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| import gradio as gr | |
| from PIL import Image | |
| from io import BytesIO | |
| import torch | |
| import os | |
| from diffusers import DiffusionPipeline, DDIMScheduler | |
| MY_SECRET_TOKEN=os.environ.get('HF_TOKEN_SD') | |
| has_cuda = torch.cuda.is_available() | |
| device = torch.device('cpu' if not has_cuda else 'cuda') | |
| pipe = DiffusionPipeline.from_pretrained( | |
| "CompVis/stable-diffusion-v1-4", | |
| safety_checker=None, | |
| use_auth_token=MY_SECRET_TOKEN, | |
| custom_pipeline="imagic_stable_diffusion", | |
| scheduler = DDIMScheduler(beta_start=0.00085, beta_end=0.012, beta_schedule="scaled_linear", clip_sample=False, set_alpha_to_one=False) | |
| ).to(device) | |
| #generator = torch.Generator("cuda").manual_seed(0) | |
| def infer(prompt, init_image): | |
| res = pipe.train( | |
| prompt, | |
| init_image, | |
| guidance_scale=7.5, | |
| num_inference_steps=50) | |
| res = pipe(alpha=1) | |
| return res.images[0] | |
| title = """ | |
| <div style="text-align: center; max-width: 650px; margin: 0 auto;"> | |
| <div | |
| style=" | |
| display: inline-flex; | |
| align-items: center; | |
| gap: 0.8rem; | |
| font-size: 1.75rem; | |
| " | |
| > | |
| <h1 style="font-weight: 900; margin-bottom: 7px;"> | |
| Imagic Stable Diffusion • Community Pipeline | |
| </h1> | |
| </div> | |
| <p style="margin-bottom: 10px; font-size: 94%"> | |
| Text-Based Real Image Editing with Diffusion Models | |
| <br />This pipeline aims to implement <a href="" target="_blank">this paper</a> to Stable Diffusion, allowing for real-world image editing. | |
| </p> | |
| </div> | |
| """ | |
| article = """ | |
| <div class="footer"> | |
| <p><a href="https://github.com/huggingface/diffusers/tree/main/examples/community#imagic-stable-diffusion" target="_blank">Community pipeline</a> baked by <a href="https://github.com/apolinario" style="text-decoration: underline;" target="_blank">@apolinario</a> - Gradio Demo by 🤗 Sylvain Filoni | |
| </p> | |
| </div> | |
| """ | |
| css = ''' | |
| #col-container {max-width: 700px; margin-left: auto; margin-right: auto;} | |
| a {text-decoration-line: underline; font-weight: 600;} | |
| .footer { | |
| margin-bottom: 45px; | |
| margin-top: 35px; | |
| text-align: center; | |
| border-bottom: 1px solid #e5e5e5; | |
| } | |
| .footer>p { | |
| font-size: .8rem; | |
| display: inline-block; | |
| padding: 0 10px; | |
| transform: translateY(10px); | |
| background: white; | |
| } | |
| .dark .footer { | |
| border-color: #303030; | |
| } | |
| .dark .footer>p { | |
| background: #0b0f19; | |
| } | |
| ''' | |
| with gr.Blocks(css=css) as block: | |
| with gr.Column(elem_id="col-container"): | |
| gr.HTML(title) | |
| prompt_input = gr.Textbox(label="Prompt", placeholder="Describe the image with what you want to change about the subject") | |
| image_init = gr.Image(source="upload", type="filepath", label="Input Image") | |
| submit_btn = gr.Button("Submit") | |
| image_output = gr.Image(label="Result") | |
| #gr.HTML(article) | |
| submit_btn.click(fn=infer, inputs=[prompt_input,image_init], outputs=[image_output]) | |
| block.queue(max_size=32,concurrency_count=20).launch(show_api=False) |