mirror of
https://github.com/easydiffusion/easydiffusion.git
synced 2025-06-21 02:18:24 +02:00
merge beta
This commit is contained in:
commit
01dde9d23a
@ -25,6 +25,8 @@ modules_to_check = {
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"fastapi": "0.85.1",
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"fastapi": "0.85.1",
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"pycloudflared": "0.2.0",
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"pycloudflared": "0.2.0",
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"ruamel.yaml": "0.17.21",
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"ruamel.yaml": "0.17.21",
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"sqlalchemy": "2.0.19",
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"python-multipart": "0.0.6",
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# "xformers": "0.0.16",
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# "xformers": "0.0.16",
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}
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}
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modules_to_log = ["torch", "torchvision", "sdkit", "stable-diffusion-sdkit"]
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modules_to_log = ["torch", "torchvision", "sdkit", "stable-diffusion-sdkit"]
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@ -38,6 +38,7 @@ SD_UI_DIR = os.getenv("SD_UI_PATH", None)
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CONFIG_DIR = os.path.abspath(os.path.join(SD_UI_DIR, "..", "scripts"))
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CONFIG_DIR = os.path.abspath(os.path.join(SD_UI_DIR, "..", "scripts"))
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MODELS_DIR = os.path.abspath(os.path.join(SD_DIR, "..", "models"))
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MODELS_DIR = os.path.abspath(os.path.join(SD_DIR, "..", "models"))
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BUCKET_DIR = os.path.abspath(os.path.join(SD_DIR, "..", "bucket"))
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USER_PLUGINS_DIR = os.path.abspath(os.path.join(SD_DIR, "..", "plugins"))
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USER_PLUGINS_DIR = os.path.abspath(os.path.join(SD_DIR, "..", "plugins"))
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CORE_PLUGINS_DIR = os.path.abspath(os.path.join(SD_UI_DIR, "plugins"))
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CORE_PLUGINS_DIR = os.path.abspath(os.path.join(SD_UI_DIR, "plugins"))
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127
ui/easydiffusion/bucket_manager.py
Normal file
127
ui/easydiffusion/bucket_manager.py
Normal file
@ -0,0 +1,127 @@
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from typing import List
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from fastapi import Depends, FastAPI, HTTPException, Response, File
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from fastapi.responses import FileResponse
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from sqlalchemy.orm import Session
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from easydiffusion.easydb import crud, models, schemas
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from easydiffusion.easydb.database import SessionLocal, engine
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from requests.compat import urlparse
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from os.path import abspath
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import base64, json
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MIME_TYPES = {
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"jpg": "image/jpeg",
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"jpeg": "image/jpeg",
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"gif": "image/gif",
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"png": "image/png",
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"webp": "image/webp",
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"js": "text/javascript",
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"htm": "text/html",
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"html": "text/html",
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"css": "text/css",
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"json": "application/json",
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"mjs": "application/json",
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"yaml": "application/yaml",
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"svg": "image/svg+xml",
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"txt": "text/plain",
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}
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def init():
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from easydiffusion.server import server_api
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models.BucketBase.metadata.create_all(bind=engine)
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# Dependency
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def get_db():
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db = SessionLocal()
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try:
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yield db
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finally:
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db.close()
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@server_api.get("/bucket/{obj_path:path}")
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def bucket_get_object(obj_path: str, db: Session = Depends(get_db)):
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filename = get_filename_from_url(obj_path)
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path = get_path_from_url(obj_path)
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if filename==None:
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bucket = crud.get_bucket_by_path(db, path=path)
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if bucket == None:
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raise HTTPException(status_code=404, detail="Bucket not found")
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bucketfiles = db.query(models.BucketFile).with_entities(models.BucketFile.filename).filter(models.BucketFile.bucket_id == bucket.id).all()
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bucketfiles = [ x.filename for x in bucketfiles ]
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return bucketfiles
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else:
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bucket_id = crud.get_bucket_by_path(db, path).id
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bucketfile = db.query(models.BucketFile).filter(models.BucketFile.bucket_id == bucket_id, models.BucketFile.filename == filename).first()
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suffix = get_suffix_from_filename(filename)
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return Response(content=bucketfile.data, media_type=MIME_TYPES.get(suffix, "application/octet-stream"))
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@server_api.post("/bucket/{obj_path:path}")
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def bucket_post_object(obj_path: str, file: bytes = File(), db: Session = Depends(get_db)):
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filename = get_filename_from_url(obj_path)
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path = get_path_from_url(obj_path)
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bucket = crud.get_bucket_by_path(db, path)
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if bucket == None:
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bucket_id = crud.create_bucket(db=db, bucket=schemas.BucketCreate(path=path))
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else:
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bucket_id = bucket.id
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bucketfile = schemas.BucketFileCreate(filename=filename, data=file)
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result = crud.create_bucketfile(db=db, bucketfile=bucketfile, bucket_id=bucket_id)
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result.data = base64.encodestring(result.data)
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return result
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@server_api.post("/buckets/{bucket_id}/items/", response_model=schemas.BucketFile)
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def create_bucketfile_in_bucket(
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bucket_id: int, bucketfile: schemas.BucketFileCreate, db: Session = Depends(get_db)
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):
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bucketfile.data = base64.decodestring(bucketfile.data)
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result = crud.create_bucketfile(db=db, bucketfile=bucketfile, bucket_id=bucket_id)
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result.data = base64.encodestring(result.data)
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return result
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@server_api.get("/image/{image_path:path}")
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def get_image(image_path: str, db: Session = Depends(get_db)):
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from easydiffusion.easydb.mappings import Image
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image_path = str(abspath(image_path))
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amount = len(db.query(Image).filter(Image.path == image_path).all())
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if amount > 0:
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image = db.query(Image).filter(Image.path == image_path).first()
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return FileResponse(image.path)
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else:
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raise HTTPException(status_code=404, detail="Image not found")
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@server_api.get("/all_images")
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def get_all_images(db: Session = Depends(get_db)):
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from easydiffusion.easydb.mappings import Image
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images = db.query(Image).all()
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sum_string = "<div id='imagecontainer'>"
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for img in images:
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options = f"Path: {img.path}\nPrompt: {img.prompt}\nNegative Prompt: {img.negative_prompt}\nSeed: {img.seed}\nModel: {img.use_stable_diffusion_model}\nSize: {img.height}x{img.width}\nSampler: {img.sampler_name}\nSteps: {img.num_inference_steps}\nGuidance Scale: {img.guidance_scale}\nLoRA: {img.lora}\nUpscaling: {img.use_upscale}\nFace Correction: {img.use_face_correction}\n"
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sum_string += f"<img src='/image/{img.path}' title='{options}'>"
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sum_string += "</div>"
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return Response(content=sum_string, media_type="text/html")
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def get_filename_from_url(url):
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path = urlparse(url).path
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name = path[path.rfind('/')+1:]
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return name or None
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def get_path_from_url(url):
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path = urlparse(url).path
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path = path[0:path.rfind('/')]
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return path or None
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def get_suffix_from_filename(filename):
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return filename[filename.rfind('.')+1:]
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25
ui/easydiffusion/easydb/crud.py
Normal file
25
ui/easydiffusion/easydb/crud.py
Normal file
@ -0,0 +1,25 @@
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from sqlalchemy.orm import Session
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from easydiffusion.easydb import models, schemas
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def get_bucket_by_path(db: Session, path: str):
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return db.query(models.Bucket).filter(models.Bucket.path == path).first()
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def create_bucket(db: Session, bucket: schemas.BucketCreate):
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db_bucket = models.Bucket(path=bucket.path)
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db.add(db_bucket)
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db.commit()
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db.refresh(db_bucket)
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return db_bucket
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def create_bucketfile(db: Session, bucketfile: schemas.BucketFileCreate, bucket_id: int):
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db_bucketfile = models.BucketFile(**bucketfile.dict(), bucket_id=bucket_id)
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db.merge(db_bucketfile)
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db.commit()
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from pprint import pprint
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db_bucketfile = db.query(models.BucketFile).filter(models.BucketFile.bucket_id==bucket_id, models.BucketFile.filename==bucketfile.filename).first()
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return db_bucketfile
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15
ui/easydiffusion/easydb/database.py
Normal file
15
ui/easydiffusion/easydb/database.py
Normal file
@ -0,0 +1,15 @@
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import os
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from easydiffusion import app
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from sqlalchemy import create_engine
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from sqlalchemy.ext.declarative import declarative_base
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from sqlalchemy.orm import sessionmaker
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os.makedirs(app.BUCKET_DIR, exist_ok=True)
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SQLALCHEMY_DATABASE_URL = "sqlite:///"+os.path.join(app.BUCKET_DIR, "bucket.db")
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print("## SQLALCHEMY_DATABASE_URL = ", SQLALCHEMY_DATABASE_URL)
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engine = create_engine(SQLALCHEMY_DATABASE_URL, connect_args={"check_same_thread": False})
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SessionLocal = sessionmaker(autocommit=False, autoflush=False, bind=engine)
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BucketBase = declarative_base()
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32
ui/easydiffusion/easydb/mappings.py
Normal file
32
ui/easydiffusion/easydb/mappings.py
Normal file
@ -0,0 +1,32 @@
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from sqlalchemy import Column, Integer, String, Float, Boolean
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from sqlalchemy.ext.declarative import declarative_base
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Base = declarative_base()
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class Image(Base):
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__tablename__ = 'images'
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path = Column(String, primary_key=True)
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seed = Column(Integer)
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use_stable_diffusion_model = Column(String)
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clip_skip = Column(Boolean)
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use_vae_model = Column(String)
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sampler_name = Column(String)
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width = Column(Integer)
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|
height = Column(Integer)
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num_inference_steps = Column(Integer)
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guidance_scale = Column(Float)
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|
lora = Column(String)
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|
use_hypernetwork_model = Column(String)
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tiling = Column(String)
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use_face_correction = Column(String)
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use_upscale = Column(String)
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|
prompt = Column(String)
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|
negative_prompt = Column(String)
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|
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|
def __repr__(self):
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|
return "<Image(path='%s', seed='%s', use_stable_diffusion_model='%s', clip_skip='%s', use_vae_model='%s', sampler_name='%s', width='%s', height='%s', num_inference_steps='%s', guidance_scale='%s', lora='%s', use_hypernetwork_model='%s', tiling='%s', use_face_correction='%s', use_upscale='%s', prompt='%s', negative_prompt='%s')>" % (
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|
self.path, self.seed, self.use_stable_diffusion_model, self.clip_skip, self.use_vae_model, self.sampler_name, self.width, self.height, self.num_inference_steps, self.guidance_scale, self.lora, self.use_hypernetwork_model, self.tiling, self.use_face_correction, self.use_upscale, self.prompt, self.negative_prompt)
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|
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|
from easydiffusion.easydb.database import engine
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Image.metadata.create_all(engine)
|
25
ui/easydiffusion/easydb/models.py
Normal file
25
ui/easydiffusion/easydb/models.py
Normal file
@ -0,0 +1,25 @@
|
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|
from sqlalchemy import Boolean, Column, ForeignKey, Integer, String, BLOB
|
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|
from sqlalchemy.orm import relationship
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|
|
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|
from easydiffusion.easydb.database import BucketBase
|
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|
|
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|
|
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|
class Bucket(BucketBase):
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|
__tablename__ = "bucket"
|
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|
|
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|
id = Column(Integer, primary_key=True, index=True)
|
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|
path = Column(String, unique=True, index=True)
|
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|
|
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|
bucketfiles = relationship("BucketFile", back_populates="bucket")
|
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|
|
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|
|
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|
class BucketFile(BucketBase):
|
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|
__tablename__ = "bucketfile"
|
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|
|
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|
filename = Column(String, index=True, primary_key=True)
|
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|
bucket_id = Column(Integer, ForeignKey("bucket.id"), primary_key=True)
|
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|
|
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|
data = Column(BLOB, index=False)
|
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|
|
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|
bucket = relationship("Bucket", back_populates="bucketfiles")
|
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|
|
36
ui/easydiffusion/easydb/schemas.py
Normal file
36
ui/easydiffusion/easydb/schemas.py
Normal file
@ -0,0 +1,36 @@
|
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|
from typing import List, Union
|
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|
|
||||||
|
from pydantic import BaseModel
|
||||||
|
|
||||||
|
|
||||||
|
class BucketFileBase(BaseModel):
|
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|
filename: str
|
||||||
|
data: bytes
|
||||||
|
|
||||||
|
|
||||||
|
class BucketFileCreate(BucketFileBase):
|
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|
pass
|
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|
|
||||||
|
|
||||||
|
class BucketFile(BucketFileBase):
|
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|
bucket_id: int
|
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|
|
||||||
|
class Config:
|
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|
orm_mode = True
|
||||||
|
|
||||||
|
|
||||||
|
class BucketBase(BaseModel):
|
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|
path: str
|
||||||
|
|
||||||
|
|
||||||
|
class BucketCreate(BucketBase):
|
||||||
|
pass
|
||||||
|
|
||||||
|
|
||||||
|
class Bucket(BucketBase):
|
||||||
|
id: int
|
||||||
|
bucketfiles: List[BucketFile] = []
|
||||||
|
|
||||||
|
class Config:
|
||||||
|
orm_mode = True
|
||||||
|
|
@ -142,6 +142,47 @@ def save_images_to_disk(
|
|||||||
output_quality=output_format.output_quality,
|
output_quality=output_format.output_quality,
|
||||||
output_lossless=output_format.output_lossless,
|
output_lossless=output_format.output_lossless,
|
||||||
)
|
)
|
||||||
|
|
||||||
|
for i in range(len(filtered_images)):
|
||||||
|
path_i = f"{os.path.join(save_dir_path, make_filename(i))}.{output_format.output_format.lower()}"
|
||||||
|
|
||||||
|
def createLoraString(metadata_entries, i):
|
||||||
|
if metadata_entries[i]["use_lora_model"] is None:
|
||||||
|
return "None"
|
||||||
|
elif isinstance(metadata_entries[i]["use_lora_model"], list):
|
||||||
|
loraString = ""
|
||||||
|
for j in range(len(metadata_entries[i]["use_lora_model"])):
|
||||||
|
loraString += metadata_entries[i]["use_lora_model"][j] + ":" + str(metadata_entries[i]["lora_alpha"][j]) + " "
|
||||||
|
return loraString.trim()
|
||||||
|
else:
|
||||||
|
return metadata_entries[i]["use_lora_model"] + ":" + str(metadata_entries[i]["lora_alpha"])
|
||||||
|
|
||||||
|
from easydiffusion.easydb.mappings import Image
|
||||||
|
from easydiffusion.easydb.database import SessionLocal
|
||||||
|
|
||||||
|
session = SessionLocal()
|
||||||
|
session.add(Image(
|
||||||
|
path = path_i,
|
||||||
|
seed = metadata_entries[i]["seed"],
|
||||||
|
use_stable_diffusion_model = metadata_entries[i]["use_stable_diffusion_model"],
|
||||||
|
clip_skip = metadata_entries[i]["clip_skip"],
|
||||||
|
use_vae_model = metadata_entries[i]["use_vae_model"],
|
||||||
|
sampler_name = metadata_entries[i]["sampler_name"],
|
||||||
|
width = metadata_entries[i]["width"],
|
||||||
|
height = metadata_entries[i]["height"],
|
||||||
|
num_inference_steps = metadata_entries[i]["num_inference_steps"],
|
||||||
|
guidance_scale = metadata_entries[i]["guidance_scale"],
|
||||||
|
lora = createLoraString(metadata_entries, i),
|
||||||
|
use_hypernetwork_model = metadata_entries[i]["use_hypernetwork_model"],
|
||||||
|
tiling = metadata_entries[i]["tiling"],
|
||||||
|
use_face_correction = metadata_entries[i]["use_face_correction"],
|
||||||
|
use_upscale = metadata_entries[i]["use_upscale"],
|
||||||
|
prompt = metadata_entries[i]["prompt"],
|
||||||
|
negative_prompt = metadata_entries[i]["negative_prompt"]
|
||||||
|
))
|
||||||
|
session.commit()
|
||||||
|
session.close()
|
||||||
|
|
||||||
if task_data.metadata_output_format:
|
if task_data.metadata_output_format:
|
||||||
for metadata_output_format in task_data.metadata_output_format.split(","):
|
for metadata_output_format in task_data.metadata_output_format.split(","):
|
||||||
if metadata_output_format.lower() in ["json", "txt", "embed"]:
|
if metadata_output_format.lower() in ["json", "txt", "embed"]:
|
||||||
|
@ -49,6 +49,9 @@
|
|||||||
<span id="tab-about" class="tab">
|
<span id="tab-about" class="tab">
|
||||||
<span><i class="fa fa-comments icon"></i> Help & Community</span>
|
<span><i class="fa fa-comments icon"></i> Help & Community</span>
|
||||||
</span>
|
</span>
|
||||||
|
<span id="tab-gallery" class="tab">
|
||||||
|
<span><i class="fa fa-images icon"></i> Gallery</span>
|
||||||
|
</span>
|
||||||
</div>
|
</div>
|
||||||
</div>
|
</div>
|
||||||
|
|
||||||
@ -511,6 +514,10 @@
|
|||||||
</div>
|
</div>
|
||||||
</div>
|
</div>
|
||||||
</div>
|
</div>
|
||||||
|
<div id="tab-content-gallery" class="tab-content">
|
||||||
|
<button class="primaryButton" onclick="refreshGallery()">Refresh</button>
|
||||||
|
<div id="imagecontainer"></div>
|
||||||
|
</div>
|
||||||
</div>
|
</div>
|
||||||
|
|
||||||
<div class="popup" id="splash-screen" data-version="1">
|
<div class="popup" id="splash-screen" data-version="1">
|
||||||
|
@ -1,4 +1,4 @@
|
|||||||
from easydiffusion import model_manager, app, server
|
from easydiffusion import model_manager, app, server, bucket_manager
|
||||||
from easydiffusion.server import server_api # required for uvicorn
|
from easydiffusion.server import server_api # required for uvicorn
|
||||||
|
|
||||||
app.init()
|
app.init()
|
||||||
@ -8,6 +8,7 @@ server.init()
|
|||||||
# Init the app
|
# Init the app
|
||||||
model_manager.init()
|
model_manager.init()
|
||||||
app.init_render_threads()
|
app.init_render_threads()
|
||||||
|
bucket_manager.init()
|
||||||
|
|
||||||
# start the browser ui
|
# start the browser ui
|
||||||
app.open_browser()
|
app.open_browser()
|
||||||
|
@ -1831,4 +1831,24 @@ div#enlarge-buttons {
|
|||||||
/* hack for fixing Image Modifier Improvements plugin */
|
/* hack for fixing Image Modifier Improvements plugin */
|
||||||
#imageTagPopupContainer {
|
#imageTagPopupContainer {
|
||||||
position: absolute;
|
position: absolute;
|
||||||
}
|
}
|
||||||
|
/* Gallery CSS */
|
||||||
|
#imagecontainer {
|
||||||
|
display: flex;
|
||||||
|
justify-content: space-around;
|
||||||
|
flex-flow: row wrap;
|
||||||
|
align-items: center;
|
||||||
|
}
|
||||||
|
|
||||||
|
#imagecontainer>img {
|
||||||
|
width: 30vw;
|
||||||
|
min-width: 256px;
|
||||||
|
max-width: 1024px;
|
||||||
|
height: auto;
|
||||||
|
margin-block: 1vh;
|
||||||
|
border: 4px white solid;
|
||||||
|
}
|
||||||
|
|
||||||
|
#tab-content-gallery>button {
|
||||||
|
margin: 8px;
|
||||||
|
}
|
||||||
|
BIN
ui/media/images/noimg.png
Normal file
BIN
ui/media/images/noimg.png
Normal file
Binary file not shown.
After Width: | Height: | Size: 1.3 KiB |
@ -537,6 +537,7 @@ function showImages(reqBody, res, outputContainer, livePreview) {
|
|||||||
{ text: "Upscale", on_click: onUpscaleClick },
|
{ text: "Upscale", on_click: onUpscaleClick },
|
||||||
{ text: "Fix Faces", on_click: onFixFacesClick },
|
{ text: "Fix Faces", on_click: onFixFacesClick },
|
||||||
],
|
],
|
||||||
|
{ text: "Use as Thumbnail", on_click: onUseAsThumbnailClick },
|
||||||
]
|
]
|
||||||
|
|
||||||
// include the plugins
|
// include the plugins
|
||||||
@ -677,6 +678,20 @@ function onMakeSimilarClick(req, img) {
|
|||||||
createTask(newTaskRequest)
|
createTask(newTaskRequest)
|
||||||
}
|
}
|
||||||
|
|
||||||
|
function onUseAsThumbnailClick(req, img) {
|
||||||
|
console.log(req)
|
||||||
|
console.log(img)
|
||||||
|
let embedding = prompt("Embedding name")
|
||||||
|
fetch(img.src)
|
||||||
|
.then(response => response.blob())
|
||||||
|
.then(async function(blob) {
|
||||||
|
const formData = new FormData()
|
||||||
|
formData.append("file", blob)
|
||||||
|
const response = await fetch(`bucket/embeddings/${embedding}.jpg`, { method: 'POST', body: formData });
|
||||||
|
console.log(response)
|
||||||
|
})
|
||||||
|
}
|
||||||
|
|
||||||
function enqueueImageVariationTask(req, img, reqDiff) {
|
function enqueueImageVariationTask(req, img, reqDiff) {
|
||||||
const imageSeed = img.getAttribute("data-seed")
|
const imageSeed = img.getAttribute("data-seed")
|
||||||
|
|
||||||
@ -2509,19 +2524,27 @@ document.getElementById("toggle-tensorrt-install").addEventListener("click", fun
|
|||||||
|
|
||||||
/* Embeddings */
|
/* Embeddings */
|
||||||
|
|
||||||
|
let icl = []
|
||||||
function updateEmbeddingsList(filter = "") {
|
function updateEmbeddingsList(filter = "") {
|
||||||
function html(model, prefix = "", filter = "") {
|
function html(model, iconlist = [], prefix = "", filter = "") {
|
||||||
filter = filter.toLowerCase()
|
filter = filter.toLowerCase()
|
||||||
let toplevel = ""
|
let toplevel = ""
|
||||||
let folders = ""
|
let folders = ""
|
||||||
|
console.log(iconlist)
|
||||||
|
let embIcon = Object.assign({}, ...iconlist.map( x=> ({[x.toLowerCase().split('.').slice(0,-1).join('.')]:x})))
|
||||||
|
|
||||||
model?.forEach((m) => {
|
model?.forEach((m) => {
|
||||||
if (typeof m == "string") {
|
if (typeof m == "string") {
|
||||||
if (m.toLowerCase().search(filter) != -1) {
|
let token=m.toLowerCase()
|
||||||
toplevel += `<button data-embedding="${m}">${m}</button> `
|
if (token.search(filter) != -1) {
|
||||||
|
let img = '/media/images/noimg.png'
|
||||||
|
if (token in embIcon) {
|
||||||
|
img = `/bucket/embeddings/${embIcon[token]}`
|
||||||
|
}
|
||||||
|
toplevel += `<button data-embedding="${m}"><img src="${img}" height="128" width="128"><br>${m}</button> `
|
||||||
}
|
}
|
||||||
} else {
|
} else {
|
||||||
let subdir = html(m[1], prefix + m[0] + "/", filter)
|
let subdir = html(m[1], iconlist, prefix + m[0] + "/", filter)
|
||||||
if (subdir != "") {
|
if (subdir != "") {
|
||||||
folders +=
|
folders +=
|
||||||
`<div class="embedding-category"><h4 class="collapsible">${prefix}${m[0]}</h4><div class="collapsible-content">` +
|
`<div class="embedding-category"><h4 class="collapsible">${prefix}${m[0]}</h4><div class="collapsible-content">` +
|
||||||
@ -2534,7 +2557,7 @@ function updateEmbeddingsList(filter = "") {
|
|||||||
}
|
}
|
||||||
|
|
||||||
function onButtonClick(e) {
|
function onButtonClick(e) {
|
||||||
let text = e.target.dataset["embedding"]
|
let text = e.target.closest("button").dataset["embedding"]
|
||||||
const insertIntoNegative = e.shiftKey || positiveEmbeddingText.classList.contains("displayNone")
|
const insertIntoNegative = e.shiftKey || positiveEmbeddingText.classList.contains("displayNone")
|
||||||
|
|
||||||
if (embeddingsModeField.value == "insert") {
|
if (embeddingsModeField.value == "insert") {
|
||||||
@ -2569,14 +2592,18 @@ function updateEmbeddingsList(filter = "") {
|
|||||||
}
|
}
|
||||||
// END of remove block
|
// END of remove block
|
||||||
|
|
||||||
embeddingsList.innerHTML = warning + html(modelsOptions.embeddings, "", filter)
|
fetch("/bucket/embeddings/")
|
||||||
embeddingsList.querySelectorAll("button").forEach((b) => {
|
.then(response => response.json())
|
||||||
b.addEventListener("click", onButtonClick)
|
.then(iconlist => {
|
||||||
})
|
embeddingsList.innerHTML = warning + html(modelsOptions.embeddings, iconlist, "", filter)
|
||||||
createCollapsibles(embeddingsList)
|
embeddingsList.querySelectorAll("button").forEach((b) => {
|
||||||
if (filter != "") {
|
b.addEventListener("click", onButtonClick)
|
||||||
embeddingsExpandAll()
|
})
|
||||||
}
|
createCollapsibles(embeddingsList)
|
||||||
|
if (filter != "") {
|
||||||
|
embeddingsExpandAll()
|
||||||
|
}
|
||||||
|
})
|
||||||
}
|
}
|
||||||
|
|
||||||
function showEmbeddingDialog() {
|
function showEmbeddingDialog() {
|
||||||
@ -2909,3 +2936,15 @@ let recentResolutionsValues = []
|
|||||||
heightField.value = temp
|
heightField.value = temp
|
||||||
})
|
})
|
||||||
})()
|
})()
|
||||||
|
|
||||||
|
/* Gallery JS */
|
||||||
|
|
||||||
|
function refreshGallery() {
|
||||||
|
let container = document.getElementById("imagecontainer")
|
||||||
|
container.remove()
|
||||||
|
fetch('/all_images')
|
||||||
|
.then(response => response.text())
|
||||||
|
.then(text => new DOMParser().parseFromString(text, 'text/html'))
|
||||||
|
.then(html_like => html_like.getElementsByTagName('div')[0])
|
||||||
|
.then(div => document.getElementById("tab-content-gallery").appendChild(div))
|
||||||
|
}
|
Loading…
x
Reference in New Issue
Block a user