`anomalib.models.draem.utils.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=1, persistence=0.5)	Generate Perlin noise parameterized by the octaves method. Numpy version.
`generate_perlin_noise_2d`(shape, res)	Fractal perlin noise.
`rand_perlin_2d_np`(shape, res, fade=lambda t: 6 * t*5 - 15 t*4 + 10 t**3)	Generate a random image containing Perlin noise. Numpy version.
`rand_perlin_2d`(shape, res, fade=lambda t: 6 * t*5 - 15 t*4 + 10 t**3)	Generate a random image containing Perlin noise. PyTorch version.
`rand_perlin_2d_octaves`(shape, res, octaves=1, persistence=0.5)	Generate Perlin noise parameterized by the octaves method. PyTorch version.

anomalib.models.draem.utils.perlin.lerp_np(x, y, w)[source]¶: Helper function.

anomalib.models.draem.utils.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.models.draem.utils.perlin.generate_perlin_noise_2d(shape, res)[source]¶: Fractal perlin noise.

anomalib.models.draem.utils.perlin.rand_perlin_2d_np(shape, res, fade=lambda t: ...)[source]¶: Generate a random image containing Perlin noise. Numpy version.

anomalib.models.draem.utils.perlin.rand_perlin_2d(shape, res, fade=lambda t: ...)[source]¶: Generate a random image containing Perlin noise. PyTorch version.

anomalib.models.draem.utils.perlin.rand_perlin_2d_octaves(shape, res, octaves=1, persistence=0.5)[source]¶: Generate Perlin noise parameterized by the octaves method. PyTorch version.