imlab.extractor_wrapper.Wrapper

class imlab.extractor_wrapper.Wrapper(weight: ~typing.Optional[str] = None, model_type: str = 'yoloV7', image_size: int = 640, model: ~typing.Optional[object] = None, preprocess: callable = <function preprocess>, decode: callable = <function decode>, classes: list = [], model_mod: str = 'use')

Bases: object

Wrapper. Pytorch wrapper

__init__(weight: ~typing.Optional[str] = None, model_type: str = 'yoloV7', image_size: int = 640, model: ~typing.Optional[object] = None, preprocess: callable = <function preprocess>, decode: callable = <function decode>, classes: list = [], model_mod: str = 'use') → None

__init__.

Parameters

• weight (str) –

• model_type (str) –

• image_size (int) –

• model (object) –

• preprocess (callable) –

• decode (callable) –

• classes (list) –

• model_mod (str) –

Return type

None

Methods

__init__([weight, model_type, image_size, ...])	__init__.
norm_input(image)	norm_input.
open_img(image)	open_img.

norm_input(image: object) → FloatTensor

norm_input.

Parameters

image (object) –

Return type

torch.FloatTensor

open_img(image: object) → ndarray

open_img.

Parameters

image (object) –

Return type

np.ndarray