preprocess_cifar10.py 文件源码

def create_zca(imgs, filter_bias=0.1):
    meanX = np.mean(imgs, axis=0)

    covX = np.cov(imgs.T)
    D, E = np.linalg.eigh(covX + filter_bias * np.eye(covX.shape[0], covX.shape[1]))

    assert not np.isnan(D).any()
    assert not np.isnan(E).any()
    assert D.min() > 0

    D **= -.5

    W = np.dot(E, np.dot(np.diag(D), E.T))

    def transform(images):
        return np.dot(images - meanX, W)

    return transform