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Geometric transforms (augmentations.geometric.transforms)

class albumentations.augmentations.geometric.transforms.ElasticTransform (alpha=1, sigma=50, alpha_affine=50, interpolation=1, border_mode=4, value=None, mask_value=None, always_apply=False, approximate=False, p=0.5) [view source on GitHub]

Elastic deformation of images as described in [Simard2003]_ (with modifications). Based on https://gist.github.com/erniejunior/601cdf56d2b424757de5

.. [Simard2003] Simard, Steinkraus and Platt, "Best Practices for Convolutional Neural Networks applied to Visual Document Analysis", in Proc. of the International Conference on Document Analysis and Recognition, 2003.

Parameters:

Name Type Description
alpha float
sigma float

Gaussian filter parameter.
alpha_affine float

The range will be (-alpha_affine, alpha_affine)
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.
border_mode OpenCV flag

flag that is used to specify the pixel extrapolation method. Should be one of: cv2.BORDER_CONSTANT, cv2.BORDER_REPLICATE, cv2.BORDER_REFLECT, cv2.BORDER_WRAP, cv2.BORDER_REFLECT_101. Default: cv2.BORDER_REFLECT_101
value int, float, list of ints, list of float

padding value if border_mode is cv2.BORDER_CONSTANT.
mask_value int, float, list of ints, list of float

padding value if border_mode is cv2.BORDER_CONSTANT applied for masks.
approximate boolean

Whether to smooth displacement map with fixed kernel size. Enabling this option gives ~2X speedup on large images.

Targets: image, mask

Image types: uint8, float32

class albumentations.augmentations.geometric.transforms.Perspective (scale=(0.05, 0.1), keep_size=True, pad_mode=0, pad_val=0, mask_pad_val=0, fit_output=False, interpolation=1, always_apply=False, p=0.5) [view source on GitHub]

Perform a random four point perspective transform of the input.

Parameters:

Name Type Description
scale float or [float, float]

standard deviation of the normal distributions. These are used to sample the random distances of the subimage's corners from the full image's corners. If scale is a single float value, the range will be (0, scale). Default: (0.05, 0.1).
keep_size bool

Whether to resize image’s back to their original size after applying the perspective transform. If set to False, the resulting images may end up having different shapes and will always be a list, never an array. Default: True
pad_mode OpenCV flag

OpenCV border mode.
pad_val int, float, list of int, list of float

padding value if border_mode is cv2.BORDER_CONSTANT. Default: 0
mask_pad_val int, float, list of int, list of float

padding value for mask if border_mode is cv2.BORDER_CONSTANT. Default: 0
fit_output bool

If True, the image plane size and position will be adjusted to still capture the whole image after perspective transformation. (Followed by image resizing if keep_size is set to True.) Otherwise, parts of the transformed image may be outside of the image plane. This setting should not be set to True when using large scale values as it could lead to very large images. Default: False
p float

probability of applying the transform. Default: 0.5.

Targets: image, mask, keypoints, bboxes

Image types: uint8, float32

class albumentations.augmentations.geometric.transforms.ShiftScaleRotate (shift_limit=0.0625, scale_limit=0.1, rotate_limit=45, interpolation=1, border_mode=4, value=None, mask_value=None, shift_limit_x=None, shift_limit_y=None, always_apply=False, p=0.5) [view source on GitHub]

Randomly apply affine transforms: translate, scale and rotate the input.

Parameters:

Name Type Description
shift_limit [float, float] or float

shift factor range for both height and width. If shift_limit is a single float value, the range will be (-shift_limit, shift_limit). Absolute values for lower and upper bounds should lie in range [0, 1]. Default: (-0.0625, 0.0625).
scale_limit [float, float] or float

scaling factor range. If scale_limit is a single float value, the range will be (-scale_limit, scale_limit). Default: (-0.1, 0.1).
rotate_limit [int, int] or int

rotation range. If rotate_limit is a single int value, the range will be (-rotate_limit, rotate_limit). Default: (-45, 45).
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.
border_mode OpenCV flag

flag that is used to specify the pixel extrapolation method. Should be one of: cv2.BORDER_CONSTANT, cv2.BORDER_REPLICATE, cv2.BORDER_REFLECT, cv2.BORDER_WRAP, cv2.BORDER_REFLECT_101. Default: cv2.BORDER_REFLECT_101
value int, float, list of int, list of float

padding value if border_mode is cv2.BORDER_CONSTANT.
mask_value int, float, list of int, list of float

padding value if border_mode is cv2.BORDER_CONSTANT applied for masks.
shift_limit_x [float, float] or float

shift factor range for width. If it is set then this value instead of shift_limit will be used for shifting width. If shift_limit_x is a single float value, the range will be (-shift_limit_x, shift_limit_x). Absolute values for lower and upper bounds should lie in the range [0, 1]. Default: None.
shift_limit_y [float, float] or float

shift factor range for height. If it is set then this value instead of shift_limit will be used for shifting height. If shift_limit_y is a single float value, the range will be (-shift_limit_y, shift_limit_y). Absolute values for lower and upper bounds should lie in the range [0, 1]. Default: None.
p float

probability of applying the transform. Default: 0.5.

Targets: image, mask, keypoints

Image types: uint8, float32