Files
SHARK-Studio/apps/stable_diffusion/web/index.py
2023-02-01 09:12:45 +05:30

248 lines
9.1 KiB
Python

import os
import sys
from pathlib import Path
if "AMD_ENABLE_LLPC" not in os.environ:
os.environ["AMD_ENABLE_LLPC"] = "1"
if sys.platform == "darwin":
os.environ["DYLD_LIBRARY_PATH"] = "/usr/local/lib"
def resource_path(relative_path):
"""Get absolute path to resource, works for dev and for PyInstaller"""
base_path = getattr(
sys, "_MEIPASS", os.path.dirname(os.path.abspath(__file__))
)
return os.path.join(base_path, relative_path)
import gradio as gr
from PIL import Image
from apps.stable_diffusion.src import (
prompt_examples,
args,
get_available_devices,
)
from apps.stable_diffusion.scripts import txt2img_inf
nodlogo_loc = resource_path("logos/nod-logo.png")
sdlogo_loc = resource_path("logos/sd-demo-logo.png")
demo_css = resource_path("css/sd_dark_theme.css")
with gr.Blocks(title="Stable Diffusion", css=demo_css) as shark_web:
with gr.Row(elem_id="ui_title"):
nod_logo = Image.open(nodlogo_loc)
logo2 = Image.open(sdlogo_loc)
with gr.Row():
with gr.Column(scale=1, elem_id="demo_title_outer"):
gr.Image(
value=nod_logo,
show_label=False,
interactive=False,
elem_id="top_logo",
).style(width=150, height=100)
with gr.Column(scale=5, elem_id="demo_title_outer"):
gr.Image(
value=logo2,
show_label=False,
interactive=False,
elem_id="demo_title",
).style(width=150, height=100)
with gr.Row(elem_id="ui_body"):
with gr.Row():
with gr.Column(scale=1, min_width=600):
with gr.Row():
with gr.Group():
model_id = gr.Dropdown(
label="Model ID",
value="stabilityai/stable-diffusion-2-1-base",
choices=[
"Linaqruf/anything-v3.0",
"prompthero/openjourney",
"wavymulder/Analog-Diffusion",
"stabilityai/stable-diffusion-2-1",
"stabilityai/stable-diffusion-2-1-base",
"CompVis/stable-diffusion-v1-4",
],
)
custom_model_id = gr.Textbox(
placeholder="check here: https://huggingface.co/models eg. runwayml/stable-diffusion-v1-5",
value="",
label="HuggingFace Model ID",
)
with gr.Group():
ckpt_loc = gr.File(
label="Upload checkpoint",
file_types=[".ckpt", ".safetensors"],
)
with gr.Group(elem_id="prompt_box_outer"):
prompt = gr.Textbox(
label="Prompt",
value="cyberpunk forest by Salvador Dali",
lines=1,
elem_id="prompt_box",
)
negative_prompt = gr.Textbox(
label="Negative Prompt",
value="trees, green",
lines=1,
elem_id="prompt_box",
)
with gr.Accordion(label="Advance Options", open=False):
with gr.Row():
scheduler = gr.Dropdown(
label="Scheduler",
value="SharkEulerDiscrete",
choices=[
"DDIM",
"PNDM",
"LMSDiscrete",
"DPMSolverMultistep",
"EulerDiscrete",
"EulerAncestralDiscrete",
"SharkEulerDiscrete",
],
)
batch_size = gr.Slider(
1, 4, value=1, step=1, label="Number of Images"
)
with gr.Row():
height = gr.Slider(
384, 786, value=512, step=8, label="Height"
)
width = gr.Slider(
384, 786, value=512, step=8, label="Width"
)
precision = gr.Radio(
label="Precision",
value="fp16",
choices=[
"fp16",
"fp32",
],
visible=False,
)
max_length = gr.Radio(
label="Max Length",
value=64,
choices=[
64,
77,
],
visible=False,
)
with gr.Row():
steps = gr.Slider(
1, 100, value=50, step=1, label="Steps"
)
guidance_scale = gr.Slider(
0,
50,
value=7.5,
step=0.1,
label="CFG Scale",
)
with gr.Row():
seed = gr.Number(value=-1, precision=0, label="Seed")
available_devices = get_available_devices()
device = gr.Dropdown(
label="Device",
value=available_devices[0],
choices=available_devices,
)
with gr.Row():
random_seed = gr.Button("Randomize Seed")
random_seed.click(
None,
inputs=[],
outputs=[seed],
_js="() => Math.floor(Math.random() * 4294967295)",
)
stable_diffusion = gr.Button("Generate Image")
with gr.Accordion(label="Prompt Examples!", open=False):
ex = gr.Examples(
examples=prompt_examples,
inputs=prompt,
cache_examples=False,
elem_id="prompt_examples",
)
with gr.Column(scale=1, min_width=600):
with gr.Group():
gallery = gr.Gallery(
label="Generated images",
show_label=False,
elem_id="gallery",
).style(grid=[2], height="auto")
std_output = gr.Textbox(
value="Nothing to show.",
lines=4,
show_label=False,
)
output_dir = args.output_dir if args.output_dir else Path.cwd()
output_dir = Path(output_dir, "generated_imgs")
output_loc = gr.Textbox(
label="Saving Images at",
value=output_dir,
interactive=False,
)
prompt.submit(
txt2img_inf,
inputs=[
prompt,
negative_prompt,
height,
width,
steps,
guidance_scale,
seed,
batch_size,
scheduler,
model_id,
custom_model_id,
ckpt_loc,
precision,
device,
max_length,
],
outputs=[gallery, std_output],
show_progress=args.progress_bar,
)
stable_diffusion.click(
txt2img_inf,
inputs=[
prompt,
negative_prompt,
height,
width,
steps,
guidance_scale,
seed,
batch_size,
scheduler,
model_id,
custom_model_id,
ckpt_loc,
precision,
device,
max_length,
],
outputs=[gallery, std_output],
show_progress=args.progress_bar,
)
shark_web.queue()
shark_web.launch(
share=args.share,
inbrowser=True,
server_name="0.0.0.0",
server_port=args.server_port,
)