| import gradio as gr | |
| import modin.pandas as pd | |
| import torch | |
| import numpy as np | |
| from PIL import Image | |
| from diffusers import DiffusionPipeline | |
| from huggingface_hub import login | |
| import os | |
| login(token=os.environ.get('HF_KEY')) | |
| device = "cuda" if torch.cuda.is_available() else "cpu" | |
| pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-refiner-0.9", torch_dtype=torch.float16) if torch.cuda.is_available() else DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-refiner-0.9", safety_checker=None) | |
| pipe = pipe.to(device) | |
| def resize(value,img): | |
| img = Image.open(img) | |
| img = img.resize((value,value)) | |
| return img | |
| def infer(source_img, prompt, negative_prompt, guide, steps, seed, Strength): | |
| generator = torch.Generator(device).manual_seed(seed) | |
| source_image = resize(768, source_img) | |
| source_image.save('source.png') | |
| image = pipe(prompt, negative_prompt=negative_prompt, image=source_image, strength=Strength, guidance_scale=guide, num_inference_steps=steps).images[0] | |
| return image | |
| gr.Interface(fn=infer, inputs=[gr.Image(source="upload", type="filepath", label="Raw Image. Must Be .png"), gr.Textbox(label = 'Prompt Input Text. 77 Token (Keyword or Symbol) Maximum'), gr.Textbox(label='What you Do Not want the AI to generate.'), | |
| gr.Slider(2, 15, value = 7, label = 'Guidance Scale'), | |
| gr.Slider(1, 25, value = 10, step = 1, label = 'Number of Iterations'), | |
| gr.Slider(label = "Seed", minimum = 0, maximum = 987654321987654321, step = 1, randomize = True), | |
| gr.Slider(label='Strength', minimum = 0, maximum = 1, step = .05, value = .5)], | |
| outputs='image', title = "Stable Diffusion XL 0.9 Image to Image Pipeline CPU", description = "For more information on Stable Diffusion XL 0.9 see https://github.com/Stability-AI/stablediffusion <br><br>Upload an Image (<b>MUST Be .PNG and 512x512 or 768x768</b>) enter a Prompt, or let it just do its Thing, then click submit. 10 Iterations takes about ~900-1200 seconds currently. For more informationon about Stable Diffusion or Suggestions for prompts, keywords, artists or styles see https://github.com/Maks-s/sd-akashic", article = "Code Monkey: <a href=\"https://huggingface.co/Manjushri\">Manjushri</a>").queue(max_size=5).launch() |