random_sized_crop

RandomSizedCrop

Bases: MultiVariateAlbumentation

Crop a random part of the input and rescale it to some size.

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[str]	The key of masks to be modified (with the same random factors as the image).	None
bbox_in	Optional[str]	The key of a bounding box(es) to be modified (with the same random factors as the image).	None
keypoints_in	Optional[str]	The key of keypoints 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[str]	The key to write the modified masks (defaults to masks_in if None).	None
bbox_out	Optional[str]	The key to write the modified bounding box(es) (defaults to bbox_in if None).	None
keypoints_out	Optional[str]	The key to write the modified keypoints (defaults to keypoints_in if None).	None
bbox_params	Union[BboxParams, str, None]	Parameters defining the type of bounding box ('coco', 'pascal_voc', 'albumentations' or 'yolo').	None
keypoint_params	Union[KeypointParams, str, None]	Parameters defining the type of keypoints ('xy', 'yx', 'xya', 'xys', 'xyas', 'xysa').	None
min_max_height	Tuple[int, int]	Crop size limits.	required
height	int	Height after crop and resize.	required
width	int	Width after crop and resize.	required
w2h_ratio	float	Aspect ratio of crop.	1.0
interpolation	int	flag that is used to specify the interpolation algorithm. Should be one of: cv2.INTER_NEAREST, cv2.INTER_LINEAR, cv2.INTER_CUBIC, cv2.INTER_AREA, cv2.INTER_LANCZOS4.	INTER_LINEAR

Image types

uint8, float32

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

@traceable()
class RandomSizedCrop(MultiVariateAlbumentation):
    """Crop a random part of the input and rescale it to some size.

    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 key of masks to be modified (with the same random factors as the image).
        bbox_in: The key of a bounding box(es) to be modified (with the same random factors as the image).
        keypoints_in: The key of keypoints 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 key to write the modified masks (defaults to `masks_in` if None).
        bbox_out: The key to write the modified bounding box(es) (defaults to `bbox_in` if None).
        keypoints_out: The key to write the modified keypoints (defaults to `keypoints_in` if None).
        bbox_params: Parameters defining the type of bounding box ('coco', 'pascal_voc', 'albumentations' or 'yolo').
        keypoint_params: Parameters defining the type of keypoints ('xy', 'yx', 'xya', 'xys', 'xyas', 'xysa').
        min_max_height: Crop size limits.
        height: Height after crop and resize.
        width: Width after crop and resize.
        w2h_ratio: Aspect ratio of crop.
        interpolation: flag that is used to specify the interpolation algorithm. Should be one of:
            cv2.INTER_NEAREST, cv2.INTER_LINEAR, cv2.INTER_CUBIC, cv2.INTER_AREA, cv2.INTER_LANCZOS4.

    Image types:
        uint8, float32
    """
    def __init__(self,
                 min_max_height: Tuple[int, int],
                 height: int,
                 width: int,
                 w2h_ratio: float = 1.0,
                 interpolation: int = cv2.INTER_LINEAR,
                 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[str] = None,
                 bbox_in: Optional[str] = None,
                 keypoints_in: Optional[str] = None,
                 image_out: Optional[str] = None,
                 mask_out: Optional[str] = None,
                 masks_out: Optional[str] = None,
                 bbox_out: Optional[str] = None,
                 keypoints_out: Optional[str] = None,
                 bbox_params: Union[BboxParams, str, None] = None,
                 keypoint_params: Union[KeypointParams, str, None] = None):
        super().__init__(
            RandomSizedCropAlb(min_max_height=min_max_height,
                               height=height,
                               width=width,
                               w2h_ratio=w2h_ratio,
                               interpolation=interpolation,
                               always_apply=True),
            image_in=image_in,
            mask_in=mask_in,
            masks_in=masks_in,
            bbox_in=bbox_in,
            keypoints_in=keypoints_in,
            image_out=image_out,
            mask_out=mask_out,
            masks_out=masks_out,
            bbox_out=bbox_out,
            keypoints_out=keypoints_out,
            bbox_params=bbox_params,
            keypoint_params=keypoint_params,
            mode=mode,
            ds_id=ds_id)