load saved model

1from keras.models import load_model
2model = load_model('my_model.h5')
3

1# compile the model in order to make predictions
2model.compile(optimizer = 'adam', loss = 'binary_crossentropy', metrics = ['accuracy'])
3

1#Now you can predict results for a new entry image.
2
3from keras.preprocessing import image
4
5test_image = image.load_img(imagePath, target_size = (64, 64)) 
6test_image = image.img_to_array(test_image)
7test_image = np.expand_dims(test_image, axis = 0)
8
9#predict the result
10result = model.predict(test_image)
11