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( """

Stable Diffusion CPU

""" ) 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()