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T4
File size: 2,906 Bytes
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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("circulus/canvers-realistic-v3.6", torch_dtype=torch.float16, safety_checker=None)
pipe = pipe.to(device)
pipe.enable_xformers_memory_efficient_attention()
upscaler = StableDiffusionLatentUpscalePipeline.from_pretrained("stabilityai/sd-x2-latent-upscaler", torch_dtype=torch.float16, safety_checker=None)
upscaler = upscaler.to(device)
upscaler.enable_xformers_memory_efficient_attention()
def genie (Prompt, negative_prompt, height, width, scale, steps, Seed, upscale):
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, negative_prompt=negative_prompt, image=low_res_latents, num_inference_steps=5, guidance_scale=0, 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(fn=genie, inputs=[gr.Textbox(label='What you want the AI to generate. 77 Token Limit.'),
gr.Textbox(label='What you Do Not want the AI to generate. 77 Token Limit'),
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?', value='No'),
],
outputs=gr.Image(label='Generated Image'),
title="PhotoReal V2 with SD x2 Upscaler - GPU",
description="<br><br><b/>Warning: This Demo is capable of producing NSFW content.",
article = "If You Enjoyed this Demo and would like to Donate, you can send to any of these Wallets. <br>BTC: bc1qzdm9j73mj8ucwwtsjx4x4ylyfvr6kp7svzjn84 <br>3LWRoKYx6bCLnUrKEdnPo3FCSPQUSFDjFP <br>DOGE: DK6LRc4gfefdCTRk9xPD239N31jh9GjKez <br>SHIB (BEP20): 0xbE8f2f3B71DFEB84E5F7E3aae1909d60658aB891 <br>PayPal: https://www.paypal.me/ManjushriBodhisattva <br>ETH: 0xbE8f2f3B71DFEB84E5F7E3aae1909d60658aB891 <br>Code Monkey: <a href=\"https://huggingface.co/Manjushri\">Manjushri</a>").launch(debug=True, max_threads=80) |