我们可以将两个以上的数据连接到一个张量吗 [英] can we concatenate more then two data to one tensor

问题描述

我有三个包含数据的numpy数组.

I have three numpy array that contains my data.

X_train = np.zeros((1, 288, 288, 3), dtype=np.uint8)

X_train2 = np.zeros((1, 288, 288, 3), dtype=np.uint8)

X_train3 = np.zeros((1, 288, 288, 3), dtype=np.uint8)

使用np.concatenate，我可以将两个图像连接到一个张量，如下所示:

Using np.concatenate I can concatenate two image to one tensor as below :

X_train2=np.concatenate([X_train, X_train2], axis = -1)

我想使用numpy将多个图像X_train以及X_train2和X_train3连接到一个张量.

I want to concatenate multiple image X_train and X_train2 and X_train3 to one tensor is it possible using numpy.

推荐答案

是.您可以根据需要串联任意多个numpy数组.

Yes. You can concatenate as many numpy array as you want.

X_train_final = np.concatenate([X_train, X_train2, X_train3], axis = -1)

是有效的，它将为您提供一个数组，最后一个维度将是原始数组的3倍.您可以按照自己的喜好继续这种方式.

is valid and will give you an array where, the last dimension will be 3 times as in the original array. You can continue this way for as many arrays as you likee.

阅读文档: https://numpy.org/doc /1.18/reference/generation/numpy.concatenate.html

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