@ -208,7 +244,7 @@ def prepare_enviroment(): ...@@ -208,7 +244,7 @@ def prepare_enviroment():
run_pip(f"install -r {requirements_file}", "requirements for Web UI") run_pip(f"install -r {requirements_file}", "requirements for Web UI")
run_extensions_installers() run_extensions_installers(settings_file=args.ui_settings_file)
if update_check: if update_check:
version_check(commit) version_check(commit)
...@@ -218,32 +254,41 @@ def prepare_enviroment(): ...@@ -218,32 +254,41 @@ def prepare_enviroment():
exit(0) exit(0)
if run_tests: if run_tests:
tests(test_argv) exitcode = tests(test_dir)
exit(0) exit(exitcode)
def tests(argv): def tests(test_dir):
if "--api" not in argv: if "--api" not in sys.argv:
argv.append("--api") sys.argv.append("--api")
if "--ckpt" not in sys.argv:
sys.argv.append("--ckpt")
sys.argv.append("./test/test_files/empty.pt")
if "--skip-torch-cuda-test" not in sys.argv:
sys.argv.append("--skip-torch-cuda-test")
print(f"Launching Web UI in another process for testing with arguments: {' '.join(argv[1:])}") print(f"Launching Web UI in another process for testing with arguments: {' '.join(sys.argv[1:])}")
with open('test/stdout.txt', "w", encoding="utf8") as stdout, open('test/stderr.txt', "w", encoding="utf8") as stderr: 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) proc = subprocess.Popen([sys.executable, *sys.argv], stdout=stdout, stderr=stderr)
import test.server_poll import test.server_poll
test.server_poll.run_tests() exitcode = test.server_poll.run_tests(proc, test_dir)
print(f"Stopping Web UI process with id {proc.pid}") print(f"Stopping Web UI process with id {proc.pid}")
proc.kill() proc.kill()
return exitcode
def start_webui(): def start():
print(f"Launching Web UI with arguments: {' '.join(sys.argv[1:])}") print(f"Launching {'API server' if '--nowebui' in sys.argv else 'Web UI'} with arguments: {' '.join(sys.argv[1:])}")
import webui import webui
webui.webui() if '--nowebui' in sys.argv:
webui.api_only()
else:
webui.webui()
if __name__ == "__main__": if __name__ == "__main__":
prepare_enviroment() prepare_enviroment()
start_webui() start()
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import inspect import inspect
from click import prompt
from pydantic import BaseModel, Field, create_model from pydantic import BaseModel, Field, create_model
from typing import Any, Optional from typing import Any, Optional
from typing_extensions import Literal from typing_extensions import Literal
from inflection import underscore from inflection import underscore
from modules.processing import StableDiffusionProcessingTxt2Img, StableDiffusionProcessingImg2Img from modules.processing import StableDiffusionProcessingTxt2Img, StableDiffusionProcessingImg2Img
from modules.shared import sd_upscalers from modules.shared import sd_upscalers, opts, parser
from typing import Dict, List
API_NOT_ALLOWED = [ API_NOT_ALLOWED = [
"self", "self",
...@@ -65,6 +65,7 @@ class PydanticModelGenerator: ...@@ -65,6 +65,7 @@ class PydanticModelGenerator:
self._model_name = model_name self._model_name = model_name
self._class_data = merge_class_params(class_instance) self._class_data = merge_class_params(class_instance)
self._model_def = [ self._model_def = [
ModelDef( ModelDef(
field=underscore(k), field=underscore(k),
...@@ -109,12 +110,12 @@ StableDiffusionImg2ImgProcessingAPI = PydanticModelGenerator( ...@@ -109,12 +110,12 @@ StableDiffusionImg2ImgProcessingAPI = PydanticModelGenerator(
).generate_model() ).generate_model()
class TextToImageResponse(BaseModel): class TextToImageResponse(BaseModel):
images: list[str] = Field(default=None, title="Image", description="The generated image in base64 format.") images: List[str] = Field(default=None, title="Image", description="The generated image in base64 format.")
parameters: dict parameters: dict
info: str info: str
class ImageToImageResponse(BaseModel): class ImageToImageResponse(BaseModel):
images: list[str] = Field(default=None, title="Image", description="The generated image in base64 format.") images: List[str] = Field(default=None, title="Image", description="The generated image in base64 format.")
parameters: dict parameters: dict
info: str info: str
...@@ -147,10 +148,10 @@ class FileData(BaseModel): ...@@ -147,10 +148,10 @@ class FileData(BaseModel):
name: str = Field(title="File name") name: str = Field(title="File name")
class ExtrasBatchImagesRequest(ExtrasBaseRequest): class ExtrasBatchImagesRequest(ExtrasBaseRequest):
imageList: list[FileData] = Field(title="Images", description="List of images to work on. Must be Base64 strings") imageList: List[FileData] = Field(title="Images", description="List of images to work on. Must be Base64 strings")
class ExtrasBatchImagesResponse(ExtraBaseResponse): class ExtrasBatchImagesResponse(ExtraBaseResponse):
images: list[str] = Field(title="Images", description="The generated images in base64 format.") images: List[str] = Field(title="Images", description="The generated images in base64 format.")
class PNGInfoRequest(BaseModel): class PNGInfoRequest(BaseModel):
image: str = Field(title="Image", description="The base64 encoded PNG image") image: str = Field(title="Image", description="The base64 encoded PNG image")
...@@ -166,3 +167,76 @@ class ProgressResponse(BaseModel): ...@@ -166,3 +167,76 @@ class ProgressResponse(BaseModel):
eta_relative: float = Field(title="ETA in secs") eta_relative: float = Field(title="ETA in secs")
state: dict = Field(title="State", description="The current state snapshot") state: dict = Field(title="State", description="The current state snapshot")
current_image: str = Field(default=None, title="Current image", description="The current image in base64 format. opts.show_progress_every_n_steps is required for this to work.") current_image: str = Field(default=None, title="Current image", description="The current image in base64 format. opts.show_progress_every_n_steps is required for this to work.")
class InterrogateRequest(BaseModel):
image: str = Field(default="", title="Image", description="Image to work on, must be a Base64 string containing the image's data.")
model: str = Field(default="clip", title="Model", description="The interrogate model used.")
class InterrogateResponse(BaseModel):
caption: str = Field(default=None, title="Caption", description="The generated caption for the image.")
fields = {}
for key, metadata in opts.data_labels.items():
value = opts.data.get(key)
optType = opts.typemap.get(type(metadata.default), type(value))
if (metadata is not None):
fields.update({key: (Optional[optType], Field(
default=metadata.default ,description=metadata.label))})
else:
fields.update({key: (Optional[optType], Field())})
OptionsModel = create_model("Options", **fields)
flags = {}
_options = vars(parser)['_option_string_actions']
for key in _options:
if(_options[key].dest != 'help'):
flag = _options[key]
_type = str
if _options[key].default is not None: _type = type(_options[key].default)
flags.update({flag.dest: (_type,Field(default=flag.default, description=flag.help))})
FlagsModel = create_model("Flags", **flags)
class SamplerItem(BaseModel):
name: str = Field(title="Name")
aliases: List[str] = Field(title="Aliases")
options: Dict[str, str] = Field(title="Options")
class UpscalerItem(BaseModel):
name: str = Field(title="Name")
model_name: Optional[str] = Field(title="Model Name")
model_path: Optional[str] = Field(title="Path")
model_url: Optional[str] = Field(title="URL")
class SDModelItem(BaseModel):
title: str = Field(title="Title")
model_name: str = Field(title="Model Name")
hash: str = Field(title="Hash")
filename: str = Field(title="Filename")
config: str = Field(title="Config file")
class HypernetworkItem(BaseModel):
name: str = Field(title="Name")
path: Optional[str] = Field(title="Path")
class FaceRestorerItem(BaseModel):
name: str = Field(title="Name")
cmd_dir: Optional[str] = Field(title="Path")
class RealesrganItem(BaseModel):
name: str = Field(title="Name")
path: Optional[str] = Field(title="Path")
scale: Optional[int] = Field(title="Scale")
class PromptStyleItem(BaseModel):
name: str = Field(title="Name")
prompt: Optional[str] = Field(title="Prompt")
negative_prompt: Optional[str] = Field(title="Negative Prompt")
class ArtistItem(BaseModel):
name: str = Field(title="Name")
score: float = Field(title="Score")
category: str = Field(title="Category")
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...@@ -36,6 +36,7 @@ def setup_model(dirname): ...@@ -36,6 +36,7 @@ def setup_model(dirname):
from basicsr.utils.download_util import load_file_from_url from basicsr.utils.download_util import load_file_from_url
from basicsr.utils import imwrite, img2tensor, tensor2img from basicsr.utils import imwrite, img2tensor, tensor2img
from facelib.utils.face_restoration_helper import FaceRestoreHelper from facelib.utils.face_restoration_helper import FaceRestoreHelper
from facelib.detection.retinaface import retinaface
from modules.shared import cmd_opts from modules.shared import cmd_opts
net_class = CodeFormer net_class = CodeFormer
...@@ -65,6 +66,8 @@ def setup_model(dirname): ...@@ -65,6 +66,8 @@ def setup_model(dirname):
net.load_state_dict(checkpoint) net.load_state_dict(checkpoint)
net.eval() net.eval()
if hasattr(retinaface, 'device'):
retinaface.device = devices.device_codeformer
face_helper = FaceRestoreHelper(1, face_size=512, crop_ratio=(1, 1), det_model='retinaface_resnet50', save_ext='png', use_parse=True, device=devices.device_codeformer) face_helper = FaceRestoreHelper(1, face_size=512, crop_ratio=(1, 1), det_model='retinaface_resnet50', save_ext='png', use_parse=True, device=devices.device_codeformer)
self.net = net self.net = net
......
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...@@ -199,7 +199,7 @@ def upscale_without_tiling(model, img): ...@@ -199,7 +199,7 @@ def upscale_without_tiling(model, img):
img = img[:, :, ::-1] img = img[:, :, ::-1]
img = np.ascontiguousarray(np.transpose(img, (2, 0, 1))) / 255 img = np.ascontiguousarray(np.transpose(img, (2, 0, 1))) / 255
img = torch.from_numpy(img).float() img = torch.from_numpy(img).float()
img = devices.mps_contiguous_to(img.unsqueeze(0), devices.device_esrgan) img = img.unsqueeze(0).to(devices.device_esrgan)
with torch.no_grad(): with torch.no_grad():
output = model(img) output = model(img)
output = output.squeeze().float().cpu().clamp_(0, 1).numpy() output = output.squeeze().float().cpu().clamp_(0, 1).numpy()
......
...@@ -6,7 +6,6 @@ import git ...@@ -6,7 +6,6 @@ import git
from modules import paths, shared from modules import paths, shared
extensions = [] extensions = []
extensions_dir = os.path.join(paths.script_path, "extensions") extensions_dir = os.path.join(paths.script_path, "extensions")
...@@ -34,8 +33,11 @@ class Extension: ...@@ -34,8 +33,11 @@ class Extension:
if repo is None or repo.bare: if repo is None or repo.bare:
self.remote = None self.remote = None
else: else:
self.remote = next(repo.remote().urls, None) try:
self.status = 'unknown' self.remote = next(repo.remote().urls, None)
self.status = 'unknown'
except Exception:
self.remote = None
def list_files(self, subdir, extension): def list_files(self, subdir, extension):
from modules import scripts from modules import scripts
...@@ -63,9 +65,12 @@ class Extension: ...@@ -63,9 +65,12 @@ class Extension:
self.can_update = False self.can_update = False
self.status = "latest" self.status = "latest"
def pull(self): def fetch_and_reset_hard(self):
repo = git.Repo(self.path) repo = git.Repo(self.path)
repo.remotes.origin.pull() # Fix: `error: Your local changes to the following files would be overwritten by merge`,
# because WSL2 Docker set 755 file permissions instead of 644, this results to the error.
repo.git.fetch('--all')
repo.git.reset('--hard', 'origin')
def list_extensions(): def list_extensions():
...@@ -81,3 +86,4 @@ def list_extensions(): ...@@ -81,3 +86,4 @@ def list_extensions():
extension = Extension(name=dirname, path=path, enabled=dirname not in shared.opts.disabled_extensions) extension = Extension(name=dirname, path=path, enabled=dirname not in shared.opts.disabled_extensions)
extensions.append(extension) extensions.append(extension)
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...@@ -36,7 +36,9 @@ def gfpgann(): ...@@ -36,7 +36,9 @@ def gfpgann():
else: else:
print("Unable to load gfpgan model!") print("Unable to load gfpgan model!")
return None return None
model = gfpgan_constructor(model_path=model_file, upscale=1, arch='clean', channel_multiplier=2, bg_upsampler=None) if hasattr(facexlib.detection.retinaface, 'device'):
facexlib.detection.retinaface.device = devices.device_gfpgan
model = gfpgan_constructor(model_path=model_file, upscale=1, arch='clean', channel_multiplier=2, bg_upsampler=None, device=devices.device_gfpgan)
loaded_gfpgan_model = model loaded_gfpgan_model = model
return model return model
......
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...@@ -9,7 +9,7 @@ from modules import devices, sd_hijack, shared ...@@ -9,7 +9,7 @@ from modules import devices, sd_hijack, shared
from modules.hypernetworks import hypernetwork from modules.hypernetworks import hypernetwork
not_available = ["hardswish", "multiheadattention"] not_available = ["hardswish", "multiheadattention"]
keys = ["linear"] + list(x for x in hypernetwork.HypernetworkModule.activation_dict.keys() if x not in not_available) keys = list(x for x in hypernetwork.HypernetworkModule.activation_dict.keys() if x not in not_available)
def create_hypernetwork(name, enable_sizes, overwrite_old, layer_structure=None, activation_func=None, weight_init=None, add_layer_norm=False, use_dropout=False): def create_hypernetwork(name, enable_sizes, overwrite_old, layer_structure=None, activation_func=None, weight_init=None, add_layer_norm=False, use_dropout=False):
# Remove illegal characters from name. # Remove illegal characters from name.
......
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...@@ -148,8 +148,7 @@ class InterrogateModels: ...@@ -148,8 +148,7 @@ class InterrogateModels:
clip_image = self.clip_preprocess(pil_image).unsqueeze(0).type(self.dtype).to(devices.device_interrogate) clip_image = self.clip_preprocess(pil_image).unsqueeze(0).type(self.dtype).to(devices.device_interrogate)
precision_scope = torch.autocast if shared.cmd_opts.precision == "autocast" else contextlib.nullcontext with torch.no_grad(), devices.autocast():
with torch.no_grad(), precision_scope("cuda"):
image_features = self.clip_model.encode_image(clip_image).type(self.dtype) image_features = self.clip_model.encode_image(clip_image).type(self.dtype)
image_features /= image_features.norm(dim=-1, keepdim=True) image_features /= image_features.norm(dim=-1, keepdim=True)
......
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