Add a step to inspect the data of AerocraftML notebook

aeroplanes.py

!wget https://s3-us-west-2.amazonaws.com/awsgeek-devweek-austin/mlclassify_train.rec --quiet
!mkdir -p training_data

 %matplotlib inline

 from mxnet import recordio
 import mxnet as mx
 import cv2
 import matplotlib.pyplot as plt
 import matplotlib.image as mpimg
 from PIL import Image

 record = mx.recordio.MXRecordIO('mlclassify_train.rec', 'r')

 ## Extract all images from recordio file
 i = 0
 while True:
     item = record.read()
     if not item:
         break
     header, img = mx.recordio.unpack_img(item)
     filename = "training_data/aeroplane%s.jpg" % i
     cv2.imwrite(filename, img)
     i += 1
 record.close()

 ## Display the image without extracting from file
 #b,g,r = cv2.split(img)
 #img = cv2.merge([r,g,b])
 #plt.imshow(img)

 ## Plot images for displaying in the notebook
 object_categories = ['dornier-328','boeing-747','airbus-a320']
 f, axarr = plt.subplots(1,3, figsize=(30,30))
 col = 0
 for i in range(3):
     im = Image.open('training_data/aeroplane%d.jpg' % (i+1))
     axarr[col].text(0, 0, '%s' %(object_categories[i] ), fontsize=30, color='blue')
     frame = axarr[col].imshow(im)
     col += 1
 plt.show()