models.py

from keras.layers import Dense,Dropout,Conv3D,Input,MaxPool3D,Flatten,Activation
from keras.regularizers import l2
from keras.models import Model


def c3d_model():
    input_shape = (112,112,16,3)
    weight_decay = 0.005
    nb_classes = 2

    inputs = Input(input_shape)
    x = Conv3D(64,(3,3,3),strides=(1,1,1),padding='same',
               activation='relu',kernel_regularizer=l2(weight_decay))(inputs)
    x = MaxPool3D((2,2,1),strides=(2,2,1),padding='same')(x)

    x = Conv3D(128,(3,3,3),strides=(1,1,1),padding='same',
               activation='relu',kernel_regularizer=l2(weight_decay))(x)
    x = MaxPool3D((2,2,2),strides=(2,2,2),padding='same')(x)

    x = Conv3D(128,(3,3,3),strides=(1,1,1),padding='same',
               activation='relu',kernel_regularizer=l2(weight_decay))(x)
    x = MaxPool3D((2,2,2),strides=(2,2,2),padding='same')(x)

    x = Conv3D(256,(3,3,3),strides=(1,1,1),padding='same',
               activation='relu',kernel_regularizer=l2(weight_decay))(x)
    x = MaxPool3D((2,2,2),strides=(2,2,2),padding='same')(x)

    x = Conv3D(256, (3, 3, 3), strides=(1, 1, 1), padding='same',
               activation='relu',kernel_regularizer=l2(weight_decay))(x)
    x = MaxPool3D((2, 2, 2), strides=(2, 2, 2), padding='same')(x)

    x = Flatten()(x)
    x = Dense(2048,activation='relu',kernel_regularizer=l2(weight_decay))(x)
    x = Dropout(0.5)(x)
    x = Dense(2048,activation='relu',kernel_regularizer=l2(weight_decay))(x)
    x = Dropout(0.5)(x)
    x = Dense(nb_classes,kernel_regularizer=l2(weight_decay))(x)
    x = Activation('softmax')(x)

    model = Model(inputs, x)
    return model