CNN_single_image_test.py

import numpy as np
from PIL import Image
import sys

"""
This program takes a single image as its input
and returns the top three predicted emotions
"""
current = Image.open(sys.argv[1])

#current
current = current.convert('L')
current = current.resize((48, 48))
data = np.array(current.getdata())
#10 on top
#11 on top
#13 okay
#15 okay
data = np.reshape(data, (1, 48, 48, 1))
from keras.models import load_model
#360 824
model = load_model('my_model_360_iter_batch_100.h5')

prediction = model.predict(data)
order = np.argsort(prediction)[0,:]
#print order
#print prediction
#first = np.argmax(prediction)
#prediction[0, first] = 0
#second = np.argmax(prediction)

tag_dict = {0: 'Angry', 1: 'Sadness', 2: 'Surprise', 3: 'Happiness', 4: 'Disgust', 5: 'Fear', 6: 'Neutral'}

#print tag_dict
print "First: " + tag_dict[order[-1]]
print "Second: " +tag_dict[order[-2]]
print "Third: " +tag_dict[order[-3]]