crop_and_pad

CropAndPad

Bases: MultiVariateAlbumentation

Crop and pad images by pixel amounts or fractions of image sizes.

Parameters:

Name	Type	Description	Default
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_in	Optional[str]	The key of an image to be modified.	None
mask_in	Optional[str]	The key of a mask to be modified (with the same random factors as the image).	None
masks_in	Optional[Iterable[str]]	The list of mask keys to be modified (with the same random factors as the image).	None
image_out	Optional[str]	The key to write the modified image (defaults to image_in if None).	None
mask_out	Optional[str]	The key to write the modified mask (defaults to mask_in if None).	None
masks_out	Optional[Iterable[str]]	The list of keys to write the modified masks (defaults to masks_in if None).	None
px	Union[None, int, Tuple[int, int]]	The number of pixels to crop (negative values) or pad (positive values) on each side of the image. Either this or the parameter percent may be set, not both at the same time.	None
percent	Union[None, float, Tuple[float, float]]	The number of pixels to crop (negative values) or pad (positive values) on each side of the image given as a fraction of the image height/width.	None
pad_mode	Union[int, str]	OpenCV border mode.	'constant'
pad_cval	Union[int, Tuple[float], List[int]]	The constant value to use if the pad mode is BORDER_CONSTANT. If a tuple of two number s and at least one of them is a float, then a random number will be uniformly sampled per image from the continuous interval [a, b] and used as the value. If both number s are int s, the interval is discrete. If a list of number, then a random value will be chosen from the elements of the list and used as the value.	0
pad_cval_mask	Union[None, int, Tuple[float], List[int]]	Same as pad_cval but only for masks.	None
interpolation	str	flag that is used to specify the interpolation algorithm	'bilinear'
keep_size	bool	Whether to keep the same size as original image.	True

Image types

uint8, float32

Source code in fastestimator/fastestimator/op/numpyop/multivariate/crop_and_pad.py

@traceable()
class CropAndPad(MultiVariateAlbumentation):
    """Crop and pad images by pixel amounts or fractions of image sizes.

    Args:
        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_in: The key of an image to be modified.
        mask_in: The key of a mask to be modified (with the same random factors as the image).
        masks_in: The list of mask keys to be modified (with the same random factors as the image).
        image_out: The key to write the modified image (defaults to `image_in` if None).
        mask_out: The key to write the modified mask (defaults to `mask_in` if None).
        masks_out: The list of keys to write the modified masks (defaults to `masks_in` if None).
        px: The number of pixels to crop (negative values) or pad (positive values) on each side of the image.
            Either this or the parameter percent may be set, not both at the same time.
        percent: The number of pixels to crop (negative values) or pad (positive values) on each side of the image given
             as a fraction of the image height/width.
        pad_mode: OpenCV border mode.
        pad_cval: The constant value to use if the pad mode is BORDER_CONSTANT.  If a tuple of two number s and at least
             one of them is a float, then a random number will be uniformly sampled per image from the continuous
             interval [a, b] and used as the value. If both number s are int s, the interval is discrete. If a list of
             number, then a random value will be chosen from the elements of the list and used as the value.
        pad_cval_mask: Same as pad_cval but only for masks.
        interpolation: flag that is used to specify the interpolation algorithm
        keep_size: Whether to keep the same size as original image.

    Image types:
        uint8, float32
    """
    def __init__(self,
                 px: Union[None, int, Tuple[int, int]] = None,
                 percent: Union[None, float, Tuple[float, float]] = None,
                 pad_mode: Union[int, str] = 'constant',
                 pad_cval: Union[int, Tuple[float], List[int]] = 0,
                 pad_cval_mask: Union[None, int, Tuple[float], List[int]] = None,
                 keep_size: bool = True,
                 interpolation: str = 'bilinear',
                 mode: Union[None, str, Iterable[str]] = None,
                 ds_id: Union[None, str, Iterable[str]] = None,
                 image_in: Optional[str] = None,
                 mask_in: Optional[str] = None,
                 masks_in: Optional[Iterable[str]] = None,
                 image_out: Optional[str] = None,
                 mask_out: Optional[str] = None,
                 masks_out: Optional[Iterable[str]] = None):
        order = {'nearest_neighbor': 0, 'bilinear': 1, 'bicubic': 3, 'biquartic': 4, 'biquintic': 5}[interpolation]
        border = {'constant':0, 'reflect':1}[pad_mode]
        if not pad_cval_mask:
            pad_cval_mask = pad_cval
        super().__init__(
            CropAndPadAlb(px=px,
                             percent=percent,
                             pad_mode=border,
                             pad_cval=pad_cval,
                             pad_cval_mask=pad_cval_mask,
                             keep_size=keep_size,
                             interpolation=order,
                             always_apply=True),
            image_in=image_in,
            mask_in=mask_in,
            masks_in=masks_in,
            bbox_in=None,
            keypoints_in=None,
            image_out=image_out,
            mask_out=mask_out,
            masks_out=masks_out,
            bbox_out=None,
            keypoints_out=None,
            bbox_params=None,
            keypoint_params=None,
            mode=mode,
            ds_id=ds_id)