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import gradio as gr
from models import models
from PIL import Image
import requests
import uuid
import io
import base64
import torch
from diffusers import AutoPipelineForImage2Image
from diffusers.utils import make_image_grid, load_image
base_url=f'https://omnibus-top-20-img-img-basic.hf.space/file='
loaded_model=[]
for i,model in enumerate(models):
try:
loaded_model.append(gr.load(f'models/{model}'))
except Exception as e:
print(e)
pass
print (loaded_model)
pipeline = AutoPipelineForImage2Image.from_pretrained("runwayml/stable-diffusion-v1-5", safety_checker=None, variant="fp16", use_safetensors=True).to("cpu")
def load_model(model_drop):
pipeline = AutoPipelineForImage2Image.from_pretrained("runwayml/stable-diffusion-v1-5", torch_dtype=torch.float32, use_safetensors=True)
def run_dif(prompt,im_path,model_drop,cnt,strength,guidance,infer):
out_box=[]
for i in range(int(cnt)):
yield out_box,f"Working on {i} of {int(cnt)}"
url = base_url+im_path
print(url)
init_image=load_image(url)
#image = pipeline(prompt, image=init_image, strength=0.8,guidance_scale=8.0,negative_prompt=negative_prompt,num_inference_steps=50).images[0]
image = pipeline(prompt, image=init_image, strength=float(strength),guidance_scale=float(guidance),num_inference_steps=int(infer)).images[0]
out_box.append(image)
yield out_box,"Complete"
css="""
.grid_class{
display:flex;
height:100%;
}
.img_class{
min-width:200px;
}
"""
with gr.Blocks(css=css) as app:
with gr.Row():
with gr.Column():
inp=gr.Textbox(label="Prompt")
strength=gr.Slider(label="Strength",minimum=0,maximum=1,step=0.1,value=0.2)
guidance=gr.Slider(label="Guidance",minimum=0,maximum=10,step=0.1,value=8.0)
infer=gr.Slider(label="Inference Steps",minimum=0,maximum=50,step=1,value=10)
with gr.Row():
btn=gr.Button()
stop_btn=gr.Button("Stop")
with gr.Column():
inp_im=gr.Image(type='filepath')
im_btn=gr.Button("Image Grid")
with gr.Row():
model_drop=gr.Dropdown(label="Models", choices=models, type='index', value=models[0])
cnt = gr.Number(value=1)
out_html=gr.HTML()
outp=gr.Gallery(columns=10)
#fingal=gr.Gallery(columns=10)
#im_list=gr.Textbox()
#im_btn.click(load_im,inp_im,[outp,im_list])
go_btn = btn.click(run_dif,[inp,inp_im,model_drop,cnt,strength,guidance,infer],[outp,out_html])
stop_btn.click(None,None,None,cancels=[go_btn])
app.queue().launch() |