plot_examples.py

import h5py 
import numpy as np 
data=h5py.File('forplotting.hdf5','r')
img_train=np.asarray(data['img_train']) 
img_valid=np.asarray(data['img_valid']) 
img_test=np.asarray(data['img_test']) 
import matplotlib.pyplot as plt 
#img_train=X_train[10]#np.expand_dims(X_train[10],axis=0) 
#img_valid=X_valid[10]#np.expand_dims(X_valid[10],axis=0) 
#img_test=X_test[10]#np.expand_dims(X_test[10],axis=0) 
#f=h5py.File('forplotting.hdf5','w')
#dset_xtrain=f.create_dataset("img_train",data=img_train)
#dset_ytrain=f.create_dataset("img_valid",data=img_valid)
#dset_xvalid=f.create_dataset("img_test",data=img_test) 
#f.flush() 
#f.close() 
print(img_train.shape) 
print(img_valid.shape) 
print(img_test.shape) 
plt.figure(figsize=(10, 10), facecolor='w')
plt.suptitle('Visualization of pre-processed images') 
plt.subplot(1, 3, 1)
plt.title('train') 
plt.imshow(img_train.transpose(1,2,0))
plt.subplot(1,3,2) 
plt.title('valid') 
plt.imshow(img_valid.transpose(1,2,0)) 
plt.subplot(1, 3, 3)
plt.title('test') 
plt.imshow(img_test.transpose(1,2,0))
plt.savefig('TrainTestValidateExample.png')