diff --git a/modules/util/augment.py b/modules/util/augment.py index 790d4f1bd6d0a2aeb70d1d222d2396224e6cea89..f66e94d678718e0d48fbd676015f9e874ccfcfd0 100644 --- a/modules/util/augment.py +++ b/modules/util/augment.py @@ -87,3 +87,47 @@ def augment_icing(): partial(augment_steps_fn, data, data_b, label)) return augment_fn + + +def augment_image_3arg(): + """ Helper function used for augmentation of images in the dataset. + Returns: + tf.data.Dataset mappable function for image augmentation + """ + + def augment_fn(data, data_b, label, *args, **kwargs): + # Augmenting data (~ 80%) + + def augment_steps_fn(data, data_b, label): + # Randomly rotating image (~50%) + def rotate_fn(data, data_b, label): + times = tf.random.uniform(minval=1, maxval=4, dtype=tf.int32, shape=[]) + return (tf.image.rot90(data, times), + tf.image.rot90(data_b, times), + tf.image.rot90(label, times)) + + data, data_b, label = tf.cond( + tf.less_equal(tf.random.uniform([]), 0.5), + lambda: rotate_fn(data, data_b, label), + lambda: (data, data_b, label)) + + # Randomly flipping image (~50%) + def flip_fn(data, data_b, label): + return (tf.image.flip_left_right(data), + tf.image.flip_left_right(data_b), + tf.image.flip_left_right(label)) + + data, data_b, label = tf.cond( + tf.less_equal(tf.random.uniform([]), 0.5), + lambda: flip_fn(data, data_b, label), + lambda: (data, data_b, label)) + + return data, data_b, label + + # Randomly returning unchanged data (~20%) + return tf.cond( + tf.less_equal(tf.random.uniform([]), 0.2), + lambda: (data, data_b, label), + partial(augment_steps_fn, data, data_b, label)) + + return augment_fn \ No newline at end of file