import gradio as gr import torch import numpy as np import modin.pandas as pd from PIL import Image from diffusers import DiffusionPipeline, StableDiffusionLatentUpscalePipeline device = "cuda" if torch.cuda.is_available() else "cpu" pipe = DiffusionPipeline.from_pretrained("models/stablediffusionapi/juggernaut-xl-v5", torch_dtype=torch.float16, safety_checker=None, use_safetensors=False) upscaler = StableDiffusionLatentUpscalePipeline.from_pretrained("stabilityai/sd-x2-latent-upscaler", torch_dtype=torch.float16) upscaler = upscaler.to(device) pipe = pipe.to(device) def genie (Prompt, negative_prompt, height, width, scale, steps, seed, upscale, upscale_prompt, upscale_neg, upscale_scale, upscale_steps): generator = torch.Generator(device=device).manual_seed(seed) if upscale == "Yes": low_res_latents = pipe(Prompt, negative_prompt=negative_prompt, height=height, width=width, num_inference_steps=steps, guidance_scale=scale, generator=generator, output_type="latent").images image = upscaler(prompt=upscale_prompt, negative_prompt=upscale_neg, image=low_res_latents, num_inference_steps=upscale_steps, guidance_scale=upscale_scale, generator=generator).images[0] else: image = pipe(Prompt, negative_prompt=negative_prompt, height=height, width=width, num_inference_steps=steps, guidance_scale=scale, generator=generator).images[0] return image gr.Interface(theme='ParityError/Anime', fn=genie, inputs=[gr.Textbox(label='Input field right under here(Prompt)'), gr.Textbox(label='What You dont want (Negative Prompt)'), gr.Slider(512, 1024, 768, step=128, label='Height'), gr.Slider(512, 1024, 768, step=128, label='Width'), gr.Slider(1, maximum=15, value=10, step=.25), gr.Slider(25, maximum=100, value=50, step=25), gr.Slider(minimum=1, step=1, maximum=9999999999999999, randomize=True), # gr.Radio(["Yes", "No"], label='Upscale?'), #gr.Textbox(label='Upscaler Prompt: Optional'), #gr.Textbox(label='Upscaler Negative Prompt: Both Optional And Experimental'), #gr.Slider(minimum=0, maximum=15, value=0, step=1, label='Upscale Guidance Scale'), #gr.Slider(minimum=5, maximum=25, value=5, step=5, label='Upscaler Iterations') ], outputs=gr.Image(label='Generated Image'), title="Dream Art (SD) ", description="

Info:Dream Art (SD)
This App is our favorite now and shows how Stable diffusion works i a good way !

", ).launch(debug=True, max_threads=True)