本文整理匯總了Python中data_provider.preprocess_image方法的典型用法代碼示例。如果您正苦於以下問題：Python data_provider.preprocess_image方法的具體用法？Python data_provider.preprocess_image怎麽用？Python data_provider.preprocess_image使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類data_provider的用法示例。
在下文中一共展示了data_provider.preprocess_image方法的2個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: test_preprocessed_image_values_are_in_range
# 需要導入模塊: import data_provider [as 別名]
# 或者: from data_provider import preprocess_image [as 別名]
def test_preprocessed_image_values_are_in_range(self):
image_shape = (5, 4, 3)
fake_image = np.random.randint(low=0, high=255, size=image_shape)
image_tf = data_provider.preprocess_image(fake_image)
with self.test_session() as sess:
image_np = sess.run(image_tf)
self.assertEqual(image_np.shape, image_shape)
min_value, max_value = np.min(image_np), np.max(image_np)
self.assertTrue((-1.28 < min_value) and (min_value < 1.27))
self.assertTrue((-1.28 < max_value) and (max_value < 1.27)) 示例2: create_model
# 需要導入模塊: import data_provider [as 別名]
# 或者: from data_provider import preprocess_image [as 別名]
def create_model(batch_size, dataset_name):
width, height = get_dataset_image_size(dataset_name)
dataset = common_flags.create_dataset(split_name=FLAGS.split_name)
model = common_flags.create_model(
num_char_classes=dataset.num_char_classes,
seq_length=dataset.max_sequence_length,
num_views=dataset.num_of_views,
null_code=dataset.null_code,
charset=dataset.charset)
raw_images = tf.placeholder(tf.uint8, shape=[batch_size, height, width, 3])
images = tf.map_fn(data_provider.preprocess_image, raw_images,
dtype=tf.float32)
endpoints = model.create_base(images, labels_one_hot=None)
return raw_images, endpoints