UpSampling2D层在Keras中如何工作?

时间:2019-05-29 15:24:36

标签: python keras deep-learning keras-layer

UpSampling2D层在Keras中如何工作?根据{{​​3}}:

  

分别用size[0]size[1]重复数据的行和列。

那么,如果size=(2, 2),它如何重复输入矩阵的行和列?您能举例说明一下程序吗?

1 个答案:

答案 0 :(得分:2)

如果

  

分别用size[0]size[1]重复数据的行和列。

没有帮助,那么也许一个例子会有所帮助:

>>> import numpy as np
>>> from keras.layers import UpSampling2D
>>> from keras.models import Sequential
>>> model = Sequential()
>>> model.add(UpSampling2D(size=(2,2), input_shape=(3,3,1)))

>>> x = np.arange(9).reshape(1,3,3,1)
>>> x[0,:,:,0]  # this is what x looks like initially
array([[0, 1, 2],
       [3, 4, 5],
       [6, 7, 8]])
>>> y = model.predict(x)
>>> y[0,:,:,0] # this is what it looks like after upsampling
array([[0., 0., 1., 1., 2., 2.],
       [0., 0., 1., 1., 2., 2.],
       [3., 3., 4., 4., 5., 5.],
       [3., 3., 4., 4., 5., 5.],
       [6., 6., 7., 7., 8., 8.],
       [6., 6., 7., 7., 8., 8.]], dtype=float32)