| from enum import Enum
|
| from PIL import Image
|
| from typing import Any, Optional, Union
|
|
|
| from constants import LCM_DEFAULT_MODEL, LCM_DEFAULT_MODEL_OPENVINO
|
| from paths import FastStableDiffusionPaths
|
| from pydantic import BaseModel
|
|
|
|
|
| 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 Lora(BaseModel):
|
| models_dir: str = FastStableDiffusionPaths.get_lora_models_path()
|
| path: Optional[Any] = None
|
| weight: Optional[float] = 0.5
|
| fuse: bool = True
|
| enabled: bool = False
|
|
|
|
|
| class ControlNetSetting(BaseModel):
|
| adapter_path: Optional[str] = None
|
| conditioning_scale: float = 0.5
|
| enabled: bool = False
|
| _control_image: Image = None
|
|
|
|
|
| class GGUFModel(BaseModel):
|
| gguf_models: str = FastStableDiffusionPaths.get_gguf_models_path()
|
| diffusion_path: Optional[str] = None
|
| clip_path: Optional[str] = None
|
| t5xxl_path: Optional[str] = None
|
| vae_path: Optional[str] = None
|
|
|
|
|
| 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
|
| clip_skip: Optional[int] = 1
|
| token_merging: Optional[float] = 0
|
| 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
|
| lora: Optional[Lora] = Lora()
|
| controlnet: Optional[Union[ControlNetSetting, list[ControlNetSetting]]] = None
|
| dirs: dict = {
|
| "controlnet": FastStableDiffusionPaths.get_controlnet_models_path(),
|
| "lora": FastStableDiffusionPaths.get_lora_models_path(),
|
| }
|
| rebuild_pipeline: bool = False
|
| use_gguf_model: bool = False
|
| gguf_model: Optional[GGUFModel] = GGUFModel()
|
|
|
