def preprocess(img): img = tf.image.resize_images(img, [360, 360]) img = common_layers.image_augmentation(tf.to_float(img) / 255.) return tf.to_int64(img * 255.)
def testImageAugmentation(self): x = np.random.rand(500, 500, 3) with self.test_session() as session: y = common_layers.image_augmentation(tf.constant(x)) res = session.run(y) self.assertEqual(res.shape, (299, 299, 3))
def preprocess(img): img = tf.image.resize_images(img, [360, 360]) img = common_layers.image_augmentation( tf.to_float(img) / 255., crop_size=resize_size) return tf.to_int64(img * 255.)