RGBShift

Description

Randomly shift values for each channel of the input RGB image.

    Args:
        r_shift_limit ((int, int) or int): range for changing values for the red channel. If r_shift_limit is a
            single int, the range will be (-r_shift_limit, r_shift_limit). Default: (-20, 20).
        g_shift_limit ((int, int) or int): range for changing values for the green channel. If g_shift_limit is a
            single int, the range will be (-g_shift_limit, g_shift_limit). Default: (-20, 20).
        b_shift_limit ((int, int) or int): range for changing values for the blue channel. If b_shift_limit is a
            single int, the range will be (-b_shift_limit, b_shift_limit). Default: (-20, 20).
        p (float): probability of applying the transform. Default: 0.5.

    Targets:
        image

    Image types:
        uint8, float32

    Note:
        - For uint8 images, the shift values represent absolute pixel values in the range [0, 255].
          For example, a shift of 20 for a uint8 image would add 20 to the corresponding channel.
        - For float32 images, the shift values represent fractions of the full value range [0, 1].
          For example, a shift of 0.1 for a float32 image would add 0.1 to the corresponding channel.
        - The shift values are applied independently to each channel.
        - After applying the shift, values are clipped to the valid range for the image dtype:
          [0, 255] for uint8 and [0, 1] for float32.

    Examples:
        >>> import numpy as np
        >>> import albumentations as A
        >>>
        # Shift RGB channels for uint8 image
        >>> image = np.random.randint(0, 256, (100, 100, 3), dtype=np.uint8)
        >>> transform = A.RGBShift(r_shift_limit=30, g_shift_limit=30, b_shift_limit=30, p=1.0)
        >>> shifted_image = transform(image=image)['image']
        >>>
        # Shift RGB channels for float32 image
        >>> image = np.random.rand(100, 100, 3).astype(np.float32)
        >>> transform = A.RGBShift(r_shift_limit=0.1, g_shift_limit=0.1, b_shift_limit=0.1, p=1.0)
        >>> shifted_image = transform(image=image)['image']

    

Parameters

• r_shift_limit: int | tuple[int, int] | float | tuple[float, float] (default: (-20, 20))
• g_shift_limit: int | tuple[int, int] | float | tuple[float, float] (default: (-20, 20))
• b_shift_limit: int | tuple[int, int] | float | tuple[float, float] (default: (-20, 20))
• p: float (default: 0.5)

Targets

• Image