Reshaping numpy array containing image data

Question

I have a numpy array: all_data=(10000,3072) where each cell in array is data of a 32*32*3 image. When the data in the cell is formatted as:

np.transpose(np.reshape(image_data,(3, 32,32)), (1,2,0))

the real image is displayed (using plt.imshow or any such libraries) . Now i want to transform all_data such that the shape of all_data is (10000,32,32,3) How can i do this?

what is image_data? Is it the same as all_data or is it something else? — Atlas7
– Atlas7, Commented Aug 1, 2017 at 23:48

akuiper · Accepted Answer · 2017-08-01 23:03:54Z

1

You could try this, (the same reshaping process but keep the first dimension untouched):

all_data.reshape(10000, 3, 32, 32).transpose(0,2,3,1)

Example:

all_data = np.arange(24).reshape(2,12)

Target reshape it to (2,2,2,3):

all_data
# array([[ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11],
#        [12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23]])

Reshape one element of the data:

all_data[0].reshape(3,2,2).transpose(1,2,0)
# array([[[ 0,  4,  8],
#         [ 1,  5,  9]],

#        [[ 2,  6, 10],
#         [ 3,  7, 11]]])

Reshape it all together:

all_data.reshape(2,3,2,2).transpose(0,2,3,1)[0]
# array([[[ 0,  4,  8],
#         [ 1,  5,  9]],

#        [[ 2,  6, 10],
#         [ 3,  7, 11]]])

edited Aug 1, 2017 at 23:03

answered Aug 1, 2017 at 22:20

akuiper

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