msaf/algorithms/foote/segmenter.py
def compute_gaussian_krnl(M):
    """Creates a gaussian kernel following Foote's paper."""
    g = signal.gaussian(M, M // 3., sym=True)
    G = np.dot(g.reshape(-1, 1), g.reshape(1, -1))
    G[M // 2:, :M // 2] = -G[M // 2:, :M // 2]
    G[:M // 2, M // 2:] = -G[:M // 2, M // 2:]
    return G
def compute_gaussian_krnl(M):
    """Creates a gaussian kernel following Foote's paper."""
    g = signal.gaussian(M, M // 3., sym=True)
    G = np.dot(g.reshape(-1, 1), g.reshape(1, -1))
    G[M // 2:, :M // 2] = -G[M // 2:, :M // 2]
    G[:M // 2, M // 2:] = -G[:M // 2, M // 2:]
    return G
Creates a gaussian kernel following Foote's paper.