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to_sepia

ToSepia

Bases: ImageOnlyAlbumentation

Convert an RGB image to sepia.

Parameters:

Name Type Description Default
inputs Union[str, Iterable[str]]

Key(s) of images to be converted to sepia.

 required
outputs Union[str, Iterable[str]]

Key(s) into which to write the sepia images.

 required
mode Union[None, str, Iterable[str]]

What mode(s) to execute this Op in. For example, "train", "eval", "test", or "infer". To execute regardless of mode, pass None. To execute in all modes except for a particular one, you can pass an argument like "!infer" or "!train".

 None
ds_id Union[None, str, Iterable[str]]

What dataset id(s) to execute this Op in. To execute regardless of ds_id, pass None. To execute in all ds_ids except for a particular one, you can pass an argument like "!ds1".

 None
Image types

uint8, float32

Source code in fastestimator/fastestimator/op/numpyop/univariate/to_sepia.py 
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@traceable()
class ToSepia(ImageOnlyAlbumentation):
    """Convert an RGB image to sepia.

    Args:
        inputs: Key(s) of images to be converted to sepia.
        outputs: Key(s) into which to write the sepia images.
        mode: What mode(s) to execute this Op in. For example, "train", "eval", "test", or "infer". To execute
            regardless of mode, pass None. To execute in all modes except for a particular one, you can pass an argument
            like "!infer" or "!train".
        ds_id: What dataset id(s) to execute this Op in. To execute regardless of ds_id, pass None. To execute in all
            ds_ids except for a particular one, you can pass an argument like "!ds1".

    Image types:
        uint8, float32
    """
    def __init__(self,
                 inputs: Union[str, Iterable[str]],
                 outputs: Union[str, Iterable[str]],
                 mode: Union[None, str, Iterable[str]] = None,
                 ds_id: Union[None, str, Iterable[str]] = None):
        super().__init__(ToSepiaAlb(always_apply=True), inputs=inputs, outputs=outputs, mode=mode, ds_id=ds_id)