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91a9f46 a96c23b a16025e 91a9f46 ab8c880 91a9f46 a96c23b 029f729 92b9f01 57eba6f 96f13be 92b9f01 a16025e 91a9f46 96f13be 92b9f01 96f13be 9fbf6ac 96f13be 5f4d01b a96c23b a16025e 91a9f46 | 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 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 | #!/usr/bin/env python
from __future__ import annotations
import os
import pathlib
import shlex
import subprocess
import gradio as gr
if os.getenv('SYSTEM') == 'spaces':
with open('patch') as f:
subprocess.run(shlex.split('patch -p1'), stdin=f, cwd='ControlNet')
base_url = 'https://huggingface.co/lllyasviel/ControlNet/resolve/main/annotator/ckpts/'
names = [
'body_pose_model.pth',
'dpt_hybrid-midas-501f0c75.pt',
'hand_pose_model.pth',
'mlsd_large_512_fp32.pth',
'mlsd_tiny_512_fp32.pth',
'network-bsds500.pth',
'upernet_global_small.pth',
]
for name in names:
command = f'wget https://huggingface.co/lllyasviel/ControlNet/resolve/main/annotator/ckpts/{name} -O {name}'
out_path = pathlib.Path(f'ControlNet/annotator/ckpts/{name}')
if out_path.exists():
continue
subprocess.run(shlex.split(command), cwd='ControlNet/annotator/ckpts/')
from gradio_canny2image import create_demo as create_demo_canny
from gradio_depth2image import create_demo as create_demo_depth
from gradio_fake_scribble2image import create_demo as create_demo_fake_scribble
from gradio_hed2image import create_demo as create_demo_hed
from gradio_hough2image import create_demo as create_demo_hough
from gradio_normal2image import create_demo as create_demo_normal
from gradio_pose2image import create_demo as create_demo_pose
from gradio_scribble2image import create_demo as create_demo_scribble
from gradio_scribble2image_interactive import \
create_demo as create_demo_scribble_interactive
from gradio_seg2image import create_demo as create_demo_seg
from model import Model
from model import array_of_photos
MAX_IMAGES = 1
model = Model()
def shima(name):
print(array_of_photos)
print("shimaaa this is !!!!!!", len(array_of_photos))
print("type", type(array_of_photos))
print("type of last", type(array_of_photos[-1]))
return array_of_photos
with gr.Blocks(css='style.css') as demo:
with gr.TabItem('Canny'):
create_demo_canny(model.process_canny, max_images=MAX_IMAGES)
with gr.TabItem('Hough'):
with gr.Row():
with gr.Column(elem_id='33'):
input = gr.Image()
shima_but = gr.Button('shiii')
gr.Textbox
with gr.Column():
output = gr.Gallery()
shima_but.click(shima, input, [output])
demo.queue(api_open=False).launch()
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