| 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 | |
| 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 = np.random.seed(0) if seed == 0 else 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.", | |
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