| 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() |
|
|
