dsift.py 文件源码

def gen_dgauss(sigma):
    '''
    gradient of the gaussian on both directions.
    '''
    fwid = np.int(2 * np.ceil(sigma))
    G = np.array(range(-fwid, fwid + 1)) ** 2
    G = G.reshape((G.size, 1)) + G
    G = np.exp(- G / 2.0 / sigma / sigma)
    G /= np.sum(G)
    GH, GW = np.gradient(G)
    GH *= 2.0 / np.sum(np.abs(GH))
    GW *= 2.0 / np.sum(np.abs(GW))
    return GH, GW