diffusion / demo.py
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import time
import gradio as gr
from generate import generate
# base font stacks
mono_fonts = ["monospace"]
sans_fonts = [
"sans-serif",
"Apple Color Emoji",
"Segoe UI Emoji",
"Segoe UI Symbol",
"Noto Color Emoji",
]
def read_file(path: str) -> str:
with open(path, "r", encoding="utf-8") as file:
return file.read()
def toggle_json(checkbox: gr.Checkbox, json: gr.JSON) -> None:
json.visible = checkbox
# don't request a GPU if input is bad
def generate_btn_click(*args, **kwargs):
start = time.perf_counter()
if "prompt" in kwargs:
prompt = kwargs.get("prompt")
elif len(args) > 0:
prompt = args[0]
else:
prompt = None
if prompt is None or prompt.strip() == "":
raise gr.Error("You must enter a prompt")
images = generate(*args, **kwargs)
end = time.perf_counter()
diff = end - start
gr.Info(f"Generated {len(images)} images in {diff:.2f}s")
return images
with gr.Blocks(
css="./demo.css",
js="./demo.js",
theme=gr.themes.Default(
# colors
primary_hue=gr.themes.colors.orange,
secondary_hue=gr.themes.colors.blue,
neutral_hue=gr.themes.colors.gray,
# sizing
text_size=gr.themes.sizes.text_md,
spacing_size=gr.themes.sizes.spacing_md,
radius_size=gr.themes.sizes.radius_sm,
# fonts
font=[gr.themes.GoogleFont("Inter"), *sans_fonts],
font_mono=[gr.themes.GoogleFont("Ubuntu Mono"), *mono_fonts],
).set(
block_background_fill=gr.themes.colors.gray.c50,
block_background_fill_dark=gr.themes.colors.gray.c900,
block_border_width="0px",
block_border_width_dark="0px",
block_shadow="0 0 #0000",
block_shadow_dark="0 0 #0000",
block_title_text_weight=500,
form_gap_width="0px",
section_header_text_weight=500,
),
) as demo:
gr.HTML(read_file("header.html"))
output_images = gr.Gallery(
height=320,
label="Output",
show_label=False,
columns=4,
interactive=False,
elem_id="gallery",
)
with gr.Group():
prompt = gr.Textbox(
label="Prompt",
show_label=False,
lines=2,
placeholder="corgi, at the beach, cute",
value=None,
elem_id="prompt",
)
generate_btn = gr.Button("Generate", variant="primary", elem_classes=[])
with gr.Accordion(
label="Menu",
open=True,
elem_id="menu",
elem_classes=["accordion"],
):
with gr.Tabs(elem_id="menu-tabs"):
with gr.TabItem("⚙️ Settings"):
with gr.Group():
negative_prompt = gr.Textbox(
label="Negative Prompt",
lines=1,
placeholder="ugly",
value="",
)
with gr.Row():
num_images = gr.Dropdown(
label="Images",
choices=[1, 2, 3, 4],
value=1,
filterable=False,
)
aspect_ratio = gr.Dropdown(
label="Aspect Ratio",
choices=["1:1", "4:3", "3:4", "16:9", "9:16"],
value="1:1",
filterable=False,
)
with gr.Row():
guidance_scale = gr.Slider(
label="Guidance Scale",
minimum=1.0,
maximum=15.0,
step=0.1,
value=7,
)
inference_steps = gr.Slider(
label="Inference Steps",
minimum=1,
maximum=50,
step=1,
value=30,
)
with gr.Column():
seed = gr.Number(label="Seed", value=0)
with gr.Row():
random_seed_btn = gr.Button(
"🎲 Random",
variant="secondary",
size="sm",
scale=1,
)
increment_seed = gr.Checkbox(
label="Autoincrement",
value=True,
scale=8,
elem_classes=["checkbox"],
elem_id="increment-seed",
)
with gr.TabItem("🧠 Model"):
model = gr.Dropdown(
label="Model",
choices=[
"fluently/Fluently-v4",
"Lykon/dreamshaper-8",
"prompthero/openjourney-v4",
"runwayml/stable-diffusion-v1-5",
"SG161222/Realistic_Vision_V5.1_Novae",
],
value="Lykon/dreamshaper-8",
)
scheduler = gr.Dropdown(
label="Scheduler",
choices=[
"DEIS 2M",
"DPM++ 2M",
"DPM2 a",
"Euler a",
"Heun",
"LMS",
"PNDM",
],
value="DEIS 2M",
elem_id="scheduler",
)
use_karras = gr.Checkbox(
label="Karras σ",
value=True,
elem_classes=["checkbox"],
)
with gr.TabItem("ℹ️ About", elem_id="about"):
gr.Markdown(read_file("about.md"))
# update the random seed using JavaScript
random_seed_btn.click(None, outputs=[seed], js="() => Math.floor(Math.random() * 2**32)")
generate_btn.click(
generate_btn_click,
api_name="generate",
outputs=[output_images],
inputs=[
prompt,
negative_prompt,
seed,
model,
scheduler,
aspect_ratio,
guidance_scale,
inference_steps,
use_karras,
num_images,
increment_seed,
],
)
# https://www.gradio.app/docs/gradio/interface#interface-queue
demo.queue().launch(
{
"server_name": "0.0.0.0",
"server_port": 7860,
}
)