How keras model H5 works in theory
When you save your model as h5-file, you save the model structure, all its parameters and further informations like state of your optimizer and so on. It is just an efficient way to save huge amounts of information. You could use json or xml file formats to do this as well. 
You can't classifiy anything only using this file (it is not executable). You have to rebuild the graph as a tensorflow graph from this file. To do so you simply use the load_model() function from keras, which returns a keras.models.Model object. Then you can use this object to classifiy new data, with keras predict() function.
After training the trained model will be saved as H5 format. But I didn't know how that H5 file can be used as classifier to classifying new data. How H5 model works in theory when classifying new data?