resnetmodule.py

# A single resnet module consisting of 1 x 1 conv - 3 x 3 conv and 1 x 1 conv
def resnet_module(x, filters, pool=False):
    res = x
    stride = 1
    if pool:
        stride = 2
        res = Conv2D(filters, kernel_size=1, strides=2, padding="same")(res)
        res = BatchNormalization()(res)

    x = Conv2D(int(filters / 4), kernel_size=1, strides=stride, padding="same")(x)
    x = BatchNormalization()(x)
    x = Activation("relu")(x)

    x = Conv2D(int(filters / 4), kernel_size=3, strides=1, padding="same")(x)
    x = BatchNormalization()(x)
    x = Activation("relu")(x)

    x = Conv2D(filters, kernel_size=1, strides=1, padding="same")(x)
    x = BatchNormalization()(x)

    x = add([x, res])
    x = Activation("relu")(x)

    return x