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| import gradio as gr | |
| import torch | |
| from torch import autocast | |
| from diffusers import StableDiffusionPipeline | |
| from datasets import load_dataset | |
| from PIL import Image | |
| import re | |
| import streamlit as st | |
| model_id = "CompVis/stable-diffusion-v1-4" | |
| device = "cpu" | |
| #If you are running this code locally, you need to either do a 'huggingface-cli login` or paste your User Access Token from here https://huggingface.co/settings/tokens into the use_auth_token field below. | |
| pipe = StableDiffusionPipeline.from_pretrained(model_id, use_auth_token=st.secrets["AUTH_KEY"], torch_dtype=torch.float32) | |
| def dummy(images, **kwargs): return images, False | |
| pipe.safety_checker = dummy | |
| def infer(prompt, width, height, steps, scale, seed): | |
| if seed == -1: | |
| images_list = pipe( | |
| [prompt], | |
| height=height, | |
| width=width, | |
| num_inference_steps=steps, | |
| guidance_scale=scale, | |
| generator=torch.Generator(device=device).manual_seed(seed)) | |
| else: | |
| images_list = pipe( | |
| [prompt], | |
| height=height, | |
| width=width, | |
| num_inference_steps=steps, | |
| guidance_scale=scale) | |
| return images_list["sample"] | |
| css = """ | |
| .gradio-container { | |
| font-family: 'IBM Plex Sans', sans-serif; | |
| } | |
| .gr-button { | |
| color: white; | |
| border-color: black; | |
| background: black; | |
| } | |
| input[type='range'] { | |
| accent-color: black; | |
| } | |
| .dark input[type='range'] { | |
| accent-color: #dfdfdf; | |
| } | |
| .container { | |
| max-width: 730px; | |
| margin: auto; | |
| padding-top: 1.5rem; | |
| } | |
| #gallery { | |
| min-height: 22rem; | |
| margin-bottom: 15px; | |
| margin-left: auto; | |
| margin-right: auto; | |
| border-bottom-right-radius: .5rem !important; | |
| border-bottom-left-radius: .5rem !important; | |
| } | |
| #gallery>div>.h-full { | |
| min-height: 20rem; | |
| } | |
| .details:hover { | |
| text-decoration: underline; | |
| } | |
| .gr-button { | |
| white-space: nowrap; | |
| } | |
| .gr-button:focus { | |
| border-color: rgb(147 197 253 / var(--tw-border-opacity)); | |
| outline: none; | |
| box-shadow: var(--tw-ring-offset-shadow), var(--tw-ring-shadow), var(--tw-shadow, 0 0 #0000); | |
| --tw-border-opacity: 1; | |
| --tw-ring-offset-shadow: var(--tw-ring-inset) 0 0 0 var(--tw-ring-offset-width) var(--tw-ring-offset-color); | |
| --tw-ring-shadow: var(--tw-ring-inset) 0 0 0 calc(3px var(--tw-ring-offset-width)) var(--tw-ring-color); | |
| --tw-ring-color: rgb(191 219 254 / var(--tw-ring-opacity)); | |
| --tw-ring-opacity: .5; | |
| } | |
| .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; | |
| } | |
| .acknowledgments h4{ | |
| margin: 1.25em 0 .25em 0; | |
| font-weight: bold; | |
| font-size: 115%; | |
| } | |
| """ | |
| block = gr.Blocks(css=css) | |
| with block: | |
| gr.HTML( | |
| """ | |
| <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;"> | |
| Stable Diffusion CPU | |
| </h1> | |
| </div> | |
| </div> | |
| """ | |
| ) | |
| with gr.Group(): | |
| with gr.Box(): | |
| with gr.Row().style(mobile_collapse=False, equal_height=True): | |
| text = gr.Textbox( | |
| label="Enter your prompt", | |
| show_label=False, | |
| max_lines=1, | |
| placeholder="Enter your prompt", | |
| ).style( | |
| border=(True, False, True, True), | |
| rounded=(True, False, False, True), | |
| container=False, | |
| ) | |
| btn = gr.Button("Generate image").style( | |
| margin=False, | |
| rounded=(False, True, True, False), | |
| ) | |
| gallery = gr.Gallery( | |
| label="Generated images", show_label=False, elem_id="gallery" | |
| ).style(grid=[2], height="auto") | |
| with gr.Row().style(mobile_collapse=False, equal_height=True): | |
| width = gr.Slider(label="Width", minimum=32, maximum=1024, value=512, step=8) | |
| height = gr.Slider(label="Height", minimum=32, maximum=1024, value=512, step=8) | |
| with gr.Row(): | |
| steps = gr.Slider(label="Steps", minimum=1, maximum=50, value=30, step=1) | |
| scale = gr.Slider( | |
| label="Guidance Scale", minimum=0, maximum=50, value=7.5, step=0.1 | |
| ) | |
| seed = gr.Slider( | |
| label="Seed", | |
| minimum=-1, | |
| maximum=2147483647, | |
| step=1, | |
| value=-1, | |
| ) | |
| text.submit(infer, inputs=[text, width, height, steps, scale, seed], outputs=gallery) | |
| btn.click(infer, inputs=[text, width, height, steps, scale, seed], outputs=gallery) | |
| block.queue(max_size=10).launch() |