TDNMdemo / inference_pb2.pyi
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from google.protobuf import descriptor as _descriptor
from google.protobuf import message as _message
from typing import ClassVar as _ClassVar, Optional as _Optional
DESCRIPTOR: _descriptor.FileDescriptor
class HairSwapRequest(_message.Message):
__slots__ = ("face", "shape", "color", "blending", "poisson_iters", "poisson_erosion", "use_cache")
FACE_FIELD_NUMBER: _ClassVar[int]
SHAPE_FIELD_NUMBER: _ClassVar[int]
COLOR_FIELD_NUMBER: _ClassVar[int]
BLENDING_FIELD_NUMBER: _ClassVar[int]
POISSON_ITERS_FIELD_NUMBER: _ClassVar[int]
POISSON_EROSION_FIELD_NUMBER: _ClassVar[int]
USE_CACHE_FIELD_NUMBER: _ClassVar[int]
face: bytes
shape: bytes
color: bytes
blending: str
poisson_iters: int
poisson_erosion: int
use_cache: bool
def __init__(self, face: _Optional[bytes] = ..., shape: _Optional[bytes] = ..., color: _Optional[bytes] = ..., blending: _Optional[str] = ..., poisson_iters: _Optional[int] = ..., poisson_erosion: _Optional[int] = ..., use_cache: bool = ...) -> None: ...
class HairSwapResponse(_message.Message):
__slots__ = ("image",)
IMAGE_FIELD_NUMBER: _ClassVar[int]
image: bytes
def __init__(self, image: _Optional[bytes] = ...) -> None: ...