import gradio as gr import torch from diffusers import StableDiffusionXLPipeline, AutoencoderKL from huggingface_hub import hf_hub_download import spaces from PIL import Image import requests from translatepy import Translator translator = Translator() # Constants model = "Corcelio/openvision" vae_model = "madebyollin/sdxl-vae-fp16-fix" CSS = """ .gradio-container { max-width: 690px !important; } footer { visibility: hidden; } """ JS = """function () { gradioURL = window.location.href if (!gradioURL.endsWith('?__theme=dark')) { window.location.replace(gradioURL + '?__theme=dark'); } }""" # Load VAE component vae = AutoencoderKL.from_pretrained( vae_model, torch_dtype=torch.float16 ) # Ensure model and scheduler are initialized in GPU-enabled function if torch.cuda.is_available(): pipe = StableDiffusionXLPipeline.from_pretrained(model, vae=vae, torch_dtype=torch.float16).to("cuda") # Function @spaces.GPU() def generate_image( prompt, negative, width=1024, height=1024, scale=1.5, steps=30): prompt = str(translator.translate(prompt, 'English')) print(f'prompt:{prompt}') image = pipe( prompt, negative_prompt=negative, width=width, height=height, guidance_scale=scale, num_inference_steps=steps, ) print(image.images[0]) return image.images[0] examples = [ "a cat eating a piece of cheese", "a ROBOT riding a BLUE horse on Mars, photorealistic", "Ironman VS Hulk, ultrarealistic", "a CUTE robot artist painting on an easel", "Astronaut in a jungle, cold color palette, oil pastel, detailed, 8k", "An alien holding sign board contain word 'Flash', futuristic, neonpunk", "Kids going to school, Anime style" ] # Gradio Interface with gr.Blocks(css=CSS, js=JS, theme="soft") as demo: gr.HTML("