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Crop transforms (augmentations.crops.transforms)

class albumentations.augmentations.crops.transforms.BBoxSafeRandomCrop (erosion_rate=0.0, always_apply=False, p=1.0) [view source on GitHub]

Crop a random part of the input without loss of bboxes.

Parameters:

Name Type Description
erosion_rate float

erosion rate applied on input image height before crop.
p float

probability of applying the transform. Default: 1.

Targets: image, mask, bboxes Image types: uint8, float32

class albumentations.augmentations.crops.transforms.CenterCrop (height, width, always_apply=False, p=1.0) [view source on GitHub]

Crop the central part of the input.

Parameters:

Name Type Description
height int

height of the crop.
width int

width of the crop.
p float

probability of applying the transform. Default: 1.

Targets: image, mask, bboxes, keypoints

Image types: uint8, float32

Note: It is recommended to use uint8 images as input. Otherwise the operation will require internal conversion float32 -> uint8 -> float32 that causes worse performance.

class albumentations.augmentations.crops.transforms.Crop (x_min=0, y_min=0, x_max=1024, y_max=1024, always_apply=False, p=1.0) [view source on GitHub]

Crop region from image.

Parameters:

Name Type Description
x_min int

Minimum upper left x coordinate.
y_min int

Minimum upper left y coordinate.
x_max int

Maximum lower right x coordinate.
y_max int

Maximum lower right y coordinate.

Targets: image, mask, bboxes, keypoints

Image types: uint8, float32

class albumentations.augmentations.crops.transforms.CropAndPad (px=None, percent=None, pad_mode=0, pad_cval=0, pad_cval_mask=0, keep_size=True, sample_independently=True, interpolation=1, always_apply=False, p=1.0) [view source on GitHub]

Crop and pad images by pixel amounts or fractions of image sizes. Cropping removes pixels at the sides (i.e. extracts a subimage from a given full image). Padding adds pixels to the sides (e.g. black pixels). This transformation will never crop images below a height or width of 1.

Note: This transformation automatically resizes images back to their original size. To deactivate this, add the parameter keep_size=False.

Parameters:

Name Type Description
px int or tuple

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. * If None, then pixel-based cropping/padding will not be used. * If int, then that exact number of pixels will always be cropped/padded. * If a tuple of two int s with values a and b, then each side will be cropped/padded by a random amount sampled uniformly per image and side from the interval [a, b]. If however sample_independently is set to False, only one value will be sampled per image and used for all sides. * If a tuple of four entries, then the entries represent top, right, bottom, left. Each entry may be a single int (always crop/pad by exactly that value), a tuple of two int s a and b (crop/pad by an amount within [a, b]), a list of int s (crop/pad by a random value that is contained in the list).
percent float or tuple

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. E.g. if this is set to -0.1, the transformation will always crop away 10% of the image's height at both the top and the bottom (both 10% each), as well as 10% of the width at the right and left. Expected value range is (-1.0, inf). Either this or the parameter px may be set, not both at the same time. * If None, then fraction-based cropping/padding will not be used. * If float, then that fraction will always be cropped/padded. * If a tuple of two float s with values a and b, then each side will be cropped/padded by a random fraction sampled uniformly per image and side from the interval [a, b]. If however sample_independently is set to False, only one value will be sampled per image and used for all sides. * If a tuple of four entries, then the entries represent top, right, bottom, left. Each entry may be a single float (always crop/pad by exactly that percent value), a tuple of two float s a and b (crop/pad by a fraction from [a, b]), a list of float s (crop/pad by a random value that is contained in the list).
pad_mode int

OpenCV border mode.
pad_cval number, Sequence[number]

The constant value to use if the pad mode is BORDER_CONSTANT. * If number, then that value will be used. * 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 number, Sequence[number]

Same as pad_cval but only for masks.
keep_size bool

After cropping and padding, the result image will usually have a different height/width compared to the original input image. If this parameter is set to True, then the cropped/padded image will be resized to the input image's size, i.e. the output shape is always identical to the input shape.
sample_independently bool

If False and the values for px/percent result in exactly one probability distribution for all image sides, only one single value will be sampled from that probability distribution and used for all sides. I.e. the crop/pad amount then is the same for all sides. If True, four values will be sampled independently, one per side.
interpolation OpenCV flag

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. Default: cv2.INTER_LINEAR.

Targets: image, mask, bboxes, keypoints

Image types: any

class albumentations.augmentations.crops.transforms.CropNonEmptyMaskIfExists (height, width, ignore_values=None, ignore_channels=None, always_apply=False, p=1.0) [view source on GitHub]

Crop area with mask if mask is non-empty, else make random crop.

Parameters:

Name Type Description
height int

vertical size of crop in pixels
width int

horizontal size of crop in pixels
ignore_values list of int

values to ignore in mask, 0 values are always ignored (e.g. if background value is 5 set ignore_values=[5] to ignore)
ignore_channels list of int

channels to ignore in mask (e.g. if background is a first channel set ignore_channels=[0] to ignore)
p float

probability of applying the transform. Default: 1.0.

Targets: image, mask, bboxes, keypoints

Image types: uint8, float32

class albumentations.augmentations.crops.transforms.RandomCrop (height, width, always_apply=False, p=1.0) [view source on GitHub]

Crop a random part of the input.

Parameters:

Name Type Description
height int

height of the crop.
width int

width of the crop.
p float

probability of applying the transform. Default: 1.

Targets: image, mask, bboxes, keypoints

Image types: uint8, float32

class albumentations.augmentations.crops.transforms.RandomCropFromBorders (crop_left=0.1, crop_right=0.1, crop_top=0.1, crop_bottom=0.1, always_apply=False, p=1.0) [view source on GitHub]

Crop bbox from image randomly cut parts from borders without resize at the end

Parameters:

Name Type Description
crop_left float

single float value in (0.0, 1.0) range. Default 0.1. Image will be randomly cut
crop_right float

single float value in (0.0, 1.0) range. Default 0.1. Image will be randomly cut
crop_top float

singlefloat value in (0.0, 1.0) range. Default 0.1. Image will be randomly cut
crop_bottom float

single float value in (0.0, 1.0) range. Default 0.1. Image will be randomly cut
p float

probability of applying the transform. Default: 1.

Targets: image, mask, bboxes, keypoints

Image types: uint8, float32

class albumentations.augmentations.crops.transforms.RandomCropNearBBox (max_part_shift=(0.3, 0.3), cropping_box_key='cropping_bbox', always_apply=False, p=1.0) [view source on GitHub]

Crop bbox from image with random shift by x,y coordinates

Parameters:

Name Type Description
max_part_shift float, [float, float]

Max shift in height and width dimensions relative to cropping_bbox dimension. If max_part_shift is a single float, the range will be (max_part_shift, max_part_shift). Default (0.3, 0.3).
cropping_box_key str

Additional target key for cropping box. Default cropping_bbox
p float

probability of applying the transform. Default: 1.

Targets: image, mask, bboxes, keypoints

Image types: uint8, float32

Examples:

>>> aug = Compose([RandomCropNearBBox(max_part_shift=(0.1, 0.5), cropping_box_key='test_box')],
>>>              bbox_params=BboxParams("pascal_voc"))
>>> result = aug(image=image, bboxes=bboxes, test_box=[0, 5, 10, 20])

class albumentations.augmentations.crops.transforms.RandomResizedCrop (height, width, scale=(0.08, 1.0), ratio=(0.75, 1.3333333333333333), interpolation=1, always_apply=False, p=1.0) [view source on GitHub]

Torchvision's variant of crop a random part of the input and rescale it to some size.

Parameters:

Name Type Description
height int

height after crop and resize.
width int

width after crop and resize.
scale [float, float]

range of size of the origin size cropped
ratio [float, float]

range of aspect ratio of the origin aspect ratio cropped
interpolation OpenCV flag

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. Default: cv2.INTER_LINEAR.
p float

probability of applying the transform. Default: 1.

Targets: image, mask, bboxes, keypoints

Image types: uint8, float32

class albumentations.augmentations.crops.transforms.RandomSizedBBoxSafeCrop (height, width, erosion_rate=0.0, interpolation=1, always_apply=False, p=1.0) [view source on GitHub]

Crop a random part of the input and rescale it to some size without loss of bboxes.

Parameters:

Name Type Description
height int

height after crop and resize.
width int

width after crop and resize.
erosion_rate float

erosion rate applied on input image height before crop.
interpolation OpenCV flag

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. Default: cv2.INTER_LINEAR.
p float

probability of applying the transform. Default: 1.

Targets: image, mask, bboxes Image types: uint8, float32

class albumentations.augmentations.crops.transforms.RandomSizedCrop (min_max_height, height, width, w2h_ratio=1.0, interpolation=1, always_apply=False, p=1.0) [view source on GitHub]

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

Parameters:

Name Type Description
min_max_height [int, int]

crop size limits.
height int

height after crop and resize.
width int

width after crop and resize.
w2h_ratio float

aspect ratio of crop.
interpolation OpenCV flag

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. Default: cv2.INTER_LINEAR.
p float

probability of applying the transform. Default: 1.

Targets: image, mask, bboxes, keypoints

Image types: uint8, float32