loading an image from cifar-10 dataset

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I am using cifar-10 dataset for my training my classifier. I have downloaded the dataset and tried to display am image from the dataset. I have used the following code:

from six.moves import cPickle as pickle
from  PIL import Image
import numpy as np

f = open('/home/jayanth/udacity/cifar-10-batches-py/data_batch_1', 'rb')

tupled_data= pickle.load(f, encoding='bytes')

f.close()

img = tupled_data[b'data']

single_img = np.array(img[5])

single_img_reshaped = single_img.reshape(32,32,3)

plt.imshow(single_img_reshaped)

the description of data is as follows: Each array stores a 32x32 colour image. The first 1024 entries contain the red channel values, the next 1024 the green, and the final 1024 the blue. The image is stored in row-major order, so that the first 32 entries of the array are the red channel values of the first row of the image.

Is my implementation correct?

the above code gave me the following image: enter image description here

deep-learning numpy python
3 Answers

Since Python uses the default C-like indexing order (row-major order), it can be forced to work in column-major order:

import numpy as np
import matplotlib.pyplot as plt

# I assume you have loaded your data into x_train (see some tutorial)

data = x_train[0, :] # get a row data
data = np.reshape(data, (32,32,3), order='F' ) # Fortran-like indexing order
plt.imshow(data)
user_34815230 
single_img_reshaped = single_img.reshape(3,32,32).transpose([1, 2, 0])
user_56577150
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