medium_data_augmentation_finished.py

class RandomInvert(tf.keras.layers.Layer):
    def __init__(self, max_value = 255, factor=0.5, **kwargs):
        super().__init__(**kwargs)
        self.factor = factor
        self.max_value = max_value

    def call(self, x):
        if  tf.random.uniform([]) < self.factor:
            x = (self.max_value - x)
        return x

data_augmentation = tf.keras.Sequential([
    RandomInvert(max_value = 1.0),
    tf.keras.layers.RandomFlip("horizontal_and_vertical"),
    tf.keras.layers.RandomRotation((-0.4, 0.4)),
    tf.keras.layers.RandomBrightness(factor=(-0.2, 0.2), value_range=(0., 1.)),
    tf.keras.layers.GaussianNoise(0.005),
    tf.keras.layers.RandomZoom(height_factor=(-0.4, 0.4)),
    tf.keras.layers.RandomContrast(factor=(0.1, 0.9)),
    tf.keras.layers.RandomTranslation(height_factor=0.2, width_factor=0.2)
])