HOGGenerator

class mmpretrain.models.selfsup.HOGGenerator(nbins=9, pool=8, gaussian_window=16)

Generate HOG feature for images.

This module is used in MaskFeat to generate HOG feature. The code is modified from file slowfast/models/operators.py. Here is the link of HOG wikipedia.

Parameters:

• nbins (int) – Number of bin. Defaults to 9.

• pool (float) – Number of cell. Defaults to 8.

• gaussian_window (int) – Size of gaussian kernel. Defaults to 16.

forward(x)

Generate hog feature for each batch images.

Parameters:

x (torch.Tensor) – Input images of shape (N, 3, H, W).

Returns:

Hog features.

Return type:

torch.Tensor

generate_hog_image(hog_out)

Generate HOG image according to HOG features.

get_gaussian_kernel(kernlen, std)

Returns a 2D Gaussian kernel array.