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mmedit.evaluation.functional.gaussian_funcs

Module Contents

Functions

gaussian(x, sigma)

Gaussian function.

dgaussian(x, sigma)

Gradient of gaussian.

gauss_filter(sigma[, epsilon])

Gradient of gaussian.

gauss_gradient(img, sigma)

Gaussian gradient.

mmedit.evaluation.functional.gaussian_funcs.gaussian(x, sigma)[源代码]

Gaussian function.

参数
  • x (array_like) – The independent variable.

  • sigma (float) – Standard deviation of the gaussian function.

返回

Gaussian value of x.

返回类型

np.ndarray or scalar

mmedit.evaluation.functional.gaussian_funcs.dgaussian(x, sigma)[源代码]

Gradient of gaussian.

参数
  • x (array_like) – The independent variable.

  • sigma (float) – Standard deviation of the gaussian function.

返回

Gradient of gaussian of x.

返回类型

np.ndarray or scalar

mmedit.evaluation.functional.gaussian_funcs.gauss_filter(sigma, epsilon=0.01)[源代码]

Gradient of gaussian.

参数
  • sigma (float) – Standard deviation of the gaussian kernel.

  • epsilon (float) – Small value used when calculating kernel size. Default: 1e-2.

返回

Gaussian filter along x axis. filter_y (np.ndarray): Gaussian filter along y axis.

返回类型

filter_x (np.ndarray)

mmedit.evaluation.functional.gaussian_funcs.gauss_gradient(img, sigma)[源代码]

Gaussian gradient.

From https://www.mathworks.com/matlabcentral/mlc-downloads/downloads/ submissions/8060/versions/2/previews/gaussgradient/gaussgradient.m/ index.html

参数
  • img (np.ndarray) – Input image.

  • sigma (float) – Standard deviation of the gaussian kernel.

返回

Gaussian gradient of input img.

返回类型

np.ndarray

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