File size: 1,219 Bytes
b6b08f6
3353a40
af2f25b
3353a40
9e40e71
4b7a185
af2f25b
8646ee7
a2ffcba
a8fdbd7
a2ffcba
184a373
 
 
a2ffcba
184a373
 
 
ffd68ae
184a373
 
 
b6eb1a4
 
184a373
b6eb1a4
184a373
 
cead56a
e540908
184a373
 
ed523c3
35cd00c
 
 
8646ee7
af2f25b
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
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(css='https://huggingface.co/spaces/xp3857/text-to-image/raw/main/css.css') 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()