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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 | |
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) | |
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, num_inference_steps=steps, guidance_scale=scale, generator=generator, output_type="latent").images | |
image = upscaler(prompt='', image=low_res_latents, num_inference_steps=upscale_iter, guidance_scale=0, generator=generator).images[0] | |
else: | |
image = pipe(Prompt, negative_prompt=negative_prompt, 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?'), | |
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="PhotoReal V2 with SD x2 Upscaler - GPU", | |
description="<br><br><b/>Warning: This Demo is capable of producing NSFW content.", | |
article = "Code Monkey: <a href=\"https://huggingface.co/Manjushri\">Manjushri</a>").launch(debug=True, max_threads=True) |