anomalib.data.utils.generators.perlin

Helper functions for generating Perlin noise.

Module Contents

Functions

lerp_np(x, y, w)

Helper function.

rand_perlin_2d_octaves_np(shape, res[, octaves, ...])

Generate Perlin noise parameterized by the octaves method. Numpy version.

generate_perlin_noise_2d(shape, res)

Fractal perlin noise.

random_2d_perlin(→ Union[numpy.ndarray, torch.Tensor])

Returns a random 2d perlin noise array.

_rand_perlin_2d_np(shape, res[, fade])

Generate a random image containing Perlin noise. Numpy version.

_rand_perlin_2d(shape, res[, fade])

Generate a random image containing Perlin noise. PyTorch version.

rand_perlin_2d_octaves(shape, res[, octaves, persistence])

Generate Perlin noise parameterized by the octaves method. PyTorch version.
anomalib.data.utils.generators.perlin.lerp_np(x, y, w)[source]

Helper function.

anomalib.data.utils.generators.perlin.rand_perlin_2d_octaves_np(shape, res, octaves=1, persistence=0.5)[source]

Generate Perlin noise parameterized by the octaves method. Numpy version.

anomalib.data.utils.generators.perlin.generate_perlin_noise_2d(shape, res)[source]

Fractal perlin noise.

anomalib.data.utils.generators.perlin.random_2d_perlin(shape: Tuple, res: Tuple[Union[int, torch.Tensor], Union[int, torch.Tensor]], fade=lambda t: ...) → Union[numpy.ndarray, torch.Tensor][source]

Returns a random 2d perlin noise array.

Parameters

  • shape (Tuple) – Shape of the 2d map.

  • res (Tuple[Union[int, Tensor]]) – Tuple of scales for perlin noise for height and width dimension.

  • fade (_type_, optional) – Function used for fading the resulting 2d map. Defaults to equation 6*t**5-15*t**4+10*t**3.

Returns

Random 2d-array/tensor generated using perlin noise.

Return type

Union[np.ndarray, Tensor]

anomalib.data.utils.generators.perlin._rand_perlin_2d_np(shape, res, fade=lambda t: ...)[source]

Generate a random image containing Perlin noise. Numpy version.

anomalib.data.utils.generators.perlin._rand_perlin_2d(shape, res, fade=lambda t: ...)[source]

Generate a random image containing Perlin noise. PyTorch version.

anomalib.data.utils.generators.perlin.rand_perlin_2d_octaves(shape, res, octaves=1, persistence=0.5)[source]

Generate Perlin noise parameterized by the octaves method. PyTorch version.