preprocess vgg

preprocess.py

@tf.function
def preprocess_caffe(x):
    """
    Preprocessing for Keras (VGG, ResnetV1).
    ! This works only for channels_last
    :param x: np.asarray([image, image, ...], dtype="float32") in RGB
    :return: normalized image vgg style (BGR)
    """
    batch, height, width, channels = x.shape
    x = tf.cast(x, tf.float32)
    r, g, b = tf.split(x, 3, axis=3)
    x = tf.concat([b, g, r], 3)
    mean_tensor = np.asarray([[[[103.939, 116.779, 123.68]]]], dtype=np.float32)
    result = x - mean_tensor
    return tf.keras.backend.reshape(result, (-1, height, width, channels))