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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("dreamlike-art/dreamlike-photoreal-2.0", 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="<br> <h4> <div style='width:100%'> Info:Dream Art (SD) <br> This App is our favorite now and shows how Stable diffusion works i a good way !</h4> </div>",
).launch(debug=True, max_threads=True)
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