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autocontrast

AutoContrast

Bases: NumpyOp

Adjust image contrast automatically.

This is a wrapper for functionality provided by the PIL library: https://github.com/python-pillow/Pillow/tree/master/src/PIL.

Parameters:

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

Key(s) of images to be modified.

 required
outputs Union[str, Iterable[str]]

Key(s) into which to write the modified 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

Source code in fastestimator/fastestimator/op/numpyop/univariate/autocontrast.py 
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@traceable()
class AutoContrast(NumpyOp):
    """Adjust image contrast automatically.

    This is a wrapper for functionality provided by the PIL library:
    https://github.com/python-pillow/Pillow/tree/master/src/PIL.

    Args:
        inputs: Key(s) of images to be modified.
        outputs: Key(s) into which to write the modified 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
    """
    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__(inputs=inputs, outputs=outputs, mode=mode, ds_id=ds_id)
        self.in_list, self.out_list = True, True

    def set_rua_level(self, magnitude_coef: float) -> None:
        """A method which will be invoked by RUA Op to adjust the augmentation intensity.

        Args:
            magnitude_coef: The desired augmentation intensity (range [0-1]).
        """

    def forward(self, data: List[np.ndarray], state: Dict[str, Any]) -> List[np.ndarray]:
        return [AutoContrast._apply_autocontrast(elem) for elem in data]

    @staticmethod
    def _apply_autocontrast(data: np.ndarray) -> np.ndarray:
        im = Image.fromarray(data)
        im = ImageOps.autocontrast(im)
        return np.array(im)

set_rua_level

A method which will be invoked by RUA Op to adjust the augmentation intensity.

Parameters:

Name Type Description Default
magnitude_coef float

The desired augmentation intensity (range [0-1]).

 required
Source code in fastestimator/fastestimator/op/numpyop/univariate/autocontrast.py 
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def set_rua_level(self, magnitude_coef: float) -> None:
    """A method which will be invoked by RUA Op to adjust the augmentation intensity.

    Args:
        magnitude_coef: The desired augmentation intensity (range [0-1]).
    """