import h5py, os
import caffe
import numpy as np

SIZE = 224 # fixed size to all images
with open( 'val1.txt', 'r' ) as T :
    lines = T.readlines()
# If you do not have enough memory split data into
# multiple batches and generate multiple separate h5 files
X = np.zeros( (len(lines), 3, SIZE, SIZE), dtype='f4' )
y = np.zeros( (len(lines),1), dtype='f4' )
z = np.zeros( (len(lines),4), dtype='f4' )
print y.shape
for i,l in enumerate(lines):
    sp = l.split(' ')
    cls= int(sp[1][:-1])
    img = caffe.io.load_image( sp[0] )
    img = caffe.io.resize( img, (SIZE, SIZE, 3) ) # resize to fixed size
    # you may apply other input transformations here...
    img = img.transpose((2,0,1))
    X[i] = img
    y[i] = float(cls)
    z[i] = [1,0,1,1] #Placeholder for real data
with h5py.File('test.h5','w') as H:
    H.create_dataset( 'data', data=X ) # note the name X given to the dataset!
    H.create_dataset( 'label', data=y ) # note the name y given to the dataset!
    H.create_dataset('data2', data=z)