Emboss

Description

Apply embossing effect to the input image.

    This transform creates an emboss effect by highlighting edges and creating a 3D-like texture
    in the image. It works by applying a specific convolution kernel to the image that emphasizes
    differences in adjacent pixel values.

    Args:
        alpha (tuple[float, float]): Range to choose the visibility of the embossed image.
            At 0, only the original image is visible, at 1.0 only its embossed version is visible.
            Values should be in the range [0, 1].
            Alpha will be randomly selected from this range for each image.
            Default: (0.2, 0.5)

        strength (tuple[float, float]): Range to choose the strength of the embossing effect.
            Higher values create a more pronounced 3D effect.
            Values should be non-negative.
            Strength will be randomly selected from this range for each image.
            Default: (0.2, 0.7)

        p (float): Probability of applying the transform. Should be in the range [0, 1].
            Default: 0.5

    Targets:
        image

    Image types:
        uint8, float32

    Note:
        - The emboss effect is created using a 3x3 convolution kernel.
        - The 'alpha' parameter controls the blend between the original image and the embossed version.
          A higher alpha value will result in a more pronounced emboss effect.
        - The 'strength' parameter affects the intensity of the embossing. Higher strength values
          will create more contrast in the embossed areas, resulting in a stronger 3D-like effect.
        - This transform can be useful for creating artistic effects or for data augmentation
          in tasks where edge information is important.

    Example:
        >>> import numpy as np
        >>> import albumentations as A
        >>> image = np.random.randint(0, 256, (100, 100, 3), dtype=np.uint8)
        >>> transform = A.Emboss(alpha=(0.2, 0.5), strength=(0.2, 0.7), p=0.5)
        >>> result = transform(image=image)
        >>> embossed_image = result['image']

    References:
        - https://en.wikipedia.org/wiki/Image_embossing
        - https://www.researchgate.net/publication/303412455_Application_of_Emboss_Filtering_in_Image_Processing
    

Parameters

• alpha: tuple[float, float] (default: (0.2, 0.5))
• strength: tuple[float, float] (default: (0.2, 0.7))
• p: float (default: 0.5)

Targets

• Image