app.py

from frontend.webui.ui import start_webui
import json
from argparse import ArgumentParser

import constants
from backend.controlnet import controlnet_settings_from_dict
from backend.models.gen_images import ImageFormat
from backend.models.lcmdiffusion_setting import DiffusionTask
from backend.upscale.tiled_upscale import generate_upscaled_image
from constants import APP_VERSION, DEVICE
from frontend.webui.image_variations_ui import generate_image_variations
from models.interface_types import InterfaceType
from paths import FastStableDiffusionPaths
from PIL import Image
from state import get_context, get_settings
from utils import show_system_info
from backend.device import get_device_name

parser = ArgumentParser(description=f"FAST SD CPU {constants.APP_VERSION}")
parser.add_argument(
    "-s",
    "--share",
    action="store_true",
    help="Create sharable link(Web UI)",
    required=False,
)
group = parser.add_mutually_exclusive_group(required=False)
group.add_argument(
    "-g",
    "--gui",
    action="store_true",
    help="Start desktop GUI",
)
group.add_argument(
    "-w",
    "--webui",
    action="store_true",
    help="Start Web UI",
)
group.add_argument(
    "-a",
    "--api",
    action="store_true",
    help="Start Web API server",
)
group.add_argument(
    "-r",
    "--realtime",
    action="store_true",
    help="Start realtime inference UI(experimental)",
)
group.add_argument(
    "-v",
    "--version",
    action="store_true",
    help="Version",
)

parser.add_argument(
    "-b",
    "--benchmark",
    action="store_true",
    help="Run inference benchmark on the selected device",
)
parser.add_argument(
    "--lcm_model_id",
    type=str,
    help="Model ID or path,Default stabilityai/sd-turbo",
    default="stabilityai/sd-turbo",
)
parser.add_argument(
    "--openvino_lcm_model_id",
    type=str,
    help="OpenVINO Model ID or path,Default rupeshs/sd-turbo-openvino",
    default="rupeshs/sd-turbo-openvino",
)
parser.add_argument(
    "--prompt",
    type=str,
    help="Describe the image you want to generate",
    default="",
)
parser.add_argument(
    "--negative_prompt",
    type=str,
    help="Describe what you want to exclude from the generation",
    default="",
)
parser.add_argument(
    "--image_height",
    type=int,
    help="Height of the image",
    default=512,
)
parser.add_argument(
    "--image_width",
    type=int,
    help="Width of the image",
    default=512,
)
parser.add_argument(
    "--inference_steps",
    type=int,
    help="Number of steps,default : 1",
    default=1,
)
parser.add_argument(
    "--guidance_scale",
    type=float,
    help="Guidance scale,default : 1.0",
    default=1.0,
)

parser.add_argument(
    "--number_of_images",
    type=int,
    help="Number of images to generate ,default : 1",
    default=1,
)
parser.add_argument(
    "--seed",
    type=int,
    help="Seed,default : -1 (disabled) ",
    default=-1,
)
parser.add_argument(
    "--use_openvino",
    action="store_true",
    help="Use OpenVINO model",
)

parser.add_argument(
    "--use_offline_model",
    action="store_true",
    help="Use offline model",
)
parser.add_argument(
    "--use_safety_checker",
    action="store_true",
    help="Use safety checker",
)
parser.add_argument(
    "--use_lcm_lora",
    action="store_true",
    help="Use LCM-LoRA",
)
parser.add_argument(
    "--base_model_id",
    type=str,
    help="LCM LoRA base model ID,Default Lykon/dreamshaper-8",
    default="Lykon/dreamshaper-8",
)
parser.add_argument(
    "--lcm_lora_id",
    type=str,
    help="LCM LoRA model ID,Default latent-consistency/lcm-lora-sdv1-5",
    default="latent-consistency/lcm-lora-sdv1-5",
)
parser.add_argument(
    "-i",
    "--interactive",
    action="store_true",
    help="Interactive CLI mode",
)
parser.add_argument(
    "-t",
    "--use_tiny_auto_encoder",
    action="store_true",
    help="Use tiny auto encoder for SD (TAESD)",
)
parser.add_argument(
    "-f",
    "--file",
    type=str,
    help="Input image for img2img mode",
    default="",
)
parser.add_argument(
    "--img2img",
    action="store_true",
    help="img2img mode; requires input file via -f argument",
)
parser.add_argument(
    "--batch_count",
    type=int,
    help="Number of sequential generations",
    default=1,
)
parser.add_argument(
    "--strength",
    type=float,
    help="Denoising strength for img2img and Image variations",
    default=0.3,
)
parser.add_argument(
    "--sdupscale",
    action="store_true",
    help="Tiled SD upscale,works only for the resolution 512x512,(2x upscale)",
)
parser.add_argument(
    "--upscale",
    action="store_true",
    help="EDSR SD upscale ",
)
parser.add_argument(
    "--custom_settings",
    type=str,
    help="JSON file containing custom generation settings",
    default=None,
)
parser.add_argument(
    "--usejpeg",
    action="store_true",
    help="Images will be saved as JPEG format",
)
parser.add_argument(
    "--noimagesave",
    action="store_true",
    help="Disable image saving",
)
parser.add_argument(
    "--lora",
    type=str,
    help="LoRA model full path e.g D:\lora_models\CuteCartoon15V-LiberteRedmodModel-Cartoon-CuteCartoonAF.safetensors",
    default=None,
)
parser.add_argument(
    "--lora_weight",
    type=float,
    help="LoRA adapter weight [0 to 1.0]",
    default=0.5,
)

args = parser.parse_args()

if args.version:
    print(APP_VERSION)
    exit()

# parser.print_help()
show_system_info()
print(f"Using device : {constants.DEVICE}")

if args.webui:
    app_settings = get_settings()
else:
    app_settings = get_settings()

print(f"Found {len(app_settings.lcm_models)} LCM models in config/lcm-models.txt")
print(
    f"Found {len(app_settings.stable_diffsuion_models)} stable diffusion models in config/stable-diffusion-models.txt"
)
print(
    f"Found {len(app_settings.lcm_lora_models)} LCM-LoRA models in config/lcm-lora-models.txt"
)
print(
    f"Found {len(app_settings.openvino_lcm_models)} OpenVINO LCM models in config/openvino-lcm-models.txt"
)

if args.noimagesave:
    app_settings.settings.generated_images.save_image = False
else:
    app_settings.settings.generated_images.save_image = True


print("Starting web UI mode")
start_webui(
    args.share,
)