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Merge branch 'master' into fix/progress-api

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This commit is contained in:
evshiron 2022-11-02 12:31:33 +08:00
commit 51e0a83969
31 changed files with 1911 additions and 1165 deletions
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35
javascript/extensions.js Normal file
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@ -0,0 +1,35 @@
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 []
}
function install_extension_from_index(button, url){
button.disabled = "disabled"
button.value = "Installing..."
textarea = gradioApp().querySelector('#extension_to_install textarea')
textarea.value = url
textarea.dispatchEvent(new Event("input", { bubbles: true }))
gradioApp().querySelector('#install_extension_button').click()
}

29
launch.py
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@ -7,6 +7,7 @@ import shlex
import platform
dir_repos = "repositories"
dir_extensions = "extensions"
python = sys.executable
git = os.environ.get('GIT', "git")
index_url = os.environ.get('INDEX_URL', "")
@ -16,11 +17,11 @@ def extract_arg(args, name):
return [x for x in args if x != name], name in args
def run(command, desc=None, errdesc=None):
def run(command, desc=None, errdesc=None, custom_env=None):
if desc is not None:
print(desc)
result = subprocess.run(command, stdout=subprocess.PIPE, stderr=subprocess.PIPE, shell=True)
result = subprocess.run(command, stdout=subprocess.PIPE, stderr=subprocess.PIPE, shell=True, env=os.environ if custom_env is None else custom_env)
if result.returncode != 0:
@ -101,9 +102,27 @@ def version_check(commit):
else:
print("Not a git clone, can't perform version check.")
except Exception as e:
print("versipm check failed",e)
print("version check failed", e)
def run_extensions_installers():
if not os.path.isdir(dir_extensions):
return
for dirname_extension in os.listdir(dir_extensions):
path_installer = os.path.join(dir_extensions, dirname_extension, "install.py")
if not os.path.isfile(path_installer):
continue
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))
except Exception as e:
print(e, file=sys.stderr)
def prepare_enviroment():
torch_command = os.environ.get('TORCH_COMMAND', "pip install torch==1.12.1+cu113 torchvision==0.13.1+cu113 --extra-index-url https://download.pytorch.org/whl/cu113")
requirements_file = os.environ.get('REQS_FILE', "requirements_versions.txt")
@ -189,6 +208,8 @@ def prepare_enviroment():
run_pip(f"install -r {requirements_file}", "requirements for Web UI")
run_extensions_installers()
if update_check:
version_check(commit)

4
localizations/de_DE.json
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@ -70,7 +70,7 @@
"None": "Nichts",
"Prompt matrix": "Promptmatrix",
"Prompts from file or textbox": "Prompts aus Datei oder Textfeld",
"X/Y plot": "X/Y Graf",
"X/Y plot": "X/Y Graph",
"Put variable parts at start of prompt": "Variable teile am start des Prompt setzen",
"Iterate seed every line": "Iterate seed every line",
"List of prompt inputs": "List of prompt inputs",
@ -455,4 +455,4 @@
"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.": "Gilt nur für Inpainting-Modelle. Legt fest, wie stark das Originalbild für Inpainting und img2img maskiert werden soll. 1.0 bedeutet vollständig maskiert, was das Standardverhalten ist. 0.0 bedeutet eine vollständig unmaskierte Konditionierung. Niedrigere Werte tragen dazu bei, die Gesamtkomposition des Bildes zu erhalten, sind aber bei großen Änderungen problematisch.",
"List of setting names, separated by commas, for settings that should go to the quick access bar at the top, rather than the usual setting tab. See modules/shared.py for setting names. Requires restarting to apply.": "Liste von Einstellungsnamen, getrennt durch Kommas, für Einstellungen, die in der Schnellzugriffsleiste oben erscheinen sollen, anstatt in dem üblichen Einstellungs-Tab. Siehe modules/shared.py für Einstellungsnamen. Erfordert einen Neustart zur Anwendung.",
"If this values is non-zero, it will be added to seed and used to initialize RNG for noises when using samplers with Eta. You can use this to produce even more variation of images, or you can use this to match images of other software if you know what you are doing.": "Wenn dieser Wert ungleich Null ist, wird er zum Seed addiert und zur Initialisierung des RNG für Noise bei der Verwendung von Samplern mit Eta verwendet. Dies kann verwendet werden, um noch mehr Variationen von Bildern zu erzeugen, oder um Bilder von anderer Software zu erzeugen, wenn Sie wissen, was Sie tun."
}
}

2287
localizations/it_IT.json
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File diff suppressed because it is too large Load Diff

61
localizations/ko_KR.json
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@ -9,11 +9,13 @@
" images in this directory. Loaded ": "개의 이미지가 이 경로에 존재합니다. ",
" pages": "페이지로 나뉘어 표시합니다.",
", divided into ": "입니다. ",
". Use Installed tab to restart.": "에 성공적으로 설치하였습니다. 설치된 확장기능 탭에서 UI를 재시작해주세요.",
"1st and last digit must be 1. ex:'1, 2, 1'": "1st and last digit must be 1. ex:'1, 2, 1'",
"[wiki]": " [위키] 참조",
"A directory on the same machine where the server is running.": "WebUI 서버가 돌아가고 있는 디바이스에 존재하는 디렉토리를 선택해 주세요.",
"A merger of the two checkpoints will be generated in your": "체크포인트들이 병합된 결과물이 당신의",
"A value that determines the output of random number generator - if you create an image with same parameters and seed as another image, you'll get the same result": "난수 생성기의 결과물을 지정하는 값 - 동일한 설정값과 동일한 시드를 적용 시, 완전히 똑같은 결과물을 얻게 됩니다.",
"Action": "작업",
"Add a random artist to the prompt.": "프롬프트에 랜덤한 작가 추가",
"Add a second progress bar to the console that shows progress for an entire job.": "콘솔에 전체 작업의 진행도를 보여주는 2번째 프로그레스 바 추가하기",
"Add difference": "차이점 추가",
@ -22,6 +24,8 @@
"Add model hash to generation information": "생성 정보에 모델 해시 추가",
"Add model name to generation information": "생성 정보에 모델 이름 추가",
"Add number to filename when saving": "이미지를 저장할 때 파일명에 숫자 추가하기",
"Aesthetic Gradients": "스타일 그라디언트",
"Aesthetic Image Scorer": "스타일 이미지 스코어러",
"Aesthetic imgs embedding": "스타일 이미지 임베딩",
"Aesthetic learning rate": "스타일 학습 수",
"Aesthetic steps": "스타일 스텝 수",
@ -33,22 +37,31 @@
"Always save all generated images": "생성된 이미지 항상 저장하기",
"api": "",
"append": "뒤에 삽입",
"Append commas": "쉼표 삽입",
"Apply and restart UI": "적용 후 UI 재시작",
"Apply color correction to img2img results to match original colors.": "이미지→이미지 결과물이 기존 색상과 일치하도록 색상 보정 적용하기",
"Apply selected styles to current prompt": "현재 프롬프트에 선택된 스타일 적용",
"Apply settings": "설정 적용하기",
"Artists to study": "연구할만한 작가들",
"Auto focal point crop": "초점 기준 크롭(자동 감지)",
"Autocomplete options": "자동완성 설정",
"Available": "지원되는 확장기능 목록",
"Batch count": "배치 수",
"Batch from Directory": "저장 경로로부터 여러장 처리",
"Batch img2img": "이미지→이미지 배치",
"Batch Process": "이미지 여러장 처리",
"Batch size": "배치 크기",
"behind": "최신 아님",
"BSRGAN 4x": "BSRGAN 4x",
"built with gradio": "gradio로 제작되었습니다",
"Calculates aesthetic score for generated images using CLIP+MLP Aesthetic Score Predictor based on Chad Scorer": "Chad 스코어러를 기반으로 한 CLIP+MLP 스타일 점수 예측기를 이용해 생성된 이미지의 스타일 점수를 계산합니다.",
"Cancel generate forever": "반복 생성 취소",
"cfg cnt": "CFG 변화 횟수",
"cfg count": "CFG 변화 횟수",
"CFG Scale": "CFG 스케일",
"cfg1 min/max": "CFG1 최소/최대",
"cfg2 min/max": "CFG2 최소/최대",
"Check for updates": "업데이트 확인",
"Check progress": "진행도 체크",
"Check progress (first)": "진행도 체크 (처음)",
"checkpoint": " 체크포인트 ",
@ -64,10 +77,14 @@
"CodeFormer weight parameter; 0 = maximum effect; 1 = minimum effect": "CodeFormer 가중치 설정값 (0 = 최대 효과, 1 = 최소 효과)",
"Collect": "즐겨찾기",
"Color variation": "색깔 다양성",
"Combinations": "조합",
"Combinatorial batches": "조합 배치 수",
"Combinatorial generation": "조합 생성",
"copy": "복사",
"Create a grid where images will have different parameters. Use inputs below to specify which parameters will be shared by columns and rows": "서로 다른 설정값으로 생성된 이미지의 그리드를 만듭니다. 아래의 설정으로 가로/세로에 어떤 설정값을 적용할지 선택하세요.",
"Create a text file next to every image with generation parameters.": "생성된 이미지마다 생성 설정값을 담은 텍스트 파일 생성하기",
"Create aesthetic images embedding": "스타일 이미지 임베딩 생성하기",
"Create an embedding from one or few pictures and use it to apply their style to generated images.": "하나 혹은 그 이상의 이미지들로부터 임베딩을 생성해, 그 이미지들의 스타일을 다른 이미지 생성 시 적용할 수 있게 해줍니다.",
"Create debug image": "디버그 이미지 생성",
"Create embedding": "임베딩 생성",
"Create flipped copies": "좌우로 뒤집은 복사본 생성",
@ -78,14 +95,18 @@
"custom fold": "커스텀 경로",
"Custom Name (Optional)": "병합 모델 이름 (선택사항)",
"Dataset directory": "데이터셋 경로",
"Dataset Tag Editor": "데이터셋 태그 편집기",
"date": "생성 일자",
"DDIM": "DDIM",
"Decode CFG scale": "디코딩 CFG 스케일",
"Decode steps": "디코딩 스텝 수",
"Delete": "삭제",
"delete next": "선택한 이미지부터 시작해서 삭제할 이미지 갯수",
"Denoising": "디노이징",
"Denoising Diffusion Implicit Models - best at inpainting": "Denoising Diffusion Implicit Models - 인페이팅에 뛰어남",
"Denoising strength": "디노이즈 강도",
"Denoising strength change factor": "디노이즈 강도 변경 배수",
"Description": "설명",
"Destination directory": "결과물 저장 경로",
"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.": "알고리즘이 얼마나 원본 이미지를 반영할지를 결정하는 수치입니다. 0일 경우 아무것도 바뀌지 않고, 1일 경우 원본 이미지와 전혀 관련없는 결과물을 얻게 됩니다. 1.0 아래의 값일 경우, 설정된 샘플링 스텝 수보다 적은 스텝 수를 거치게 됩니다.",
"Directory for saving images using the Save button": "저장 버튼을 이용해 저장하는 이미지들의 저장 경로",
@ -108,6 +129,8 @@
"Draw mask": "마스크 직접 그리기",
"Drop File Here": "파일을 끌어 놓으세요",
"Drop Image Here": "이미지를 끌어 놓으세요",
"Dropdown": "드롭다운",
"Dynamic Prompts": "다이나믹 프롬프트",
"Embedding": "임베딩",
"Embedding Learning rate": "임베딩 학습률",
"Emphasis: use (text) to make model pay more attention to text and [text] to make it pay less attention": "강조 : (텍스트)를 이용해 모델의 텍스트에 대한 가중치를 더 강하게 주고 [텍스트]를 이용해 더 약하게 줍니다.",
@ -127,6 +150,9 @@
"Euler a": "Euler a",
"Euler Ancestral - very creative, each can get a completely different picture depending on step count, setting steps to higher than 30-40 does not help": "Euler Ancestral - 매우 창의적, 스텝 수에 따라 완전히 다른 결과물이 나올 수 있음. 30~40보다 높은 스텝 수는 효과가 미미함",
"Existing Caption txt Action": "이미 존재하는 캡션 텍스트 처리",
"Extension": "확장기능",
"Extension index URL": "확장기능 목록 URL",
"Extensions": "확장기능",
"Extra": "고급",
"Extras": "부가기능",
"extras": "부가기능",
@ -134,7 +160,7 @@
"Face restoration": "얼굴 보정",
"Face restoration model": "얼굴 보정 모델",
"Fall-off exponent (lower=higher detail)": "감쇠 지수 (낮을수록 디테일이 올라감)",
"favorites": "즐겨찾기",
"Favorites": "즐겨찾기",
"File": "파일",
"File format for grids": "그리드 이미지 파일 형식",
"File format for images": "이미지 파일 형식",
@ -150,6 +176,7 @@
"First Page": "처음 페이지",
"Firstpass height": "초기 세로길이",
"Firstpass width": "초기 가로길이",
"Fixed seed": "시드 고정",
"Focal point edges weight": "경계면 가중치",
"Focal point entropy weight": "엔트로피 가중치",
"Focal point face weight": "얼굴 가중치",
@ -184,8 +211,10 @@
"ignore": "무시",
"Image": "이미지",
"Image Browser": "이미지 브라우저",
"Image browser": "이미지 브라우저",
"Image for img2img": "Image for img2img",
"Image for inpainting with mask": "마스크로 인페인팅할 이미지",
"Image not found (may have been already moved)": "이미지를 찾을 수 없습니다 (이미 옮겨졌을 수 있음)",
"Images Browser": "이미지 브라우저",
"Images directory": "이미지 경로",
"Images filename pattern": "이미지 파일명 패턴",
@ -193,6 +222,7 @@
"img2img alternative test": "이미지→이미지 대체버전 테스트",
"img2img DDIM discretize": "이미지→이미지 DDIM 이산화",
"img2img history": "이미지→이미지 기록",
"Implements an expressive template language for random or combinatorial prompt generation along with features to support deep wildcard directory structures.": "무작위/조합 프롬프트 생성을 위한 문법과 복잡한 와일드카드 구조를 지원합니다.",
"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.": "루프백 모드에서는 매 루프마다 디노이즈 강도에 이 값이 곱해집니다. 1보다 작을 경우 다양성이 낮아져 결과 이미지들이 고정된 형태로 모일 겁니다. 1보다 클 경우 다양성이 높아져 결과 이미지들이 갈수록 혼란스러워지겠죠.",
"Include Separate Images": "분리된 이미지 포함하기",
"Increase coherency by padding from the last comma within n tokens when using more than 75 tokens": "75개보다 많은 토큰을 사용시 마지막 쉼표로부터 N개의 토큰 이내에 패딩을 추가해 통일성 증가시키기",
@ -205,6 +235,11 @@
"Inpainting conditioning mask strength": "인페인팅 조절 마스크 강도",
"Input directory": "인풋 이미지 경로",
"Input images directory": "이미지 경로 입력",
"Inspiration": "\"영감\"",
"Install": "설치",
"Install from URL": "URL로부터 확장기능 설치",
"Installed": "설치된 확장기능",
"Installed into ": "확장기능을 ",
"Interpolation Method": "보간 방법",
"Interrogate\nCLIP": "CLIP\n분석",
"Interrogate\nDeepBooru": "DeepBooru\n분석",
@ -223,6 +258,7 @@
"Just resize": "리사이징",
"Keep -1 for seeds": "시드값 -1로 유지",
"keep whatever was there originally": "이미지 원본 유지",
"keyword": "프롬프트",
"Label": "라벨",
"Lanczos": "Lanczos",
"Last prompt:": "마지막 프롬프트 : ",
@ -230,23 +266,29 @@
"Last saved image:": "마지막으로 저장된 이미지 : ",
"latent noise": "잠재 노이즈",
"latent nothing": "잠재 공백",
"latest": "최신 버전",
"LDSR": "LDSR",
"LDSR processing steps. Lower = faster": "LDSR 스텝 수. 낮은 값 = 빠른 속도",
"leakyrelu": "leakyrelu",
"Leave blank to save images to the default path.": "기존 저장 경로에 이미지들을 저장하려면 비워두세요.",
"Leave empty for auto": "자동 설정하려면 비워두십시오",
"left": "왼쪽",
"Lets you edit captions in training datasets.": "훈련에 사용되는 데이터셋의 캡션을 수정할 수 있게 해줍니다.",
"linear": "linear",
"List of prompt inputs": "프롬프트 입력 리스트",
"List of setting names, separated by commas, for settings that should go to the quick access bar at the top, rather than the usual setting tab. See modules/shared.py for setting names. Requires restarting to apply.": "설정 탭이 아니라 상단의 빠른 설정 바에 위치시킬 설정 이름을 쉼표로 분리해서 입력하십시오. 설정 이름은 modules/shared.py에서 찾을 수 있습니다. 재시작이 필요합니다.",
"LMS": "LMS",
"LMS Karras": "LMS Karras",
"Load": "불러오기",
"Load from:": "URL로부터 불러오기",
"Loading...": "로딩 중...",
"Local directory name": "로컬 경로 이름",
"Localization (requires restart)": "현지화 (재시작 필요)",
"Log directory": "로그 경로",
"Loopback": "루프백",
"Loops": "루프 수",
"Loss:": "손실(Loss) : ",
"Magic prompt": "매직 프롬프트",
"Make an attempt to produce a picture similar to what would have been produced with same seed at specified resolution": "동일한 시드 값으로 생성되었을 이미지를 주어진 해상도로 최대한 유사하게 재현합니다.",
"Make K-diffusion samplers produce same images in a batch as when making a single image": "K-diffusion 샘플러들이 단일 이미지를 생성하는 것처럼 배치에서도 동일한 이미지를 생성하게 하기",
"Make Zip when Save?": "저장 시 Zip 생성하기",
@ -260,7 +302,9 @@
"Minimum number of pages per load": "한번 불러올 때마다 불러올 최소 페이지 수",
"Modules": "모듈",
"Move face restoration model from VRAM into RAM after processing": "처리가 완료되면 얼굴 보정 모델을 VRAM에서 RAM으로 옮기기",
"Move to favorites": "즐겨찾기로 옮기기",
"Move VAE and CLIP to RAM when training hypernetwork. Saves VRAM.": "하이퍼네트워크 훈련 진행 시 VAE와 CLIP을 RAM으로 옮기기. VRAM이 절약됩니다.",
"Moved to favorites": "즐겨찾기로 옮겨짐",
"Multiplier (M) - set to 0 to get model A": "배율 (M) - 0으로 적용하면 모델 A를 얻게 됩니다",
"Name": "이름",
"Negative prompt": "네거티브 프롬프트",
@ -285,6 +329,7 @@
"original": "원본 유지",
"Original negative prompt": "기존 네거티브 프롬프트",
"Original prompt": "기존 프롬프트",
"Others": "기타",
"Outpainting direction": "아웃페인팅 방향",
"Outpainting mk2": "아웃페인팅 마크 2",
"Output directory": "이미지 저장 경로",
@ -303,6 +348,7 @@
"Overwrite Old Hypernetwork": "기존 하이퍼네트워크 덮어쓰기",
"Page Index": "페이지 인덱스",
"parameters": "설정값",
"path name": "경로 이름",
"Path to directory where to write outputs": "결과물을 출력할 경로",
"Path to directory with input images": "인풋 이미지가 있는 경로",
"Paths for saving": "저장 경로",
@ -330,6 +376,7 @@
"Prompt template file": "프롬프트 템플릿 파일 경로",
"Prompts": "프롬프트",
"Prompts from file or textbox": "파일이나 텍스트박스로부터 프롬프트 불러오기",
"Provides an interface to browse created images in the web browser.": "생성된 이미지를 브라우저 내에서 볼 수 있는 인터페이스를 추가합니다.",
"Put variable parts at start of prompt": "변경되는 프롬프트를 앞에 위치시키기",
"quad": "quad",
"Quality for saved jpeg images": "저장된 jpeg 이미지들의 품질",
@ -337,11 +384,13 @@
"R-ESRGAN 4x+ Anime6B": "R-ESRGAN 4x+ Anime6B",
"Random": "랜덤",
"Random grid": "랜덤 그리드",
"Randomly display the pictures of the artist's or artistic genres typical style, more pictures of this artist or genre is displayed after selecting. So you don't have to worry about how hard it is to choose the right style of art when you create.": "특정 작가 또는 스타일의 이미지들 중 하나를 무작위로 보여줍니다. 선택 후 선택한 작가 또는 스타일의 이미지들이 더 나타나게 됩니다. 고르기 어려워도 걱정하실 필요 없어요!",
"Randomness": "랜덤성",
"Read generation parameters from prompt or last generation if prompt is empty into user interface.": "클립보드에 복사된 정보로부터 설정값 읽어오기/프롬프트창이 비어있을경우 제일 최근 설정값 불러오기",
"Read parameters (prompt, etc...) from txt2img tab when making previews": "프리뷰 이미지 생성 시 텍스트→이미지 탭에서 설정값(프롬프트 등) 읽어오기",
"Recommended settings: Sampling Steps: 80-100, Sampler: Euler a, Denoising strength: 0.8": "추천 설정값 - 샘플링 스텝 수 : 80-100 , 샘플러 : Euler a, 디노이즈 강도 : 0.8",
"Reload custom script bodies (No ui updates, No restart)": "커스텀 스크립트 리로드하기(UI 업데이트 없음, 재시작 없음)",
"Reloading...": "재시작 중...",
"relu": "relu",
"Renew Page": "Renew Page",
"Request browser notifications": "브라우저 알림 권한 요청",
@ -361,6 +410,7 @@
"Reuse seed from last generation, mostly useful if it was randomed": "이전 생성에서 사용된 시드를 불러옵니다. 랜덤하게 생성했을 시 도움됨",
"right": "오른쪽",
"Run": "가동",
"Sample extension. Allows you to use __name__ syntax in your prompt to get a random line from a file named name.txt in the wildcards directory. Also see Dynamic Prompts for similar functionality.": "샘플 확장기능입니다. __이름__형식의 문법을 사용해 와일드카드 경로 내의 이름.txt파일로부터 무작위 프롬프트를 적용할 수 있게 해줍니다. 유사한 확장기능으로 다이나믹 프롬프트가 있습니다.",
"Sampler": "샘플러",
"Sampler parameters": "샘플러 설정값",
"Sampling method": "샘플링 방법",
@ -412,6 +462,7 @@
"Show progressbar": "프로그레스 바 보이기",
"Show result images": "이미지 결과 보이기",
"Show Textbox": "텍스트박스 보이기",
"Shows a gallery of generated pictures by artists separated into categories.": "생성된 이미지들을 작가별로 분류해 보여줍니다. 원본 - https://artiststostudy.pages.dev",
"Sigma adjustment for finding noise for image": "이미지 노이즈를 찾기 위해 시그마 조정",
"Sigma Churn": "시그마 섞기",
"sigma churn": "시그마 섞기",
@ -424,6 +475,7 @@
"Skip": "건너뛰기",
"Slerp angle": "구면 선형 보간 각도",
"Slerp interpolation": "구면 선형 보간",
"sort by": "정렬 기준",
"Source": "원본",
"Source directory": "원본 경로",
"Split image overlap ratio": "이미지 분할 겹침 비율",
@ -431,6 +483,7 @@
"Split oversized images": "사이즈가 큰 이미지 분할하기",
"Stable Diffusion": "Stable Diffusion",
"Stable Diffusion checkpoint": "Stable Diffusion 체크포인트",
"step cnt": "스텝 변화 횟수",
"step count": "스텝 변화 횟수",
"step1 min/max": "스텝1 최소/최대",
"step2 min/max": "스텝2 최소/최대",
@ -447,6 +500,7 @@
"System": "시스템",
"Tertiary model (C)": "3차 모델 (C)",
"Textbox": "텍스트박스",
"The official port of Deforum, an extensive script for 2D and 3D animations, supporting keyframable sequences, dynamic math parameters (even inside the prompts), dynamic masking, depth estimation and warping.": "Deforum의 공식 포팅 버전입니다. 2D와 3D 애니메이션, 키프레임 시퀀스, 수학적 매개변수, 다이나믹 마스킹 등을 지원합니다.",
"This regular expression will be used extract words from filename, and they will be joined using the option below into label text used for training. Leave empty to keep filename text as it is.": "이 정규표현식은 파일명으로부터 단어를 추출하는 데 사용됩니다. 추출된 단어들은 하단의 설정을 이용해 라벨 텍스트로 변환되어 훈련에 사용됩니다. 파일명 텍스트를 유지하려면 비워두십시오.",
"This string will be used to join split words into a single line if the option above is enabled.": "이 문자열은 상단 설정이 활성화되어있을 때 분리된 단어들을 한 줄로 합치는 데 사용됩니다.",
"This text is used to rotate the feature space of the imgs embs": "이 텍스트는 이미지 임베딩의 특징 공간을 회전하는 데 사용됩니다.",
@ -467,7 +521,9 @@
"txt2img": "텍스트→이미지",
"txt2img history": "텍스트→이미지 기록",
"uniform": "uniform",
"unknown": "알수 없음",
"up": "위쪽",
"Update": "업데이트",
"Upload mask": "마스크 업로드하기",
"Upload prompt inputs": "입력할 프롬프트를 업로드하십시오",
"Upscale Before Restoring Faces": "얼굴 보정을 진행하기 전에 업스케일링 먼저 진행하기",
@ -479,9 +535,12 @@
"Upscaler 2 visibility": "업스케일러 2 가시성",
"Upscaler for img2img": "이미지→이미지 업스케일러",
"Upscaling": "업스케일링",
"URL for extension's git repository": "확장기능의 git 레포 URL",
"Use a two step process to partially create an image at smaller resolution, upscale, and then improve details in it without changing composition": "저해상도 이미지를 1차적으로 생성 후 업스케일을 진행하여, 이미지의 전체적인 구성을 바꾸지 않고 세부적인 디테일을 향상시킵니다.",
"Use an empty output directory to save pictures normally instead of writing to the output directory.": "저장 경로를 비워두면 기본 저장 폴더에 이미지들이 저장됩니다.",
"Use BLIP for caption": "캡션에 BLIP 사용",
"Use checkbox to enable the extension; it will be enabled or disabled when you click apply button": "체크박스를 이용해 적용할 확장기능을 선택하세요. 변경사항은 적용 후 UI 재시작 버튼을 눌러야 적용됩니다.",
"Use checkbox to mark the extension for update; it will be updated when you click apply button": "체크박스를 이용해 업데이트할 확장기능을 선택하세요. 업데이트는 적용 후 UI 재시작 버튼을 눌러야 적용됩니다.",
"Use deepbooru for caption": "캡션에 deepbooru 사용",
"Use dropout": "드롭아웃 사용",
"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.": "다음 태그들을 사용해 이미지 파일명 형식을 결정하세요 : [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]. 비워두면 기본값으로 설정됩니다.",

53
localizations/pt_BR.json
View File

@ -17,6 +17,7 @@
"Checkpoint Merger": "Fusão de Checkpoint",
"Train": "Treinar",
"Settings": "Configurações",
"Extensions": "Extensions",
"Prompt": "Prompt",
"Negative prompt": "Prompt negativo",
"Run": "Executar",
@ -93,13 +94,13 @@
"Eta": "Tempo estimado",
"Clip skip": "Pular Clip",
"Denoising": "Denoising",
"Cond. Image Mask Weight": "Peso da Máscara Condicional de Imagem",
"X values": "Valores de X",
"Y type": "Tipo de Y",
"Y values": "Valores de Y",
"Draw legend": "Desenhar a legenda",
"Include Separate Images": "Incluir Imagens Separadas",
"Keep -1 for seeds": "Manter em -1 para seeds",
"Drop Image Here": "Solte a imagem aqui",
"Save": "Salvar",
"Send to img2img": "Mandar para img2img",
"Send to inpaint": "Mandar para inpaint",
@ -110,6 +111,7 @@
"Inpaint": "Inpaint",
"Batch img2img": "Lote img2img",
"Image for img2img": "Imagem para img2img",
"Drop Image Here": "Solte a imagem aqui",
"Image for inpainting with mask": "Imagem para inpainting com máscara",
"Mask": "Máscara",
"Mask blur": "Desfoque da máscara",
@ -166,16 +168,10 @@
"Upscaler": "Ampliador",
"Lanczos": "Lanczos",
"LDSR": "LDSR",
"4x_foolhardy_Remacri": "4x_foolhardy_Remacri",
"Put ESRGAN models here": "Coloque modelos ESRGAN aqui",
"R-ESRGAN General 4xV3": "R-ESRGAN General 4xV3",
"R-ESRGAN AnimeVideo": "R-ESRGAN AnimeVideo",
"R-ESRGAN 4x+": "R-ESRGAN 4x+",
"R-ESRGAN 4x+ Anime6B": "R-ESRGAN 4x+ Anime6B",
"R-ESRGAN 2x+": "R-ESRGAN 2x+",
"ScuNET": "ScuNET",
"ESRGAN_4x": "ESRGAN_4x",
"ScuNET GAN": "ScuNET GAN",
"ScuNET PSNR": "ScuNET PSNR",
"put_swinir_models_here": "put_swinir_models_here",
"SwinIR 4x": "SwinIR 4x",
"Single Image": "Uma imagem",
"Batch Process": "Processo em lote",
"Batch from Directory": "Lote apartir de diretório",
@ -189,7 +185,7 @@
"GFPGAN visibility": "Visibilidade GFPGAN",
"CodeFormer visibility": "Visibilidade CodeFormer",
"CodeFormer weight (0 = maximum effect, 1 = minimum effect)": "Peso do CodeFormer (0 = efeito máximo, 1 = efeito mínimo)",
"Open output directory": "Abrir diretório de saída",
"Upscale Before Restoring Faces": "Ampliar Antes de Refinar Rostos",
"Send to txt2img": "Mandar para txt2img",
"A merger of the two checkpoints will be generated in your": "Uma fusão dos dois checkpoints será gerada em seu",
"checkpoint": "checkpoint",
@ -216,6 +212,7 @@
"Modules": "Módulos",
"Enter hypernetwork layer structure": "Entrar na estrutura de camadas da hypernetwork",
"Select activation function of hypernetwork": "Selecionar a função de ativação de hypernetwork",
"linear": "linear",
"relu": "relu",
"leakyrelu": "leakyrelu",
"elu": "elu",
@ -227,12 +224,10 @@
"glu": "glu",
"hardshrink": "hardshrink",
"hardsigmoid": "hardsigmoid",
"hardswish": "hardswish",
"hardtanh": "hardtanh",
"logsigmoid": "logsigmoid",
"logsoftmax": "logsoftmax",
"mish": "mish",
"multiheadattention": "multiheadattention",
"prelu": "prelu",
"rrelu": "rrelu",
"relu6": "relu6",
@ -274,9 +269,9 @@
"Focal point edges weight": "Peso de ponto focal para bordas",
"Create debug image": "Criar imagem de depuração",
"Preprocess": "Pré-processar",
"Train an embedding; must specify a directory with a set of 1:1 ratio images": "Treinar um embedding; precisa especificar um diretório com imagens de proporção 1:1",
"Train an embedding; must specify a directory with a set of 1:1 ratio images": "Treinar uma incorporação; precisa especificar um diretório com imagens de proporção 1:1",
"[wiki]": "[wiki]",
"Embedding": "Embedding",
"Embedding": "Incorporação",
"Embedding Learning rate": "Taxa de aprendizagem da incorporação",
"Hypernetwork Learning rate": "Taxa de aprendizagem de Hypernetwork",
"Dataset directory": "Diretório de Dataset",
@ -345,9 +340,11 @@
"Filename join string": "Nome de arquivo join string",
"Number of repeats for a single input image per epoch; used only for displaying epoch number": "Número de repetições para entrada única de imagens por época; serve apenas para mostrar o número de época",
"Save an csv containing the loss to log directory every N steps, 0 to disable": "Salvar um csv com as perdas para o diretório de log a cada N steps, 0 para desativar",
"Use cross attention optimizations while training": "Usar otimizações de atenção cruzada enquanto treinando",
"Stable Diffusion": "Stable Diffusion",
"Checkpoints to cache in RAM": "Checkpoints para manter no cache da RAM",
"Hypernetwork strength": "Força da Hypernetwork",
"Inpainting conditioning mask strength": "Força do inpaint para máscaras condicioniais",
"Apply color correction to img2img results to match original colors.": "Aplicar correção de cor nas imagens geradas em img2img, usando a imagem original como base.",
"Save a copy of image before applying color correction to img2img results": "Salvar uma cópia das imagens geradas em img2img antes de aplicar a correção de cor",
"With img2img, do exactly the amount of steps the slider specifies (normally you'd do less with less denoising).": "Durante gerações img2img, fazer examente o número de steps definidos na barra (normalmente você faz menos steps com denoising menor).",
@ -379,6 +376,7 @@
"Add model hash to generation information": "Adicionar hash do modelo para informação de geração",
"Add model name to generation information": "Adicionar nome do modelo para informação de geração",
"When reading generation parameters from text into UI (from PNG info or pasted text), do not change the selected model/checkpoint.": "Quando ler parâmetros de texto para a interface (de informações de PNG ou texto copiado), não alterar o modelo/intervalo selecionado.",
"Send seed when sending prompt or image to other interface": "Enviar seed quando enviar prompt ou imagem para outra interface",
"Font for image grids that have text": "Fonte para grade de imagens que têm texto",
"Enable full page image viewer": "Ativar visualizador de página inteira",
"Show images zoomed in by default in full page image viewer": "Mostrar imagens com zoom por definição no visualizador de página inteira",
@ -386,13 +384,17 @@
"Quicksettings list": "Lista de configurações rapidas",
"Localization (requires restart)": "Localização (precisa reiniciar)",
"ar_AR": "ar_AR",
"de_DE": "de_DE",
"es_ES": "es_ES",
"fr-FR": "fr-FR",
"fr_FR": "fr_FR",
"it_IT": "it_IT",
"ja_JP": "ja_JP",
"ko_KR": "ko_KR",
"pt_BR": "pt_BR",
"ru_RU": "ru_RU",
"tr_TR": "tr_TR",
"zh_CN": "zh_CN",
"zh_TW": "zh_TW",
"Sampler parameters": "Parâmetros de Amostragem",
"Hide samplers in user interface (requires restart)": "Esconder amostragens na interface de usuário (precisa reiniciar)",
"eta (noise multiplier) for DDIM": "tempo estimado (multiplicador de ruído) para DDIM",
@ -408,6 +410,19 @@
"Download localization template": "Baixar arquivo modelo de localização",
"Reload custom script bodies (No ui updates, No restart)": "Recarregar scripts personalizados (Sem atualizar a interface, Sem reiniciar)",
"Restart Gradio and Refresh components (Custom Scripts, ui.py, js and css only)": "Reiniciar Gradio e atualizar componentes (Scripts personalizados, ui.py, js e css)",
"Installed": "Instalado",
"Available": "Disponível",
"Install from URL": "Instalado de URL",
"Apply and restart UI": "Apicar e reiniciar a interface",
"Check for updates": "Procurar por atualizações",
"Extension": "Extensão",
"URL": "URL",
"Update": "Atualização",
"Load from:": "Carregar de:",
"Extension index URL": "Índice de extensão URL",
"URL for extension's git repository": "URL para repositório git da extensão",
"Local directory name": "Nome do diretório local",
"Install": "Instalar",
"Prompt (press Ctrl+Enter or Alt+Enter to generate)": "Prompt (apertar Ctrl+Enter ou Alt+Enter para gerar)",
"Negative prompt (press Ctrl+Enter or Alt+Enter to generate)": "Prompt Negativo (apertar Ctrl+Enter ou Alt+Enter para gerar)",
"Add a random artist to the prompt.": "Adicionar um artista aleatório para o prompt.",
@ -420,7 +435,7 @@
"Do not do anything special": "Não faça nada de especial",
"Which algorithm to use to produce the image": "O tipo de algoritmo para gerar imagens.",
"Euler Ancestral - very creative, each can get a completely different picture depending on step count, setting steps to higher than 30-40 does not help": "Euler Ancestral - cria mais variações para as imagens em diferentes passos. Mais que 40 passos cancela o efeito.",
"Denoising Diffusion Implicit Models - Funciona melhor para inpainting.": "Denoising Diffusion Implicit Models - Funciona melhor para inpainting.",
"Denoising Diffusion Implicit Models - best at inpainting": "Denoising Diffusion Implicit Models - Funciona melhor para inpainting.",
"Produce an image that can be tiled.": "Produz uma imagem que pode ser ladrilhada.",
"Use a two step process to partially create an image at smaller resolution, upscale, and then improve details in it without changing composition": "Cria um processo em duas etapas, com uma imagem em baixa qualidade primeiro, aumenta a imagem e refina os detalhes sem alterar a composição da imagem",
"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.": "Quanto o algoritmo deve manter da imagem original. Em 0, nada muda. Em 1 o algoritmo ignora a imagem original. Valores menores que 1.0 demoram mais.",
@ -438,7 +453,7 @@
"Write image to a directory (default - log/images) and generation parameters into csv file.": "Salva a imagem no diretório padrão ou escolhido e cria um arquivo csv com os parâmetros da geração.",
"Open images output directory": "Abre o diretório de saída de imagens.",
"How much to blur the mask before processing, in pixels.": "Transição do contorno da máscara, em pixels.",
"What to put inside the masked area before processing it with Stable Diffusion.": "O que vai dentro da máscara antes de processar.",
"What to put inside the masked area before processing it with Stable Diffusion.": "O que vai dentro da máscara antes de processá-la com Stable Diffusion.",
"fill it with colors of the image": "Preenche usando as cores da imagem.",
"keep whatever was there originally": "manter usando o que estava lá originalmente",
"fill it with latent space noise": "Preenche com ruídos do espaço latente.",
@ -463,6 +478,8 @@
"Restore low quality faces using GFPGAN neural network": "Restaurar rostos de baixa qualidade usando a rede neural GFPGAN",
"This regular expression will be used extract words from filename, and they will be joined using the option below into label text used for training. Leave empty to keep filename text as it is.": "Esta expressão regular vai retirar palavras do nome do arquivo e serão juntadas via regex usando a opção abaixo em etiquetas usadas em treinamento. Não mexer para manter os nomes como estão.",
"This string will be used to join split words into a single line if the option above is enabled.": "Esta string será usada para unir palavras divididas em uma única linha se a opção acima estiver habilitada.",
"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.": "Aplicável somente para modelos de inpaint. Determina quanto deve mascarar da imagem original para inpaint e img2img. 1.0 significa totalmente mascarado, que é o comportamento padrão. 0.0 significa uma condição totalmente não mascarada. Valores baixos ajudam a preservar a composição geral da imagem, mas vai encontrar dificuldades com grandes mudanças.",
"List of setting names, separated by commas, for settings that should go to the quick access bar at the top, rather than the usual setting tab. See modules/shared.py for setting names. Requires restarting to apply.": "Lista de nomes de configurações, separados por vírgulas, para configurações que devem ir para a barra de acesso rápido na parte superior, em vez da guia de configuração usual. Veja modules/shared.py para nomes de configuração. Necessita reinicialização para aplicar.",
"If this values is non-zero, it will be added to seed and used to initialize RNG for noises when using samplers with Eta. You can use this to produce even more variation of images, or you can use this to match images of other software if you know what you are doing.": "Se este valor for diferente de zero, ele será adicionado à seed e usado para inicializar o RNG para ruídos ao usar amostragens com Tempo Estimado. Você pode usar isso para produzir ainda mais variações de imagens ou pode usar isso para combinar imagens de outro software se souber o que está fazendo."
"Leave empty for auto": "Deixar desmarcado para automático"
}

16
modules/api/api.py
View File

@ -1,6 +1,8 @@
import base64
import io
import time
import uvicorn
from gradio.processing_utils import encode_pil_to_base64, decode_base64_to_file, decode_base64_to_image
from gradio.processing_utils import decode_base64_to_file, decode_base64_to_image
from fastapi import APIRouter, Depends, HTTPException
import modules.shared as shared
from modules.api.models import *
@ -28,6 +30,12 @@ def setUpscalers(req: dict):
return reqDict
def encode_pil_to_base64(image):
buffer = io.BytesIO()
image.save(buffer, format="png")
return base64.b64encode(buffer.getvalue())
class Api:
def __init__(self, app, queue_lock):
self.router = APIRouter()
@ -39,6 +47,7 @@ class Api:
self.app.add_api_route("/sdapi/v1/extra-batch-images", self.extras_batch_images_api, methods=["POST"], response_model=ExtrasBatchImagesResponse)
self.app.add_api_route("/sdapi/v1/png-info", self.pnginfoapi, methods=["POST"], response_model=PNGInfoResponse)
self.app.add_api_route("/sdapi/v1/progress", self.progressapi, methods=["GET"], response_model=ProgressResponse)
self.app.add_api_route("/sdapi/v1/interrupt", self.interruptapi, methods=["POST"])
def text2imgapi(self, txt2imgreq: StableDiffusionTxt2ImgProcessingAPI):
sampler_index = sampler_to_index(txt2imgreq.sampler_index)
@ -185,6 +194,11 @@ class Api:
return ProgressResponse(progress=progress, eta_relative=eta_relative, state=shared.state.dict(), current_image=current_image)
def interruptapi(self):
shared.state.interrupt()
return {}
def launch(self, server_name, port):
self.app.include_router(self.router)
uvicorn.run(self.app, host=server_name, port=port)

83
modules/extensions.py Normal file
View File

@ -0,0 +1,83 @@
import os
import sys
import traceback
import git
from modules import paths, shared
extensions = []
extensions_dir = os.path.join(paths.script_path, "extensions")
def active():
return [x for x in extensions if x.enabled]
class Extension:
def __init__(self, name, path, enabled=True):
self.name = name
self.path = path
self.enabled = enabled
self.status = ''
self.can_update = False
repo = None
try:
if os.path.exists(os.path.join(path, ".git")):
repo = git.Repo(path)
except Exception:
print(f"Error reading github repository info from {path}:", file=sys.stderr)
print(traceback.format_exc(), file=sys.stderr)
if repo is None or repo.bare:
self.remote = None
else:
self.remote = next(repo.remote().urls, None)
self.status = 'unknown'
def list_files(self, subdir, extension):
from modules import scripts
dirpath = os.path.join(self.path, subdir)
if not os.path.isdir(dirpath):
return []
res = []
for filename in sorted(os.listdir(dirpath)):
res.append(scripts.ScriptFile(self.path, filename, os.path.join(dirpath, filename)))
res = [x for x in res if os.path.splitext(x.path)[1].lower() == extension and os.path.isfile(x.path)]
return res
def check_updates(self):
repo = git.Repo(self.path)
for fetch in repo.remote().fetch("--dry-run"):
if fetch.flags != fetch.HEAD_UPTODATE:
self.can_update = True
self.status = "behind"
return
self.can_update = False
self.status = "latest"
def pull(self):
repo = git.Repo(self.path)
repo.remotes.origin.pull()
def list_extensions():
extensions.clear()
if not os.path.isdir(extensions_dir):
return
for dirname in sorted(os.listdir(extensions_dir)):
path = os.path.join(extensions_dir, dirname)
if not os.path.isdir(path):
continue
extension = Extension(name=dirname, path=path, enabled=dirname not in shared.opts.disabled_extensions)
extensions.append(extension)

2
modules/extras.py
View File

@ -141,7 +141,7 @@ def run_extras(extras_mode, resize_mode, image, image_folder, input_dir, output_
upscaling_resize_w, upscaling_resize_h, upscaling_crop)
cache_key = LruCache.Key(image_hash=hash(np.array(image.getdata()).tobytes()),
info_hash=hash(info),
args_hash=hash(upscale_args))
args_hash=hash((upscale_args, upscale_first)))
cached_entry = cached_images.get(cache_key)
if cached_entry is None:
res = upscale(image, *upscale_args)

5
modules/generation_parameters_copypaste.py
View File

@ -17,6 +17,11 @@ paste_fields = {}
bind_list = []
def reset():
paste_fields.clear()
bind_list.clear()
def quote(text):
if ',' not in str(text):
return text

5
modules/images.py
View File

@ -510,8 +510,9 @@ def save_image(image, path, basename, seed=None, prompt=None, extension='png', i
if extension.lower() == '.png':
pnginfo_data = PngImagePlugin.PngInfo()
for k, v in params.pnginfo.items():
pnginfo_data.add_text(k, str(v))
if opts.enable_pnginfo:
for k, v in params.pnginfo.items():
pnginfo_data.add_text(k, str(v))
image.save(fullfn, quality=opts.jpeg_quality, pnginfo=pnginfo_data)

1
modules/img2img.py
View File

@ -55,6 +55,7 @@ def process_batch(p, input_dir, output_dir, args):
filename = f"{left}-{n}{right}"
if not save_normally:
os.makedirs(output_dir, exist_ok=True)
processed_image.save(os.path.join(output_dir, filename))

4
modules/interrogate.py
View File

@ -56,9 +56,9 @@ class InterrogateModels:
import clip
if self.running_on_cpu:
model, preprocess = clip.load(clip_model_name, device="cpu")
model, preprocess = clip.load(clip_model_name, device="cpu", download_root=shared.cmd_opts.clip_models_path)
else:
model, preprocess = clip.load(clip_model_name)
model, preprocess = clip.load(clip_model_name, download_root=shared.cmd_opts.clip_models_path)
model.eval()
model = model.to(devices.device_interrogate)

21
modules/lowvram.py
View File

@ -38,13 +38,18 @@ def setup_for_low_vram(sd_model, use_medvram):
# see below for register_forward_pre_hook;
# first_stage_model does not use forward(), it uses encode/decode, so register_forward_pre_hook is
# useless here, and we just replace those methods
def first_stage_model_encode_wrap(self, encoder, x):
send_me_to_gpu(self, None)
return encoder(x)
def first_stage_model_decode_wrap(self, decoder, z):
send_me_to_gpu(self, None)
return decoder(z)
first_stage_model = sd_model.first_stage_model
first_stage_model_encode = sd_model.first_stage_model.encode
first_stage_model_decode = sd_model.first_stage_model.decode
def first_stage_model_encode_wrap(x):
send_me_to_gpu(first_stage_model, None)
return first_stage_model_encode(x)
def first_stage_model_decode_wrap(z):
send_me_to_gpu(first_stage_model, None)
return first_stage_model_decode(z)
# remove three big modules, cond, first_stage, and unet from the model and then
# send the model to GPU. Then put modules back. the modules will be in CPU.
@ -56,8 +61,8 @@ def setup_for_low_vram(sd_model, use_medvram):
# register hooks for those the first two models
sd_model.cond_stage_model.transformer.register_forward_pre_hook(send_me_to_gpu)
sd_model.first_stage_model.register_forward_pre_hook(send_me_to_gpu)
sd_model.first_stage_model.encode = lambda x, en=sd_model.first_stage_model.encode: first_stage_model_encode_wrap(sd_model.first_stage_model, en, x)
sd_model.first_stage_model.decode = lambda z, de=sd_model.first_stage_model.decode: first_stage_model_decode_wrap(sd_model.first_stage_model, de, z)
sd_model.first_stage_model.encode = first_stage_model_encode_wrap
sd_model.first_stage_model.decode = first_stage_model_decode_wrap
parents[sd_model.cond_stage_model.transformer] = sd_model.cond_stage_model
if use_medvram:

3
modules/processing.py
View File

@ -597,6 +597,9 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
if p.scripts is not None:
p.scripts.postprocess(p, res)
p.sd_model = None
p.sampler = None
return res

2
modules/safe.py
View File

@ -32,7 +32,7 @@ class RestrictedUnpickler(pickle.Unpickler):
return getattr(collections, name)
if module == 'torch._utils' and name in ['_rebuild_tensor_v2', '_rebuild_parameter']:
return getattr(torch._utils, name)
if module == 'torch' and name in ['FloatStorage', 'HalfStorage', 'IntStorage', 'LongStorage', 'DoubleStorage']:
if module == 'torch' and name in ['FloatStorage', 'HalfStorage', 'IntStorage', 'LongStorage', 'DoubleStorage', 'ByteStorage']:
return getattr(torch, name)
if module == 'torch.nn.modules.container' and name in ['ParameterDict']:
return getattr(torch.nn.modules.container, name)

19
modules/script_callbacks.py
View File

@ -3,6 +3,8 @@ import traceback
from collections import namedtuple
import inspect
from fastapi import FastAPI
from gradio import Blocks
def report_exception(c, job):
print(f"Error executing callback {job} for {c.script}", file=sys.stderr)
@ -25,6 +27,7 @@ class ImageSaveParams:
ScriptCallback = namedtuple("ScriptCallback", ["script", "callback"])
callbacks_app_started = []
callbacks_model_loaded = []
callbacks_ui_tabs = []
callbacks_ui_settings = []
@ -40,6 +43,14 @@ def clear_callbacks():
callbacks_image_saved.clear()
def app_started_callback(demo: Blocks, app: FastAPI):
for c in callbacks_app_started:
try:
c.callback(demo, app)
except Exception:
report_exception(c, 'app_started_callback')
def model_loaded_callback(sd_model):
for c in callbacks_model_loaded:
try:
@ -69,7 +80,7 @@ def ui_settings_callback():
def before_image_saved_callback(params: ImageSaveParams):
for c in callbacks_image_saved:
for c in callbacks_before_image_saved:
try:
c.callback(params)
except Exception:
@ -91,6 +102,12 @@ def add_callback(callbacks, fun):
callbacks.append(ScriptCallback(filename, fun))
def on_app_started(callback):
"""register a function to be called when the webui started, the gradio `Block` component and
fastapi `FastAPI` object are passed as the arguments"""
add_callback(callbacks_app_started, callback)
def on_model_loaded(callback):
"""register a function to be called when the stable diffusion model is created; the model is
passed as an argument"""

21
modules/scripts.py
View File

@ -7,7 +7,7 @@ import modules.ui as ui
import gradio as gr
from modules.processing import StableDiffusionProcessing
from modules import shared, paths, script_callbacks
from modules import shared, paths, script_callbacks, extensions
AlwaysVisible = object()
@ -107,17 +107,8 @@ def list_scripts(scriptdirname, extension):
for filename in sorted(os.listdir(basedir)):
scripts_list.append(ScriptFile(paths.script_path, filename, os.path.join(basedir, filename)))
extdir = os.path.join(paths.script_path, "extensions")
if os.path.exists(extdir):
for dirname in sorted(os.listdir(extdir)):
dirpath = os.path.join(extdir, dirname)
scriptdirpath = os.path.join(dirpath, scriptdirname)
if not os.path.isdir(scriptdirpath):
continue
for filename in sorted(os.listdir(scriptdirpath)):
scripts_list.append(ScriptFile(dirpath, filename, os.path.join(scriptdirpath, filename)))
for ext in extensions.active():
scripts_list += ext.list_files(scriptdirname, extension)
scripts_list = [x for x in scripts_list if os.path.splitext(x.path)[1].lower() == extension and os.path.isfile(x.path)]
@ -127,11 +118,7 @@ def list_scripts(scriptdirname, extension):
def list_files_with_name(filename):
res = []
dirs = [paths.script_path]
extdir = os.path.join(paths.script_path, "extensions")
if os.path.exists(extdir):
dirs += [os.path.join(extdir, d) for d in sorted(os.listdir(extdir))]
dirs = [paths.script_path] + [ext.path for ext in extensions.active()]
for dirpath in dirs:
if not os.path.isdir(dirpath):

4
modules/sd_hijack.py
View File

@ -94,6 +94,10 @@ class StableDiffusionModelHijack:
if type(model_embeddings.token_embedding) == EmbeddingsWithFixes:
model_embeddings.token_embedding = model_embeddings.token_embedding.wrapped
self.layers = None
self.circular_enabled = False
self.clip = None
def apply_circular(self, enable):
if self.circular_enabled == enable:
return

14
modules/sd_models.py
View File

@ -1,6 +1,7 @@
import collections
import os.path
import sys
import gc
from collections import namedtuple
import torch
import re
@ -220,6 +221,12 @@ def load_model(checkpoint_info=None):
if checkpoint_info.config != shared.cmd_opts.config:
print(f"Loading config from: {checkpoint_info.config}")
if shared.sd_model:
sd_hijack.model_hijack.undo_hijack(shared.sd_model)
shared.sd_model = None
gc.collect()
devices.torch_gc()
sd_config = OmegaConf.load(checkpoint_info.config)
if should_hijack_inpainting(checkpoint_info):
@ -233,6 +240,7 @@ def load_model(checkpoint_info=None):
checkpoint_info = checkpoint_info._replace(config=checkpoint_info.config.replace(".yaml", "-inpainting.yaml"))
do_inpainting_hijack()
sd_model = instantiate_from_config(sd_config.model)
load_model_weights(sd_model, checkpoint_info)
@ -252,14 +260,18 @@ def load_model(checkpoint_info=None):
return sd_model
def reload_model_weights(sd_model, info=None):
def reload_model_weights(sd_model=None, info=None):
from modules import lowvram, devices, sd_hijack
checkpoint_info = info or select_checkpoint()
if not sd_model:
sd_model = shared.sd_model
if sd_model.sd_model_checkpoint == checkpoint_info.filename:
return
if sd_model.sd_checkpoint_info.config != checkpoint_info.config or should_hijack_inpainting(checkpoint_info) != should_hijack_inpainting(sd_model.sd_checkpoint_info):
del sd_model
checkpoints_loaded.clear()
load_model(checkpoint_info)
return shared.sd_model

28
modules/sd_samplers.py
View File

@ -1,5 +1,6 @@
from collections import namedtuple
import numpy as np
from math import floor
import torch
import tqdm
from PIL import Image
@ -205,17 +206,22 @@ class VanillaStableDiffusionSampler:
self.mask = p.mask if hasattr(p, 'mask') else None
self.nmask = p.nmask if hasattr(p, 'nmask') else None
def adjust_steps_if_invalid(self, p, num_steps):
if (self.config.name == 'DDIM' and p.ddim_discretize == 'uniform') or (self.config.name == 'PLMS'):
valid_step = 999 / (1000 // num_steps)
if valid_step == floor(valid_step):
return int(valid_step) + 1
return num_steps
def sample_img2img(self, p, x, noise, conditioning, unconditional_conditioning, steps=None, image_conditioning=None):
steps, t_enc = setup_img2img_steps(p, steps)
steps = self.adjust_steps_if_invalid(p, steps)
self.initialize(p)
# existing code fails with certain step counts, like 9
try:
self.sampler.make_schedule(ddim_num_steps=steps, ddim_eta=self.eta, ddim_discretize=p.ddim_discretize, verbose=False)
except Exception:
self.sampler.make_schedule(ddim_num_steps=steps+1, ddim_eta=self.eta, ddim_discretize=p.ddim_discretize, verbose=False)
self.sampler.make_schedule(ddim_num_steps=steps, ddim_eta=self.eta, ddim_discretize=p.ddim_discretize, verbose=False)
x1 = self.sampler.stochastic_encode(x, torch.tensor([t_enc] * int(x.shape[0])).to(shared.device), noise=noise)
self.init_latent = x
@ -239,18 +245,14 @@ class VanillaStableDiffusionSampler:
self.last_latent = x
self.step = 0
steps = steps or p.steps
steps = self.adjust_steps_if_invalid(p, steps or p.steps)
# Wrap the conditioning models with additional image conditioning for inpainting model
if image_conditioning is not None:
conditioning = {"c_concat": [image_conditioning], "c_crossattn": [conditioning]}
unconditional_conditioning = {"c_concat": [image_conditioning], "c_crossattn": [unconditional_conditioning]}
# existing code fails with certain step counts, like 9
try:
samples_ddim = self.launch_sampling(steps, lambda: self.sampler.sample(S=steps, conditioning=conditioning, batch_size=int(x.shape[0]), shape=x[0].shape, verbose=False, unconditional_guidance_scale=p.cfg_scale, unconditional_conditioning=unconditional_conditioning, x_T=x, eta=self.eta)[0])
except Exception:
samples_ddim = self.launch_sampling(steps, lambda: self.sampler.sample(S=steps+1, conditioning=conditioning, batch_size=int(x.shape[0]), shape=x[0].shape, verbose=False, unconditional_guidance_scale=p.cfg_scale, unconditional_conditioning=unconditional_conditioning, x_T=x, eta=self.eta)[0])
samples_ddim = self.launch_sampling(steps, lambda: self.sampler.sample(S=steps, conditioning=conditioning, batch_size=int(x.shape[0]), shape=x[0].shape, verbose=False, unconditional_guidance_scale=p.cfg_scale, unconditional_conditioning=unconditional_conditioning, x_T=x, eta=self.eta)[0])
return samples_ddim

18
modules/shared.py
View File

@ -41,7 +41,7 @@ parser.add_argument("--lowram", action='store_true', help="load stable diffusion
parser.add_argument("--always-batch-cond-uncond", action='store_true', help="disables cond/uncond batching that is enabled to save memory with --medvram or --lowvram")
parser.add_argument("--unload-gfpgan", action='store_true', help="does not do anything.")
parser.add_argument("--precision", type=str, help="evaluate at this precision", choices=["full", "autocast"], default="autocast")
parser.add_argument("--share", action='store_true', help="use share=True for gradio and make the UI accessible through their site (doesn't work for me but you might have better luck)")
parser.add_argument("--share", action='store_true', help="use share=True for gradio and make the UI accessible through their site")
parser.add_argument("--ngrok", type=str, help="ngrok authtoken, alternative to gradio --share", default=None)
parser.add_argument("--ngrok-region", type=str, help="The region in which ngrok should start.", default="us")
parser.add_argument("--codeformer-models-path", type=str, help="Path to directory with codeformer model file(s).", default=os.path.join(models_path, 'Codeformer'))
@ -52,6 +52,7 @@ parser.add_argument("--realesrgan-models-path", type=str, help="Path to director
parser.add_argument("--scunet-models-path", type=str, help="Path to directory with ScuNET model file(s).", default=os.path.join(models_path, 'ScuNET'))
parser.add_argument("--swinir-models-path", type=str, help="Path to directory with SwinIR model file(s).", default=os.path.join(models_path, 'SwinIR'))
parser.add_argument("--ldsr-models-path", type=str, help="Path to directory with LDSR model file(s).", default=os.path.join(models_path, 'LDSR'))
parser.add_argument("--clip-models-path", type=str, help="Path to directory with CLIP model file(s).", default=None)
parser.add_argument("--xformers", action='store_true', help="enable xformers for cross attention layers")
parser.add_argument("--force-enable-xformers", action='store_true', help="enable xformers for cross attention layers regardless of whether the checking code thinks you can run it; do not make bug reports if this fails to work")
parser.add_argument("--deepdanbooru", action='store_true', help="enable deepdanbooru interrogator")
@ -98,6 +99,8 @@ restricted_opts = {
"outdir_save",
}
cmd_opts.disable_extension_access = cmd_opts.share or cmd_opts.listen
devices.device, devices.device_interrogate, devices.device_gfpgan, devices.device_swinir, devices.device_esrgan, devices.device_scunet, devices.device_codeformer = \
(devices.cpu if any(y in cmd_opts.use_cpu for y in [x, 'all']) else devices.get_optimal_device() for x in ['sd', 'interrogate', 'gfpgan', 'swinir', 'esrgan', 'scunet', 'codeformer'])
@ -134,6 +137,7 @@ class State:
current_image_sampling_step = 0
textinfo = None
time_start = None
need_restart = False
def skip(self):
self.skipped = True
@ -288,11 +292,12 @@ options_templates.update(options_section(('system', "System"), {
}))
options_templates.update(options_section(('training', "Training"), {
"unload_models_when_training": OptionInfo(False, "Move VAE and CLIP to RAM when training hypernetwork. Saves VRAM."),
"unload_models_when_training": OptionInfo(False, "Move VAE and CLIP to RAM when training if possible. Saves VRAM."),
"dataset_filename_word_regex": OptionInfo("", "Filename word regex"),
"dataset_filename_join_string": OptionInfo(" ", "Filename join string"),
"training_image_repeats_per_epoch": OptionInfo(1, "Number of repeats for a single input image per epoch; used only for displaying epoch number", gr.Number, {"precision": 0}),
"training_write_csv_every": OptionInfo(500, "Save an csv containing the loss to log directory every N steps, 0 to disable"),
"training_xattention_optimizations": OptionInfo(False, "Use cross attention optimizations while training"),
}))
options_templates.update(options_section(('sd', "Stable Diffusion"), {
@ -357,6 +362,12 @@ options_templates.update(options_section(('sampler-params', "Sampler parameters"
'eta_noise_seed_delta': OptionInfo(0, "Eta noise seed delta", gr.Number, {"precision": 0}),
}))
options_templates.update(options_section((None, "Hidden options"), {
"disabled_extensions": OptionInfo([], "Disable those extensions"),
}))
options_templates.update()
class Options:
data = None
@ -368,8 +379,9 @@ class Options:
def __setattr__(self, key, value):
if self.data is not None:
if key in self.data:
if key in self.data or key in self.data_labels:
self.data[key] = value
return
return super(Options, self).__setattr__(key, value)

10
modules/textual_inversion/textual_inversion.py
View File

@ -235,6 +235,7 @@ def train_embedding(embedding_name, learn_rate, batch_size, data_root, log_direc
filename = os.path.join(shared.cmd_opts.embeddings_dir, f'{embedding_name}.pt')
log_directory = os.path.join(log_directory, datetime.datetime.now().strftime("%Y-%m-%d"), embedding_name)
unload = shared.opts.unload_models_when_training
if save_embedding_every > 0:
embedding_dir = os.path.join(log_directory, "embeddings")
@ -272,6 +273,8 @@ def train_embedding(embedding_name, learn_rate, batch_size, data_root, log_direc
shared.state.textinfo = f"Preparing dataset from {html.escape(data_root)}..."
with torch.autocast("cuda"):
ds = modules.textual_inversion.dataset.PersonalizedBase(data_root=data_root, width=training_width, height=training_height, repeats=shared.opts.training_image_repeats_per_epoch, placeholder_token=embedding_name, model=shared.sd_model, device=devices.device, template_file=template_file, batch_size=batch_size)
if unload:
shared.sd_model.first_stage_model.to(devices.cpu)
embedding.vec.requires_grad = True
optimizer = torch.optim.AdamW([embedding.vec], lr=scheduler.learn_rate)
@ -328,6 +331,9 @@ def train_embedding(embedding_name, learn_rate, batch_size, data_root, log_direc
if images_dir is not None and steps_done % create_image_every == 0:
forced_filename = f'{embedding_name}-{steps_done}'
last_saved_image = os.path.join(images_dir, forced_filename)
shared.sd_model.first_stage_model.to(devices.device)
p = processing.StableDiffusionProcessingTxt2Img(
sd_model=shared.sd_model,
do_not_save_grid=True,
@ -355,6 +361,9 @@ def train_embedding(embedding_name, learn_rate, batch_size, data_root, log_direc
processed = processing.process_images(p)
image = processed.images[0]
if unload:
shared.sd_model.first_stage_model.to(devices.cpu)
shared.state.current_image = image
if save_image_with_stored_embedding and os.path.exists(last_saved_file) and embedding_yet_to_be_embedded:
@ -400,6 +409,7 @@ Last saved image: {html.escape(last_saved_image)}<br/>
filename = os.path.join(shared.cmd_opts.embeddings_dir, f'{embedding_name}.pt')
save_embedding(embedding, checkpoint, embedding_name, filename, remove_cached_checksum=True)
shared.sd_model.first_stage_model.to(devices.device)
return embedding, filename

7
modules/textual_inversion/ui.py
View File

@ -25,8 +25,10 @@ def train_embedding(*args):
assert not shared.cmd_opts.lowvram, 'Training models with lowvram not possible'
apply_optimizations = shared.opts.training_xattention_optimizations
try:
sd_hijack.undo_optimizations()
if not apply_optimizations:
sd_hijack.undo_optimizations()
embedding, filename = modules.textual_inversion.textual_inversion.train_embedding(*args)
@ -38,5 +40,6 @@ Embedding saved to {html.escape(filename)}
except Exception:
raise
finally:
sd_hijack.apply_optimizations()
if not apply_optimizations:
sd_hijack.apply_optimizations()

16
modules/ui.py
View File

@ -19,7 +19,7 @@ import numpy as np
from PIL import Image, PngImagePlugin
from modules import sd_hijack, sd_models, localization, script_callbacks
from modules import sd_hijack, sd_models, localization, script_callbacks, ui_extensions
from modules.paths import script_path
from modules.shared import opts, cmd_opts, restricted_opts
@ -671,6 +671,7 @@ def create_ui(wrap_gradio_gpu_call):
import modules.img2img
import modules.txt2img
parameters_copypaste.reset()
with gr.Blocks(analytics_enabled=False) as txt2img_interface:
txt2img_prompt, roll, txt2img_prompt_style, txt2img_negative_prompt, txt2img_prompt_style2, submit, _, _, txt2img_prompt_style_apply, txt2img_save_style, txt2img_paste, token_counter, token_button = create_toprow(is_img2img=False)
@ -1511,8 +1512,9 @@ def create_ui(wrap_gradio_gpu_call):
column = None
with gr.Row(elem_id="settings").style(equal_height=False):
for i, (k, item) in enumerate(opts.data_labels.items()):
section_must_be_skipped = item.section[0] is None
if previous_section != item.section:
if previous_section != item.section and not section_must_be_skipped:
if cols_displayed < settings_cols and (items_displayed >= items_per_col or previous_section is None):
if column is not None:
column.__exit__()
@ -1531,6 +1533,8 @@ def create_ui(wrap_gradio_gpu_call):
if k in quicksettings_names and not shared.cmd_opts.freeze_settings:
quicksettings_list.append((i, k, item))
components.append(dummy_component)
elif section_must_be_skipped:
components.append(dummy_component)
else:
component = create_setting_component(k)
component_dict[k] = component
@ -1572,9 +1576,10 @@ def create_ui(wrap_gradio_gpu_call):
def request_restart():
shared.state.interrupt()
settings_interface.gradio_ref.do_restart = True
shared.state.need_restart = True
restart_gradio.click(
fn=request_restart,
inputs=[],
outputs=[],
@ -1612,14 +1617,15 @@ def create_ui(wrap_gradio_gpu_call):
interfaces += script_callbacks.ui_tabs_callback()
interfaces += [(settings_interface, "Settings", "settings")]
extensions_interface = ui_extensions.create_ui()
interfaces += [(extensions_interface, "Extensions", "extensions")]
with gr.Blocks(css=css, analytics_enabled=False, title="Stable Diffusion") as demo:
with gr.Row(elem_id="quicksettings"):
for i, k, item in quicksettings_list:
component = create_setting_component(k, is_quicksettings=True)
component_dict[k] = component
settings_interface.gradio_ref = demo
parameters_copypaste.integrate_settings_paste_fields(component_dict)
parameters_copypaste.run_bind()

268
modules/ui_extensions.py Normal file
View File

@ -0,0 +1,268 @@
import json
import os.path
import shutil
import sys
import time
import traceback
import git
import gradio as gr
import html
from modules import extensions, shared, paths
available_extensions = {"extensions": []}
def check_access():
assert not shared.cmd_opts.disable_extension_access, "extension access disabed because of commandline flags"
def apply_and_restart(disable_list, update_list):
check_access()
disabled = json.loads(disable_list)
assert type(disabled) == list, f"wrong disable_list data for apply_and_restart: {disable_list}"
update = json.loads(update_list)
assert type(update) == list, f"wrong update_list data for apply_and_restart: {update_list}"
update = set(update)
for ext in extensions.extensions:
if ext.name not in update:
continue
try:
ext.pull()
except Exception:
print(f"Error pulling updates for {ext.name}:", file=sys.stderr)
print(traceback.format_exc(), file=sys.stderr)
shared.opts.disabled_extensions = disabled
shared.opts.save(shared.config_filename)
shared.state.interrupt()
shared.state.need_restart = True
def check_updates():
check_access()
for ext in extensions.extensions:
if ext.remote is None:
continue
try:
ext.check_updates()
except Exception:
print(f"Error checking updates for {ext.name}:", file=sys.stderr)
print(traceback.format_exc(), file=sys.stderr)
return extension_table()
def extension_table():
code = f"""<!-- {time.time()} -->
<table id="extensions">
<thead>
<tr>
<th><abbr title="Use checkbox to enable the extension; it will be enabled or disabled when you click apply button">Extension</abbr></th>
<th>URL</th>
<th><abbr title="Use checkbox to mark the extension for update; it will be updated when you click apply button">Update</abbr></th>
</tr>
</thead>
<tbody>
"""
for ext in extensions.extensions:
if ext.can_update:
ext_status = f"""<label><input class="gr-check-radio gr-checkbox" name="update_{html.escape(ext.name)}" checked="checked" type="checkbox">{html.escape(ext.status)}</label>"""
else:
ext_status = ext.status
code += f"""
<tr>
<td><label><input class="gr-check-radio gr-checkbox" name="enable_{html.escape(ext.name)}" type="checkbox" {'checked="checked"' if ext.enabled else ''}>{html.escape(ext.name)}</label></td>
<td><a href="{html.escape(ext.remote or '')}">{html.escape(ext.remote or '')}</a></td>
<td{' class="extension_status"' if ext.remote is not None else ''}>{ext_status}</td>
</tr>
"""
code += """
</tbody>
</table>
"""
return code
def normalize_git_url(url):
if url is None:
return ""
url = url.replace(".git", "")
return url
def install_extension_from_url(dirname, url):
check_access()
assert url, 'No URL specified'
if dirname is None or dirname == "":
*parts, last_part = url.split('/')
last_part = normalize_git_url(last_part)
dirname = last_part
target_dir = os.path.join(extensions.extensions_dir, dirname)
assert not os.path.exists(target_dir), f'Extension directory already exists: {target_dir}'
normalized_url = normalize_git_url(url)
assert len([x for x in extensions.extensions if normalize_git_url(x.remote) == normalized_url]) == 0, 'Extension with this URL is already installed'
tmpdir = os.path.join(paths.script_path, "tmp", dirname)
try:
shutil.rmtree(tmpdir, True)
repo = git.Repo.clone_from(url, tmpdir)
repo.remote().fetch()
os.rename(tmpdir, target_dir)
extensions.list_extensions()
return [extension_table(), html.escape(f"Installed into {target_dir}. Use Installed tab to restart.")]
finally:
shutil.rmtree(tmpdir, True)
def install_extension_from_index(url):
ext_table, message = install_extension_from_url(None, url)
return refresh_available_extensions_from_data(), ext_table, message
def refresh_available_extensions(url):
global available_extensions
import urllib.request
with urllib.request.urlopen(url) as response:
text = response.read()
available_extensions = json.loads(text)
return url, refresh_available_extensions_from_data(), ''
def refresh_available_extensions_from_data():
extlist = available_extensions["extensions"]
installed_extension_urls = {normalize_git_url(extension.remote): extension.name for extension in extensions.extensions}
code = f"""<!-- {time.time()} -->
<table id="available_extensions">
<thead>
<tr>
<th>Extension</th>
<th>Description</th>
<th>Action</th>
</tr>
</thead>
<tbody>
"""
for ext in extlist:
name = ext.get("name", "noname")
url = ext.get("url", None)
description = ext.get("description", "")
if url is None:
continue
existing = installed_extension_urls.get(normalize_git_url(url), None)
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">"""
code += f"""
<tr>
<td><a href="{html.escape(url)}">{html.escape(name)}</a></td>
<td>{html.escape(description)}</td>
<td>{install_code}</td>
</tr>
"""
code += """
</tbody>
</table>
"""
return code
def create_ui():
import modules.ui
with gr.Blocks(analytics_enabled=False) as ui:
with gr.Tabs(elem_id="tabs_extensions") as tabs:
with gr.TabItem("Installed"):
with gr.Row():
apply = gr.Button(value="Apply and restart UI", variant="primary")
check = gr.Button(value="Check for updates")
extensions_disabled_list = gr.Text(elem_id="extensions_disabled_list", visible=False).style(container=False)
extensions_update_list = gr.Text(elem_id="extensions_update_list", visible=False).style(container=False)
extensions_table = gr.HTML(lambda: extension_table())
apply.click(
fn=apply_and_restart,
_js="extensions_apply",
inputs=[extensions_disabled_list, extensions_update_list],
outputs=[],
)
check.click(
fn=check_updates,
_js="extensions_check",
inputs=[],
outputs=[extensions_table],
)
with gr.TabItem("Available"):
with gr.Row():
refresh_available_extensions_button = gr.Button(value="Load from:", variant="primary")
available_extensions_index = gr.Text(value="https://raw.githubusercontent.com/wiki/AUTOMATIC1111/stable-diffusion-webui/Extensions-index.md", label="Extension index URL").style(container=False)
extension_to_install = gr.Text(elem_id="extension_to_install", visible=False)
install_extension_button = gr.Button(elem_id="install_extension_button", visible=False)
install_result = gr.HTML()
available_extensions_table = gr.HTML()
refresh_available_extensions_button.click(
fn=modules.ui.wrap_gradio_call(refresh_available_extensions, extra_outputs=[gr.update(), gr.update()]),
inputs=[available_extensions_index],
outputs=[available_extensions_index, available_extensions_table, install_result],
)
install_extension_button.click(
fn=modules.ui.wrap_gradio_call(install_extension_from_index, extra_outputs=[gr.update(), gr.update()]),
inputs=[extension_to_install],
outputs=[available_extensions_table, extensions_table, install_result],
)
with gr.TabItem("Install from URL"):
install_url = gr.Text(label="URL for extension's git repository")
install_dirname = gr.Text(label="Local directory name", placeholder="Leave empty for auto")
install_button = gr.Button(value="Install", variant="primary")
install_result = gr.HTML(elem_id="extension_install_result")
install_button.click(
fn=modules.ui.wrap_gradio_call(install_extension_from_url, extra_outputs=[gr.update()]),
inputs=[install_dirname, install_url],
outputs=[extensions_table, install_result],
)
return ui

3
requirements.txt
View File

@ -12,7 +12,7 @@ opencv-python
requests
piexif
Pillow
pytorch_lightning
pytorch_lightning==1.7.7
realesrgan
scikit-image>=0.19
timm==0.4.12
@ -26,3 +26,4 @@ torchdiffeq
kornia
lark
inflection
GitPython

1
requirements_versions.txt
View File

@ -23,3 +23,4 @@ torchdiffeq==0.2.3
kornia==0.6.7
lark==1.1.2
inflection==0.5.1
GitPython==3.1.27

9
scripts/prompts_from_file.py
View File

@ -96,6 +96,7 @@ class Script(scripts.Script):
def ui(self, is_img2img):
checkbox_iterate = gr.Checkbox(label="Iterate seed every line", value=False)
checkbox_iterate_batch = gr.Checkbox(label="Use same random seed for all lines", value=False)
prompt_txt = gr.Textbox(label="List of prompt inputs", lines=1)
file = gr.File(label="Upload prompt inputs", type='bytes')
@ -106,9 +107,9 @@ class Script(scripts.Script):
# We don't shrink back to 1, because that causes the control to ignore [enter], and it may
# be unclear to the user that shift-enter is needed.
prompt_txt.change(lambda tb: gr.update(lines=7) if ("\n" in tb) else gr.update(lines=2), inputs=[prompt_txt], outputs=[prompt_txt])
return [checkbox_iterate, file, prompt_txt]
return [checkbox_iterate, checkbox_iterate_batch, file, prompt_txt]
def run(self, p, checkbox_iterate, file, prompt_txt: str):
def run(self, p, checkbox_iterate, checkbox_iterate_batch, file, prompt_txt: str):
lines = [x.strip() for x in prompt_txt.splitlines()]
lines = [x for x in lines if len(x) > 0]
@ -137,7 +138,7 @@ class Script(scripts.Script):
jobs.append(args)
print(f"Will process {len(lines)} lines in {job_count} jobs.")
if (checkbox_iterate and p.seed == -1):
if (checkbox_iterate or checkbox_iterate_batch) and p.seed == -1:
p.seed = int(random.randrange(4294967294))
state.job_count = job_count
@ -153,7 +154,7 @@ class Script(scripts.Script):
proc = process_images(copy_p)
images += proc.images
if (checkbox_iterate):
if checkbox_iterate:
p.seed = p.seed + (p.batch_size * p.n_iter)

25
style.css
View File

@ -530,6 +530,29 @@ img2maskimg, #img2maskimg > .h-60, #img2maskimg > .h-60 > div, #img2maskimg > .h
min-height: 480px !important;
}
/* Extensions */
#tab_extensions table{
border-collapse: collapse;
}
#tab_extensions table td, #tab_extensions table th{
border: 1px solid #ccc;
padding: 0.25em 0.5em;
}
#tab_extensions table input[type="checkbox"]{
margin-right: 0.5em;
}
#tab_extensions button{
max-width: 16em;
}
#tab_extensions input[disabled="disabled"]{
opacity: 0.5;
}
/* The following handles localization for right-to-left (RTL) languages like Arabic.
The rtl media type will only be activated by the logic in javascript/localization.js.
If you change anything above, you need to make sure it is RTL compliant by just running
@ -607,4 +630,4 @@ Then, you will need to add the RTL counterpart only if needed in the rtl section
right: unset;
left: 0.5em;
}
}
}

22
webui.py
View File

@ -9,7 +9,7 @@ from fastapi.middleware.gzip import GZipMiddleware
from modules.paths import script_path
from modules import devices, sd_samplers, upscaler
from modules import devices, sd_samplers, upscaler, extensions
import modules.codeformer_model as codeformer
import modules.extras
import modules.face_restoration
@ -23,6 +23,7 @@ import modules.sd_hijack
import modules.sd_models
import modules.shared as shared
import modules.txt2img
import modules.script_callbacks
import modules.ui
from modules import devices
@ -60,6 +61,8 @@ def wrap_gradio_gpu_call(func, extra_outputs=None):
def initialize():
extensions.list_extensions()
if cmd_opts.ui_debug_mode:
shared.sd_upscalers = upscaler.UpscalerLanczos().scalers
modules.scripts.load_scripts()
@ -75,7 +78,7 @@ def initialize():
modules.scripts.load_scripts()
modules.sd_models.load_model()
shared.opts.onchange("sd_model_checkpoint", wrap_queued_call(lambda: modules.sd_models.reload_model_weights(shared.sd_model)))
shared.opts.onchange("sd_model_checkpoint", wrap_queued_call(lambda: modules.sd_models.reload_model_weights()))
shared.opts.onchange("sd_hypernetwork", wrap_queued_call(lambda: modules.hypernetworks.hypernetwork.load_hypernetwork(shared.opts.sd_hypernetwork)))
shared.opts.onchange("sd_hypernetwork_strength", modules.hypernetworks.hypernetwork.apply_strength)
@ -92,15 +95,18 @@ def create_api(app):
api = Api(app, queue_lock)
return api
def wait_on_server(demo=None):
while 1:
time.sleep(0.5)
if demo and getattr(demo, 'do_restart', False):
if shared.state.need_restart:
shared.state.need_restart = False
time.sleep(0.5)
demo.close()
time.sleep(0.5)
break
def api_only():
initialize()
@ -132,14 +138,18 @@ def webui():
app.add_middleware(GZipMiddleware, minimum_size=1000)
if (launch_api):
if launch_api:
create_api(app)
modules.script_callbacks.app_started_callback(demo, app)
wait_on_server(demo)
sd_samplers.set_samplers()
print('Reloading Custom Scripts')
print('Reloading extensions')
extensions.list_extensions()
print('Reloading custom scripts')
modules.scripts.reload_scripts()
print('Reloading modules: modules.ui')
importlib.reload(modules.ui)
@ -148,8 +158,6 @@ def webui():
print('Restarting Gradio')
task = []
if __name__ == "__main__":
if cmd_opts.nowebui:
api_only()