model.py

from keras.models import Sequential
from keras.layers import Dense, Dropout, Flatten, Activation
from keras.layers import Convolution2D, MaxPooling2D

def load_model(input_shape, num_classes):
    model = Sequential()

    model.add(Convolution2D(6, kernel_size=(3, 3), activation='relu', input_shape=input_shape, padding="same"))
    model.add(Convolution2D(32, kernel_size=(3, 3), activation='relu'))
    model.add(MaxPooling2D(pool_size=(2, 2)))
    model.add(Dropout(0.25))

    model.add(Convolution2D(64, kernel_size=(3, 3), border_mode='same', activation='relu'))
    model.add(Convolution2D(64, kernel_size=(3, 3), activation='relu'))
    model.add(MaxPooling2D(pool_size=(2, 2)))
    model.add(Dropout(0.25))

    model.add(Flatten())
    model.add(Dense(512, activation='relu'))
    model.add(Dropout(0.5))
    model.add(Dense(num_classes, activation='softmax'))

    return model