text-to-image / app.py
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import gradio as gr
import requests
import os
name2 = "stabilityai/sd-x2-latent-upscaler"
model = gr.Interface.load(f"models/{name2}")
o = os.getenv("P")
def ac():
def im_fn(put,fac="",h=None):
if h == o:
put = f"{put}{fac}"
fac = f"{fac} "
return model(put),fac
elif h != o:
return(None,None)
def cl_fac():
return ""
with gr.Blocks() as b:
with gr.Row():
put = gr.Textbox()
btn1 = gr.Button()
with gr.Row():
out1 = gr.Image()
out2 = gr.Image()
with gr.Row():
out3 = gr.Image()
out4 = gr.Image()
with gr.Row(visible=False):
h=gr.Textbox("Q")
fac_b = gr.Textbox(value="",visible=False)
btn1.click(cl_fac,None,fac_b)
btn1.click(im_fn,[put,fac_b,h],[out1,fac_b])
out1.change(im_fn,[put,fac_b,h],[out2,fac_b])
out2.change(im_fn,[put,fac_b,h],[out3,fac_b])
out3.change(im_fn,[put,fac_b,h],[out4,fac_b])
b.queue(concurrency_count=100).launch(show_api=False)
ac()