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downscale

Downscale

Bases: ImageOnlyAlbumentation

Decrease image quality by downscaling and then upscaling.

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
scale_min float

Lower bound on the image scale. Should be < 1.

 0.25
scale_max float

Upper bound on the image scale. Should be >= scale_min.

 0.25
interpolation int

cv2 interpolation method.

 INTER_NEAREST
Image types

uint8, float32

Source code in fastestimator/fastestimator/op/numpyop/univariate/downscale.py 
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@traceable()
class Downscale(ImageOnlyAlbumentation):
    """Decrease image quality by downscaling and then upscaling.

    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".
        scale_min: Lower bound on the image scale. Should be < 1.
        scale_max:  Upper bound on the image scale. Should be >= scale_min.
        interpolation: cv2 interpolation method.

    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,
                 scale_min: float = 0.25,
                 scale_max: float = 0.25,
                 interpolation: int = cv2.INTER_NEAREST):
        super().__init__(
            DownscaleAlb(scale_min=scale_min, scale_max=scale_max, interpolation=interpolation, always_apply=True),
            inputs=inputs,
            outputs=outputs,
            mode=mode,
            ds_id=ds_id)