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#!/usr/bin/env python
from __future__ import annotations
import gradio as gr
import numpy as np
from model import Model
DESCRIPTION = "# [AvantGAN](https://github.com/ellemcfarlane/AvantGAN)"
def get_sample_image_url(name: str) -> str:
sample_image_dir = "https://huggingface.co/spaces/ellemac/avantGAN/resolve/main/samples"
return f"{sample_image_dir}/{name}.png"
def get_sample_image_markdown(name: str) -> str:
url = get_sample_image_url(name)
size = 128 if ("stylegan3" in name or "original" in name) else 64
return f"""
- size: {size}x{size}
"""
model = Model()
with gr.Blocks(css="style.css") as demo:
gr.Markdown(DESCRIPTION)
with gr.Tabs():
with gr.TabItem("App"):
with gr.Row():
with gr.Column():
model_name = gr.Dropdown(
label="Model", choices=list(model.MODEL_DICT.keys()), value="stylegan3-abstract"
)
seed = gr.Slider(label="Seed", minimum=0, maximum=np.iinfo(np.uint32).max, step=1, value=0)
run_button = gr.Button()
with gr.Column():
result = gr.Image(label="Result", elem_id="result", width=300, height=300)
with gr.TabItem("Sample Images"):
with gr.Row():
model_name2 = gr.Dropdown(
[
"stylegan3-abstract",
"stylegan3-high-fidelity",
"ada-dcgan",
"original-training-data",
],
value="stylegan3-abstract",
label="Model",
)
with gr.Row():
text = get_sample_image_markdown(model_name2.value)
sample_images = gr.Markdown(text)
run_button.click(
fn=model.set_model_and_generate_image,
inputs=[
model_name,
seed,
],
outputs=result,
api_name="run",
)
model_name2.change(
fn=get_sample_image_markdown,
inputs=model_name2,
outputs=sample_images,
queue=False,
api_name=False,
)
if __name__ == "__main__":
demo.queue(max_size=20).launch()
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