OpticalDistortion

Description

Apply optical distortion to images, masks, bounding boxes, and keypoints.

    This transformation simulates lens distortion effects by warping the image using
    a camera matrix and distortion coefficients. It's particularly useful for
    augmenting data in computer vision tasks where camera lens effects are relevant.

    Args:
        distort_limit (float or tuple of float): Range of distortion coefficient.
            If distort_limit is a single float, the range will be (-distort_limit, distort_limit).
            Default: (-0.05, 0.05).
        shift_limit (float or tuple of float): Range of shifts for the image center.
            If shift_limit is a single float, the range will be (-shift_limit, shift_limit).
            Default: (-0.05, 0.05).
        interpolation (OpenCV flag): Interpolation method used for image transformation.
            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): Border mode used for handling pixels outside the image.
            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. Default: None.
        mask_value (int, float, list of int, list of float): Padding value for mask
            if border_mode is cv2.BORDER_CONSTANT. Default: None.
        mask_interpolation (OpenCV flag): Flag that is used to specify the interpolation algorithm for mask.
            Should be one of: cv2.INTER_NEAREST, cv2.INTER_LINEAR, cv2.INTER_CUBIC, cv2.INTER_AREA, cv2.INTER_LANCZOS4.
            Default: cv2.INTER_NEAREST.
        p (float): Probability of applying the transform. Default: 0.5.

    Targets:
        image, mask, bboxes, keypoints

    Image types:
        uint8, float32

    Note:
        - The distortion is applied using OpenCV's initUndistortRectifyMap and remap functions.
        - The distortion coefficient (k) is randomly sampled from the distort_limit range.
        - The image center is shifted by dx and dy, randomly sampled from the shift_limit range.
        - Bounding boxes and keypoints are transformed along with the image to maintain consistency.

    Example:
        >>> import albumentations as A
        >>> transform = A.Compose([
        ...     A.OpticalDistortion(distort_limit=0.1, shift_limit=0.1, p=1.0),
        ... ])
        >>> transformed = transform(image=image, mask=mask, bboxes=bboxes, keypoints=keypoints)
        >>> transformed_image = transformed['image']
        >>> transformed_mask = transformed['mask']
        >>> transformed_bboxes = transformed['bboxes']
        >>> transformed_keypoints = transformed['keypoints']
    

Parameters

• distort_limit: int | tuple[int, int] | float | tuple[float, float] (default: (-0.05, 0.05))
• shift_limit: int | tuple[int, int] | float | tuple[float, float] (default: (-0.05, 0.05))
• interpolation: Literal['cv2.INTER_NEAREST', 'cv2.INTER_LINEAR', 'cv2.INTER_CUBIC', 'cv2.INTER_AREA', 'cv2.INTER_LANCZOS4', 'cv2.INTER_BITS', 'cv2.INTER_NEAREST_EXACT', 'cv2.INTER_MAX'] (default: 1)
• border_mode: Literal['cv2.BORDER_CONSTANT', 'cv2.BORDER_REPLICATE', 'cv2.BORDER_REFLECT', 'cv2.BORDER_WRAP', 'cv2.BORDER_DEFAULT', 'cv2.BORDER_TRANSPARENT'] (default: 4)
• value: float | Sequence[float] | None (default: null)
• mask_value: float | Sequence[float] | None (default: null)
• mask_interpolation: Literal['cv2.INTER_NEAREST', 'cv2.INTER_LINEAR', 'cv2.INTER_CUBIC', 'cv2.INTER_AREA', 'cv2.INTER_LANCZOS4', 'cv2.INTER_BITS', 'cv2.INTER_NEAREST_EXACT', 'cv2.INTER_MAX'] (default: 0)
• p: float (default: 0.5)

Targets

• Image
• Mask
• BBoxes
• Keypoints