InvokeAI/invokeai/app/models/metadata.py
2023-05-24 11:30:47 -04:00

76 lines
2.7 KiB
Python

from typing import Optional
from pydantic import BaseModel, Extra, Field, StrictFloat, StrictInt, StrictStr
class ImageMetadata(BaseModel):
"""
Core generation metadata for an image/tensor generated in InvokeAI.
Also includes any metadata from the image's PNG tEXt chunks.
Generated by traversing the execution graph, collecting the parameters of the nearest ancestors
of a given node.
Full metadata may be accessed by querying for the session in the `graph_executions` table.
"""
class Config:
extra = Extra.allow
"""
This lets the ImageMetadata class accept arbitrary additional fields. The CoreMetadataService
won't add any fields that are not already defined, but other a different metadata service
implementation might.
"""
type: Optional[StrictStr] = Field(
default=None,
description="The type of the ancestor node of the image output node.",
)
positive_conditioning: Optional[StrictStr] = Field(
default=None, description="The positive conditioning."
)
negative_conditioning: Optional[StrictStr] = Field(
default=None, description="The negative conditioning."
)
width: Optional[StrictInt] = Field(
default=None, description="Width of the image/latents in pixels."
)
height: Optional[StrictInt] = Field(
default=None, description="Height of the image/latents in pixels."
)
seed: Optional[StrictInt] = Field(
default=None, description="The seed used for noise generation."
)
cfg_scale: Optional[StrictFloat] = Field(
default=None, description="The classifier-free guidance scale."
)
steps: Optional[StrictInt] = Field(
default=None, description="The number of steps used for inference."
)
scheduler: Optional[StrictStr] = Field(
default=None, description="The scheduler used for inference."
)
model: Optional[StrictStr] = Field(
default=None, description="The model used for inference."
)
strength: Optional[StrictFloat] = Field(
default=None,
description="The strength used for image-to-image/latents-to-latents.",
)
latents: Optional[StrictStr] = Field(
default=None, description="The ID of the initial latents."
)
vae: Optional[StrictStr] = Field(
default=None, description="The VAE used for decoding."
)
unet: Optional[StrictStr] = Field(
default=None, description="The UNet used dor inference."
)
clip: Optional[StrictStr] = Field(
default=None, description="The CLIP Encoder used for conditioning."
)
extra: Optional[StrictStr] = Field(
default=None,
description="Uploaded image metadata, extracted from the PNG tEXt chunk.",
)