random_resized_crop

RandomResizedCrop

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
height	int	Height after crop and resize.	required
width	int	Width after crop and resize.	required
scale	Tuple[float, float]	Range of size of the origin size cropped.	(0.08, 1.0)
ratio	Tuple[float, float]	Range of aspect ratio of the origin aspect ratio cropped.	(0.75, 4 / 3)
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_resized_crop.py

@traceable()
class RandomResizedCrop(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').
        height: Height after crop and resize.
        width: Width after crop and resize.
        scale: Range of size of the origin size cropped.
        ratio: Range of aspect ratio of the origin aspect ratio cropped.
        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,
                 height: int,
                 width: int,
                 scale: Tuple[float, float] = (0.08, 1.0),
                 ratio: Tuple[float, float] = (0.75, 4 / 3),
                 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__(
            RandomResizedCropAlb(height=height,
                                 width=width,
                                 scale=scale,
                                 ratio=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)