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from pydantic import BaseModel, conint
from dataclasses import field
from typing import Optional, List, Dict, Any
from pathlib import Path
import random
class RequetModelClass(BaseModel):
pass
class Txt2ImgRequest(RequetModelClass):
prompt: Optional[str] = ""
negative_prompt: Optional[str] = ""
styles: List[str] = []
seed: int = random.randint(0, 4294967295)
subseed: int = random.randint(0, 4294967295)
subseed_strength: float = 0
seed_resize_from_h: int = -1
seed_resize_from_w: int = -1
sampler_name: str = "Euler a"
batch_size: int = 1
n_iter: int = 1
steps: int = 20
cfg_scale: float = 7
width: int = 512
height: int = 512
restore_faces: bool = False
tiling: bool = False
do_not_save_samples: bool = False
do_not_save_grid: bool = False
eta: float = 0
denoising_strength: float = 1
s_min_uncond: float = 0
s_churn: float = 0
s_tmax: float = 0
s_tmin: float = 0
s_noise: float = 0
override_settings: Dict[str, Any] = {}
override_settings_restore_afterwards: bool = False
refiner_checkpoint: str = ""
refiner_switch_at: int = 0
disable_extra_networks: bool = False
comments: Dict[str, Any] = {}
enable_hr: bool = False
firstphase_width: int = 0
firstphase_height: int = 0
hr_scale: float = 2
hr_upscaler: str = ""
hr_second_pass_steps: int = 10
hr_resize_x: int = 0
hr_resize_y: int = 0
hr_checkpoint_name: str = ""
hr_sampler_name: str = ""
hr_prompt: str = ""
hr_negative_prompt: str = ""
sampler_index: str = "Euler a"
script_name: str = ""
script_args: List[Any] = []
send_images: bool = True
save_images: bool = True
alwayson_scripts: Dict[str, Any] = {}
scheduler: str = "Automatic"
class Img2ImgRequest(RequetModelClass):
prompt: Optional[str] = ""
negative_prompt: Optional[str] = ""
styles: List[str] = []
seed: int = random.randint(0, 4294967295)
subseed: int = random.randint(0, 4294967295)
subseed_strength: float = 0
seed_resize_from_h: int = -1
seed_resize_from_w: int = -1
sampler_name: str = "Euler a"
batch_size: int = 1
n_iter: int = 1
steps: int = 50
cfg_scale: float = 7
width: int = 512
height: int = 512
restore_faces: bool = False
tiling: bool = False
do_not_save_samples: bool = False
do_not_save_grid: bool = False
eta: float = 0
denoising_strength: float = 0.75
s_min_uncond: float = 0
s_churn: float = 0
s_tmax: float = 0
s_tmin: float = 0
s_noise: float = 0
override_settings: Dict[str, Any] = {}
override_settings_restore_afterwards: bool = False
refiner_checkpoint: str = ""
refiner_switch_at: int = 0
disable_extra_networks: bool = False
comments: Dict[str, Any] = {}
init_images: List[str] = [""]
resize_mode: int = 0
image_cfg_scale: float = 0
mask: str = None
mask_blur_x: int = 4
mask_blur_y: int = 4
mask_blur: int = 0
inpainting_fill: int = 0
inpaint_full_res: bool = True
inpaint_full_res_padding: int = 0
inpainting_mask_invert: int = 0
initial_noise_multiplier: float = 0
latent_mask: str = ""
sampler_index: str = "Euler a"
include_init_images: bool = False
script_name: str = ""
script_args: List[Any] = []
send_images: bool = True
save_images: bool = True
alwayson_scripts: Dict[str, Any] = {}
scheduler: str = "Automatic"
# 以下为拓展
class TaggerRequest(RequetModelClass):
image: str = '',
model: Optional[str] = 'wd14-vit-v2'
threshold: Optional[float] = 0.35,
exclude_tags: Optional[List[str]] = []
class TopazAiRequest(BaseModel):
image: Optional[str] = None
input_folder: Optional[str or Path]
output_folder: Optional[str] = None
overwrite: Optional[bool] = False
recursive: Optional[bool] = False
format: Optional[str] = "preserve" # 可选值: jpg, jpeg, png, tif, tiff, dng, preserve
quality: Optional[conint(ge=0, le=100)] = 95 # JPEG 质量，0到100之间
compression: Optional[conint(ge=0, le=10)] = 2 # PNG 压缩，0到10之间
bit_depth: Optional[conint(strict=True, ge=8, le=16)] = 16 # TIFF 位深度，8或16
tiff_compression: Optional[str] = "zip" # 可选值: none, lzw, zip
show_settings: Optional[bool] = False
skip_processing: Optional[bool] = False
verbose: Optional[bool] = False
upscale: Optional[bool] = None
noise: Optional[bool] = None
sharpen: Optional[bool] = None
lighting: Optional[bool] = None
color: Optional[bool] = None
class SetConfigRequest(BaseModel):
class Config:
extra = "allow"
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