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from typing import Optional, Any
from enum import Enum
from pydantic import BaseModel
from constants import LCM_DEFAULT_MODEL, LCM_DEFAULT_MODEL_OPENVINO
class LCMLora(BaseModel):
base_model_id: str = "Lykon/dreamshaper-8"
lcm_lora_id: str = "latent-consistency/lcm-lora-sdv1-5"
class DiffusionTask(str, Enum):
"""Diffusion task types"""
text_to_image = "text_to_image"
image_to_image = "image_to_image"
class LCMDiffusionSetting(BaseModel):
lcm_model_id: str = LCM_DEFAULT_MODEL
openvino_lcm_model_id: str = LCM_DEFAULT_MODEL_OPENVINO
use_offline_model: bool = False
use_lcm_lora: bool = False
lcm_lora: Optional[LCMLora] = LCMLora()
use_tiny_auto_encoder: bool = False
use_openvino: bool = False
prompt: str = ""
negative_prompt: str = ""
init_image: Any = None
strength: Optional[float] = 0.6
image_height: Optional[int] = 512
image_width: Optional[int] = 512
inference_steps: Optional[int] = 1
guidance_scale: Optional[float] = 1
number_of_images: Optional[int] = 1
seed: Optional[int] = 123123
use_seed: bool = False
use_safety_checker: bool = False
diffusion_task: str = DiffusionTask.text_to_image.value
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