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问题背景：在分类网络中，往往需要突出前景，弱化背景，往往有一个操作是减去均值。
解决办法：（供参考，我是这么解决的）
求自己数据集的均值和方差
def compute_mean_std(your_dataset):
"""compute the mean and std of your dataset
Args:
your_training_dataset or your_test_dataset
witch derived from class torch.utils.data
Returns:
a tuple contains mean, std value of entire dataset
"""
data_r = numpy.dstack([your_dataset[i][1][:, :, 0] for i in range(len(your_dataset))])
data_g = numpy.dstack([your_dataset[i][1][:, :, 1] for i in range(len(your_dataset))])
data_b = numpy.dstack([your_dataset[i][1][:, :, 2] for i in range(len(your_dataset))])
mean = numpy.mean(data_r), numpy.mean(data_g), numpy.mean(data_b)
std = numpy.std(data_r), numpy.std(data_g), numpy.std(data_b)
return mean, std
