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from diffusers import AutoPipelineForText2Image
import torch
import gradio as gr
from PIL import Image
import os, random
from diffusers.utils import load_image
from accelerate import Accelerator
accelerator = Accelerator()
models =[
"prompthero/midjourney-v4-diffusion",
"nitrosocke/classic-anim-diffusion",
"stablediffusionapi/disney-pixal-cartoon",
"stablediffusionapi/edge-of-realism",
"sd-dreambooth-library/original-character-cyclps",
"AIArtsChannel/steampunk-diffusion",
"nitrosocke/mo-di-diffusion",
"MirageML/fantasy-scene",
"wavymulder/lomo-diffusion",
"sd-dreambooth-library/fashion",
"DucHaiten/DucHaitenDreamWorld",
"VegaKH/Ultraskin",
"kandinsky-community/kandinsky-2-1",
"plasmo/woolitize-768sd1-5",
"plasmo/food-crit",
"johnslegers/epic-diffusion-v1.1",
"robotjung/SemiRealMix",
"prompthero/linkedin-diffusion",
"RayHell/popupBook-diffusion",
"MirageML/lowpoly-world",
"warp-ai/wuerstchen",
"deadman44/SD_Photoreal_Merged_Models",
"johnslegers/epic-diffusion",
"wavymulder/modelshoot",
"Fictiverse/Stable_Diffusion_VoxelArt_Model",
"nousr/robo-diffusion-2-base",
"darkstorm2150/Protogen_v2.2_Official_Release",
"hassanblend/HassanBlend1.5.1.2",
"hassanblend/hassanblend1.4",
"nitrosocke/redshift-diffusion",
"prompthero/openjourney-v2",
"nitrosocke/Arcane-Diffusion",
"Lykon/DreamShaper",
"wavymulder/Analog-Diffusion",
"dreamlike-art/dreamlike-diffusion-1.0",
"dreamlike-art/dreamlike-photoreal-2.0",
"digiplay/RealismEngine_v1",
"digiplay/AIGEN_v1.4_diffusers",
"stablediffusionapi/dreamshaper-v6",
"axolotron/ice-cream-animals",
"TheLastBen/froggy-style-v21-768",
"FloydianSound/Nixeu_Diffusion_v1-5",
"digiplay/PotoPhotoRealism_v1",
]
###bor = len(models)
###current = random.randint(1, bor)
def plex(modil,prompt,neg_prompt):
pipe = accelerator.prepare(AutoPipelineForText2Image.from_pretrained(""+modil+"", torch_dtype=torch.float32))
pipe = accelerator.prepare(pipe.to("cpu"))
image = pipe(prompt=prompt, negative_prompt=neg_prompt,num_inference_steps=10).images[0]
return image
iface = gr.Interface(fn=plex,inputs=[gr.Dropdown(choices=models, type="value", value=models[0]), gr.Textbox(label="Prompt"), gr.Textbox(label="negative_prompt", value="low quality, bad quality")],outputs=gr.Image(label="Generated Output Image"), title="AutoPipelineForText2Image_SD_Multi",description="AutoPipelineForText2Image_SD_Multi")
iface.queue(max_size=1,api_open=False)
iface.launch(max_threads=1) |