本文整理汇总了Python中object_detection.inputs.create_predict_input_fn方法的典型用法代码示例。如果您正苦于以下问题：Python inputs.create_predict_input_fn方法的具体用法？Python inputs.create_predict_input_fn怎么用？Python inputs.create_predict_input_fn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object_detection.inputs的用法示例。
在下文中一共展示了inputs.create_predict_input_fn方法的6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_predict_input_with_additional_channels
# 需要导入模块: from object_detection import inputs [as 别名]
# 或者: from object_detection.inputs import create_predict_input_fn [as 别名]
def test_predict_input_with_additional_channels(self):
"""Tests the predict input function with additional channels."""
configs = _get_configs_for_model('ssd_inception_v2_pets')
configs['eval_input_configs'][0].num_additional_channels = 2
predict_input_fn = inputs.create_predict_input_fn(
model_config=configs['model'],
predict_input_config=configs['eval_input_configs'][0])
serving_input_receiver = predict_input_fn()
image = serving_input_receiver.features[fields.InputDataFields.image]
receiver_tensors = serving_input_receiver.receiver_tensors[
inputs.SERVING_FED_EXAMPLE_KEY]
# RGB + 2 additional channels = 5 channels.
self.assertEqual([1, 300, 300, 5], image.shape.as_list())
self.assertEqual(tf.float32, image.dtype)
self.assertEqual(tf.string, receiver_tensors.dtype) 示例2: test_predict_input_with_additional_channels
# 需要导入模块: from object_detection import inputs [as 别名]
# 或者: from object_detection.inputs import create_predict_input_fn [as 别名]
def test_predict_input_with_additional_channels(self):
"""Tests the predict input function with additional channels."""
configs = _get_configs_for_model('ssd_inception_v2_pets')
configs['eval_input_config'].num_additional_channels = 2
predict_input_fn = inputs.create_predict_input_fn(
model_config=configs['model'],
predict_input_config=configs['eval_input_config'])
serving_input_receiver = predict_input_fn()
image = serving_input_receiver.features[fields.InputDataFields.image]
receiver_tensors = serving_input_receiver.receiver_tensors[
inputs.SERVING_FED_EXAMPLE_KEY]
# RGB + 2 additional channels = 5 channels.
self.assertEqual([1, 300, 300, 5], image.shape.as_list())
self.assertEqual(tf.float32, image.dtype)
self.assertEqual(tf.string, receiver_tensors.dtype) 示例3: test_predict_input
# 需要导入模块: from object_detection import inputs [as 别名]
# 或者: from object_detection.inputs import create_predict_input_fn [as 别名]
def test_predict_input(self):
"""Tests the predict input function."""
configs = _get_configs_for_model('ssd_inception_v2_pets')
predict_input_fn = inputs.create_predict_input_fn(
model_config=configs['model'],
predict_input_config=configs['eval_input_configs'][0])
serving_input_receiver = predict_input_fn()
image = serving_input_receiver.features[fields.InputDataFields.image]
receiver_tensors = serving_input_receiver.receiver_tensors[
inputs.SERVING_FED_EXAMPLE_KEY]
self.assertEqual([1, 300, 300, 3], image.shape.as_list())
self.assertEqual(tf.float32, image.dtype)
self.assertEqual(tf.string, receiver_tensors.dtype) 示例4: test_predict_input
# 需要导入模块: from object_detection import inputs [as 别名]
# 或者: from object_detection.inputs import create_predict_input_fn [as 别名]
def test_predict_input(self):
"""Tests the predict input function."""
configs = _get_configs_for_model('ssd_inception_v2_pets')
predict_input_fn = inputs.create_predict_input_fn(
model_config=configs['model'])
serving_input_receiver = predict_input_fn()
image = serving_input_receiver.features[fields.InputDataFields.image]
receiver_tensors = serving_input_receiver.receiver_tensors[
inputs.SERVING_FED_EXAMPLE_KEY]
self.assertEqual([1, 300, 300, 3], image.shape.as_list())
self.assertEqual(tf.float32, image.dtype)
self.assertEqual(tf.string, receiver_tensors.dtype) 示例5: test_predict_input
# 需要导入模块: from object_detection import inputs [as 别名]
# 或者: from object_detection.inputs import create_predict_input_fn [as 别名]
def test_predict_input(self):
"""Tests the predict input function."""
configs = _get_configs_for_model('ssd_inception_v2_pets')
predict_input_fn = inputs.create_predict_input_fn(
model_config=configs['model'],
predict_input_config=configs['eval_input_config'])
serving_input_receiver = predict_input_fn()
image = serving_input_receiver.features[fields.InputDataFields.image]
receiver_tensors = serving_input_receiver.receiver_tensors[
inputs.SERVING_FED_EXAMPLE_KEY]
self.assertEqual([1, 300, 300, 3], image.shape.as_list())
self.assertEqual(tf.float32, image.dtype)
self.assertEqual(tf.string, receiver_tensors.dtype) 示例6: test_predict_input
# 需要导入模块: from object_detection import inputs [as 别名]
# 或者: from object_detection.inputs import create_predict_input_fn [as 别名]
def test_predict_input(self):
"""Tests the predict input function."""
configs = _get_configs_for_model('ssd_inception_v2_pets')
predict_input_fn = inputs.create_predict_input_fn(
model_config=configs['model'])
serving_input_receiver = predict_input_fn()
image = serving_input_receiver.features[fields.InputDataFields.image]
receiver_tensors = serving_input_receiver.receiver_tensors[
inputs.SERVING_FED_EXAMPLE_KEY]
self.assertEqual([1, 300, 300, 3], image.shape.as_list())
self.assertEqual(tf.float32, image.dtype)
self.assertEqual(tf.string, receiver_tensors.dtype)