| 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, safety_checker=None) | |
| upscaler = upscaler.to(device) | |
| pipe = pipe.to(device) | |
| 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?'), | |
| ], | |
| 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) |