gistfile1.txt

def get_model(dim = (224,224,3)):
    keras.backend.clear_session()
    model = keras.models.Sequential()
    model.add(keras.layers.Conv2D(32,(3,3),activation='relu',input_shape=dim))
    model.add(keras.layers.Conv2D(32,(3,3),activation='relu',padding="valid",))
    model.add(keras.layers.MaxPooling2D((2,2)))
    model.add(keras.layers.Dropout(.4))
    model.add(keras.layers.Conv2D(32,(5,5),activation='relu',padding="valid"))
    model.add(keras.layers.MaxPooling2D((2,2)))
    model.add(keras.layers.Dropout(.4))
    model.add(keras.layers.Conv2D(32,(5,5),activation='relu',padding="valid"))
    model.add(keras.layers.MaxPooling2D((2,2)))
    model.add(keras.layers.Dropout(.4))
    model.add(keras.layers.Conv2D(64,(5,5),activation='relu',padding="valid"))
    model.add(keras.layers.MaxPooling2D((2,2)))
    model.add(keras.layers.Dropout(.4))
    model.add(keras.layers.Conv2D(64,(5,5),activation='relu',padding="valid"))
    model.add(keras.layers.MaxPooling2D((2,2)))
    model.add(keras.layers.Dropout(.4))
    model.add(keras.layers.Flatten()) 
    model.add(keras.layers.Dropout(.4))
    model.add(keras.layers.Dense(15,activation='softmax'))
    model.summary()
    return model