x_train = x_train.reshape(x_train.shape[0], 1, img_rows, img_cols) x_test =
x_test.reshape(x_test.shape[0], 1, img_rows, img_cols) from numpy import * l =
zeros((5,4))#构建一个5*4的零矩阵 for i in range(5):#给该矩阵赋值 for j in range(4): l[i][j] =
i * 5 + j print(l)#打印赋值后的矩阵 print(shape(l))#输出l的行列值 print(l.shape[0])#输出l的行数值
print(l.shape[1])#输出l的列数值
python 图像读入 reshape尺寸时的问题
#coding=utf-8 import matplotlib.pyplot as plt import matplotlib.image as
mimage image=mimage.imread('lala.jpg') print image.shape # show a picture
image=image.reshape(1,-1) #-1是根据数组大小进行维度的自动推断
#若使用的是image=image.reshape成一行，分别为R一块, G块 ,B一块 # t=imgX1[222,:].reshape(3,32,32)
# print('t= ' ,t.shape) # image=np.transpose(t,(1,2,0))
image=image.reshape(1186,1920,3) print(image.shape) plt.imshow(image)
plt.axis('off') plt.show()

/ 如果将浮点数转换为整数，则小数部分会被截断 In [7]: arr2 = np.array([1.1, 2.2, 3.3, 4.4, 5.3221])
In [8]: arr2 Out[8]: array([ 1.1 , 2.2 , 3.3 , 4.4 , 5.3221]) // 查看当前数据类型 In
[9]: arr2.dtype Out[9]: dtype('float64') // 转换数据类型 float -> int In [10]:
arr2.astype(np.int32) Out[10]: array([1, 2, 3, 4, 5], dtype=int32) 数据类型转换
x_train = x_train.astype('float32') x_test = x_test.astype('float32')
#数据归一化（0,1） x_train /= 255 x_test /= 255