|
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) |
|
|
|
|
|
|
|
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 |
|
</p> |
|
</div> |
|
""" |
|
|
|
article = """ |
|
|
|
""" |
|
|
|
css = ''' |
|
#col-container {max-width: 700px; margin-left: auto; margin-right: auto;} |
|
a {text-decoration-line: underline; font-weight: 600;} |
|
''' |
|
|
|
|
|
with gr.Blocks(css=css) as block: |
|
with gr.Column(elem_id="col-container"): |
|
gr.HTML(title) |
|
|
|
prompt_input = gr.Textbox() |
|
image_init = gr.Image(source="upload", type="filepath") |
|
|
|
submit_btn = gr.Button("Submit") |
|
|
|
image_output = gr.Image() |
|
|
|
|
|
|
|
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) |
