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.)
