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import os
import subprocess
import sys
import tempfile
import gradio as gr
from PIL import Image
sys.path.append('/home/user/app/code')
# set up diffvg
# os.system('git clone https://github.com/BachiLi/diffvg.git')
os.chdir('diffvg')
os.system('git submodule update --init --recursive')
os.system('python setup.py install --user')
sys.path.append("/home/user/.local/lib/python3.10/site-packages/diffvg-0.0.1-py3.10-linux-x86_64.egg")
print("diffvg installed.")
os.chdir('/home/user/app')
def process_images(prompt, num_paths, token_index, seed, optimize_width=False, optimize_color=False):
with tempfile.TemporaryDirectory() as tmpdirname:
command = [
"python", "svg_render.py",
"x=diffsketcher",
f"prompt={prompt}",
f"x.num_paths={num_paths}",
f"x.token_ind={token_index}",
f"seed={seed}",
f"x.optim_width={optimize_width}",
f"x.optim_rgba={optimize_color}",
"x.optim_opacity=False",
]
result = subprocess.run(command, check=True)
if result.returncode == 0:
output_image = Image.open(os.path.join(tmpdirname, "final_render.png"))
return output_image
with gr.Blocks() as demo:
gr.Markdown("# DiffSketcher")
gr.Markdown("DiffSketcher synthesizes **vector sketches** based on **text prompts**.")
li = [
"https://raw.githubusercontent.com/ximinng/DiffSketcher/main/img/cat.svg",
"https://raw.githubusercontent.com/ximinng/DiffSketcher/main/img/rose.svg",
"https://raw.githubusercontent.com/ximinng/DiffSketcher/main/img/elephant.svg",
"https://raw.githubusercontent.com/ximinng/DiffSketcher/main/img/elephant_silhouette.svg",
"https://raw.githubusercontent.com/ximinng/DiffSketcher/main/img/horse_width.svg",
"https://raw.githubusercontent.com/ximinng/DiffSketcher/main/img/horse_rgba.svg",
"https://ximinng.github.io/PyTorch-SVGRender-project/assets/diffsketcher/Sydney_opera.svg",
"https://ximinng.github.io/PyTorch-SVGRender-project/assets/diffsketcher/Sydney_opera_width.svg",
"https://ximinng.github.io/PyTorch-SVGRender-project/assets/diffsketcher/Sydney_opera_width_color.svg",
]
gr.Gallery(li, columns=6)
with gr.Row():
with gr.Column():
text = gr.Textbox(label="prompt")
num_paths = gr.Slider(label="path number", value=96, minimum=1, maximum=500, step=1)
token_index = gr.Textbox(label="token_index", info="CLIP embedding token index. Starting from 1.")
seed = gr.Slider(0, 10000, label="random seed", value=8019)
with gr.Accordion("Selectable Inputs"):
optimize_width = gr.Checkbox(label="optimize stroke width")
optimize_color = gr.Checkbox(label="optimize stroke color")
btn = gr.Button("Synthesize")
with gr.Column():
output = gr.Image(label="output image", height=512)
btn.click(process_images,
inputs=[text, num_paths, token_index, seed, optimize_width, optimize_color],
outputs=[output])
gr.Markdown("## Examples")
gr.Markdown("Here are some config examples. Feel free to try your own prompts!")
gr.Examples(
inputs=[text, num_paths, token_index, seed, optimize_width, optimize_color],
outputs=[output],
fn=process_images,
examples=[
["A photo of Sydney opera house.", 96, 5, 8019, False, False],
["A photo of Sydney opera house.", 96, 5, 8019, True, False],
["A photo of Sydney opera house.", 128, 5, 8019, True, True],
],
)
demo.launch()
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