本文整理汇总了Python中data_provider.preprocess_image方法的典型用法代码示例。如果您正苦于以下问题：Python data_provider.preprocess_image方法的具体用法？Python data_provider.preprocess_image怎么用？Python data_provider.preprocess_image使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类data_provider的用法示例。
在下文中一共展示了data_provider.preprocess_image方法的2个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: test_preprocessed_image_values_are_in_range
# 需要导入模块: import data_provider [as 别名]
# 或者: from data_provider import preprocess_image [as 别名]
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
# 需要导入模块: import data_provider [as 别名]
# 或者: from data_provider import preprocess_image [as 别名]
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