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immich/machine-learning/app/schemas.py
renovate[bot] 20be42cec0
chore(deps): update machine-learning (#6302)
* chore(deps): update machine-learning

* fix typing, use new lifespan syntax

* wrap in try / finally

* move log

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Co-authored-by: renovate[bot] <29139614+renovate[bot]@users.noreply.github.com>
Co-authored-by: mertalev <101130780+mertalev@users.noreply.github.com>
2024-01-13 05:00:09 +00:00

46 lines
953 B
Python

from enum import StrEnum
from typing import Any, Protocol, TypedDict, TypeGuard
import numpy as np
import numpy.typing as npt
from pydantic import BaseModel
class TextResponse(BaseModel):
__root__: str
class MessageResponse(BaseModel):
message: str
class BoundingBox(TypedDict):
x1: int
y1: int
x2: int
y2: int
class ModelType(StrEnum):
CLIP = "clip"
FACIAL_RECOGNITION = "facial-recognition"
class HasProfiling(Protocol):
profiling: dict[str, float]
class Face(TypedDict):
boundingBox: BoundingBox
embedding: npt.NDArray[np.float32]
imageWidth: int
imageHeight: int
score: float
def has_profiling(obj: Any) -> TypeGuard[HasProfiling]:
return hasattr(obj, "profiling") and isinstance(obj.profiling, dict)
def is_ndarray(obj: Any, dtype: "type[np._DTypeScalar_co]") -> "TypeGuard[npt.NDArray[np._DTypeScalar_co]]":
return isinstance(obj, np.ndarray) and obj.dtype == dtype