Spaces:
Running
on
T4
Running
on
T4
import gradio as gr | |
import torch | |
import numpy as np | |
import modin.pandas as pd | |
from PIL import Image | |
from diffusers import DiffusionPipeline, StableDiffusionLatentUpscalePipeline | |
import random | |
random.seed(0) | |
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.manual_seed(seed) | |
if upscale == "Yes": | |
image = pipe(Prompt, negative_prompt=negative_prompt, height=height, width=width, num_inference_steps=steps, guidance_scale=scale).images[0] | |
upscaled = upscaler(Prompt, negative_prompt=negative_prompt, image=image, num_inference_steps=5, guidance_scale=0).images[0] | |
return (image, upscaled) | |
else: | |
image = pipe(Prompt, negative_prompt=negative_prompt, height=height, width=width, num_inference_steps=steps, guidance_scale=scale).images[0] | |
return (image, 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=7, step=.25, label='Guidance Scale'), | |
gr.Slider(25, maximum=100, value=50, step=25, label='Number of Iterations'), | |
gr.Slider(minimum=0, step=1, maximum=9999999999999999, randomize=True, label='Seed: 0 is Random'), | |
gr.Radio(["Yes", "No"], label='Upscale?', value='No'), | |
], | |
outputs=[gr.Image(label='Generated Image'), gr.Image(label='Generated Image')], | |
title="PhotoReal V3.6 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) |