diffusion / app.py
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Add ToMe
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import time
import gradio as gr
from generate import generate
DEFAULT_NEGATIVE_PROMPT = "<fast_negative>"
# 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()
# 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, Error=gr.Error)
end = time.perf_counter()
diff = end - start
gr.Info(f"Generated {len(images)} images in {diff:.2f}s")
return images
with gr.Blocks(
head=read_file("./partials/head.html"),
css="./app.css",
js="./app.js",
theme=gr.themes.Default(
# colors
neutral_hue=gr.themes.colors.gray,
primary_hue=gr.themes.colors.orange,
secondary_hue=gr.themes.colors.blue,
# sizing
text_size=gr.themes.sizes.text_md,
radius_size=gr.themes.sizes.radius_sm,
spacing_size=gr.themes.sizes.spacing_md,
# fonts
font=[gr.themes.GoogleFont("Inter"), *SANS_FONTS],
font_mono=[gr.themes.GoogleFont("Ubuntu Mono"), *MONO_FONTS],
).set(
layout_gap="8px",
block_shadow="0 0 #0000",
block_shadow_dark="0 0 #0000",
block_background_fill=gr.themes.colors.gray.c50,
block_background_fill_dark=gr.themes.colors.gray.c900,
),
) as demo:
gr.HTML(read_file("./partials/intro.html"))
with gr.Group():
output_images = gr.Gallery(
elem_classes=["gallery"],
show_share_button=False,
interactive=False,
show_label=False,
label="Output",
format="png",
columns=2,
)
prompt = gr.Textbox(
placeholder="corgi, at the beach, cute, 8k",
show_label=False,
label="Prompt",
value=None,
lines=2,
)
with gr.Row():
generate_btn = gr.Button("Generate", variant="primary", scale=6, elem_classes=[])
random_btn = gr.Button(
elem_classes=["icon-button"],
variant="secondary",
elem_id="random",
min_width=0,
value="🎲",
scale=1,
)
clear_btn = gr.ClearButton(
elem_classes=["icon-button"],
components=[output_images],
variant="secondary",
elem_id="clear",
min_width=0,
value="🗑️",
scale=1,
)
with gr.Accordion(
elem_classes=["accordion"],
elem_id="menu",
label="Open menu",
open=False,
):
with gr.Tabs():
with gr.TabItem("⚙️ Settings"):
with gr.Group():
negative_prompt = gr.Textbox(
label="Negative Prompt",
value=DEFAULT_NEGATIVE_PROMPT,
placeholder="",
lines=2,
)
with gr.Row():
num_images = gr.Dropdown(
choices=list(range(1, 9)),
filterable=False,
label="Images",
value=1,
scale=1,
)
width = gr.Slider(
label="Width",
minimum=256,
maximum=1024,
value=448,
step=32,
scale=2,
)
height = gr.Slider(
label="Height",
minimum=256,
maximum=1024,
value=576,
step=32,
scale=2,
)
with gr.Row():
guidance_scale = gr.Slider(
label="Guidance Scale",
minimum=1.0,
maximum=15.0,
value=7,
step=0.1,
)
inference_steps = gr.Slider(
label="Inference Steps",
minimum=1,
maximum=50,
value=30,
step=1,
)
with gr.Row():
model = gr.Dropdown(
value="Lykon/dreamshaper-8",
label="Model",
scale=2,
choices=[
"fluently/Fluently-v4",
"Linaqruf/anything-v3-1",
"Lykon/dreamshaper-8",
"prompthero/openjourney-v4",
"runwayml/stable-diffusion-v1-5",
"SG161222/Realistic_Vision_V5.1_Novae",
],
)
scheduler = gr.Dropdown(
elem_id="scheduler",
label="Scheduler",
value="DEIS 2M",
scale=2,
choices=[
"DEIS 2M",
"DPM++ 2M",
"DPM2 a",
"Euler a",
"Heun",
"LMS",
"PNDM",
],
)
seed = gr.Number(label="Seed", value=42, scale=1)
with gr.Row():
use_karras = gr.Checkbox(
elem_classes=["checkbox"],
label="Karras σ",
value=True,
scale=1,
)
increment_seed = gr.Checkbox(
elem_classes=["checkbox"],
label="Autoincrement",
value=True,
scale=4,
)
with gr.TabItem("🛠️ Advanced"):
with gr.Group():
with gr.Row():
deepcache_interval = gr.Slider(
label="DeepCache Interval",
minimum=1,
maximum=4,
value=2,
step=1,
)
tgate_step = gr.Slider(
label="T-GATE Step",
minimum=0,
maximum=50,
value=20,
step=1,
)
tome_ratio = gr.Slider(
label="ToMe Ratio",
minimum=0.0,
maximum=1.0,
value=0.0,
step=0.01,
)
with gr.Row():
use_taesd = gr.Checkbox(
elem_classes=["checkbox"],
label="Tiny VAE",
value=False,
scale=1,
)
use_clip_skip = gr.Checkbox(
elem_classes=["checkbox"],
label="Clip skip",
value=False,
scale=1,
)
truncate_prompts = gr.Checkbox(
elem_classes=["checkbox"],
label="Truncate prompts",
value=False,
scale=3,
)
with gr.TabItem("ℹ️ Info"):
gr.Markdown(read_file("info.md"), elem_classes=["markdown"])
# update the random seed using JavaScript
random_btn.click(None, outputs=[seed], js="() => Math.floor(Math.random() * 2**32)")
# ensure correct argument order
generate_btn.click(
generate_btn_click,
api_name="generate",
concurrency_limit=5,
outputs=[output_images],
inputs=[
prompt,
negative_prompt,
seed,
model,
scheduler,
width,
height,
guidance_scale,
inference_steps,
num_images,
use_karras,
use_taesd,
use_clip_skip,
truncate_prompts,
increment_seed,
deepcache_interval,
tgate_step,
tome_ratio,
],
)
# https://www.gradio.app/docs/gradio/interface#interface-queue
demo.queue().launch(
{
"server_name": "0.0.0.0",
"server_port": 7860,
}
)