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Python config_util.create_pipeline_proto_from_configs方法代碼示例

本文整理匯總了Python中object_detection.utils.config_util.create_pipeline_proto_from_configs方法的典型用法代碼示例。如果您正苦於以下問題:Python config_util.create_pipeline_proto_from_configs方法的具體用法?Python config_util.create_pipeline_proto_from_configs怎麽用?Python config_util.create_pipeline_proto_from_configs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object_detection.utils.config_util的用法示例。


在下文中一共展示了config_util.create_pipeline_proto_from_configs方法的5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_create_pipeline_proto_from_configs

# 需要導入模塊: from object_detection.utils import config_util [as 別名]
# 或者: from object_detection.utils.config_util import create_pipeline_proto_from_configs [as 別名]
def test_create_pipeline_proto_from_configs(self):
    """Tests that proto can be reconstructed from configs dictionary."""
    pipeline_config_path = os.path.join(self.get_temp_dir(), "pipeline.config")

    pipeline_config = pipeline_pb2.TrainEvalPipelineConfig()
    pipeline_config.model.faster_rcnn.num_classes = 10
    pipeline_config.train_config.batch_size = 32
    pipeline_config.train_input_reader.label_map_path = "path/to/label_map"
    pipeline_config.eval_config.num_examples = 20
    pipeline_config.eval_input_reader.add().queue_capacity = 100
    _write_config(pipeline_config, pipeline_config_path)

    configs = config_util.get_configs_from_pipeline_file(pipeline_config_path)
    pipeline_config_reconstructed = (
        config_util.create_pipeline_proto_from_configs(configs))
    self.assertEqual(pipeline_config, pipeline_config_reconstructed) 
開發者ID:ahmetozlu,項目名稱:vehicle_counting_tensorflow,代碼行數:18,代碼來源:config_util_test.py

示例2: test_save_pipeline_config

# 需要導入模塊: from object_detection.utils import config_util [as 別名]
# 或者: from object_detection.utils.config_util import create_pipeline_proto_from_configs [as 別名]
def test_save_pipeline_config(self):
    """Tests that the pipeline config is properly saved to disk."""
    pipeline_config = pipeline_pb2.TrainEvalPipelineConfig()
    pipeline_config.model.faster_rcnn.num_classes = 10
    pipeline_config.train_config.batch_size = 32
    pipeline_config.train_input_reader.label_map_path = "path/to/label_map"
    pipeline_config.eval_config.num_examples = 20
    pipeline_config.eval_input_reader.add().queue_capacity = 100

    config_util.save_pipeline_config(pipeline_config, self.get_temp_dir())
    configs = config_util.get_configs_from_pipeline_file(
        os.path.join(self.get_temp_dir(), "pipeline.config"))
    pipeline_config_reconstructed = (
        config_util.create_pipeline_proto_from_configs(configs))

    self.assertEqual(pipeline_config, pipeline_config_reconstructed) 
開發者ID:ahmetozlu,項目名稱:vehicle_counting_tensorflow,代碼行數:18,代碼來源:config_util_test.py

示例3: test_create_pipeline_proto_from_configs

# 需要導入模塊: from object_detection.utils import config_util [as 別名]
# 或者: from object_detection.utils.config_util import create_pipeline_proto_from_configs [as 別名]
def test_create_pipeline_proto_from_configs(self):
    """Tests that proto can be reconstructed from configs dictionary."""
    pipeline_config_path = os.path.join(self.get_temp_dir(), "pipeline.config")

    pipeline_config = pipeline_pb2.TrainEvalPipelineConfig()
    pipeline_config.model.faster_rcnn.num_classes = 10
    pipeline_config.train_config.batch_size = 32
    pipeline_config.train_input_reader.label_map_path = "path/to/label_map"
    pipeline_config.eval_config.num_examples = 20
    pipeline_config.eval_input_reader.queue_capacity = 100
    _write_config(pipeline_config, pipeline_config_path)

    configs = config_util.get_configs_from_pipeline_file(pipeline_config_path)
    pipeline_config_reconstructed = (
        config_util.create_pipeline_proto_from_configs(configs))
    self.assertEqual(pipeline_config, pipeline_config_reconstructed) 
開發者ID:cagbal,項目名稱:ros_people_object_detection_tensorflow,代碼行數:18,代碼來源:config_util_test.py

示例4: test_save_pipeline_config

# 需要導入模塊: from object_detection.utils import config_util [as 別名]
# 或者: from object_detection.utils.config_util import create_pipeline_proto_from_configs [as 別名]
def test_save_pipeline_config(self):
    """Tests that the pipeline config is properly saved to disk."""
    pipeline_config = pipeline_pb2.TrainEvalPipelineConfig()
    pipeline_config.model.faster_rcnn.num_classes = 10
    pipeline_config.train_config.batch_size = 32
    pipeline_config.train_input_reader.label_map_path = "path/to/label_map"
    pipeline_config.eval_config.num_examples = 20
    pipeline_config.eval_input_reader.queue_capacity = 100

    config_util.save_pipeline_config(pipeline_config, self.get_temp_dir())
    configs = config_util.get_configs_from_pipeline_file(
        os.path.join(self.get_temp_dir(), "pipeline.config"))
    pipeline_config_reconstructed = (
        config_util.create_pipeline_proto_from_configs(configs))

    self.assertEqual(pipeline_config, pipeline_config_reconstructed) 
開發者ID:ambakick,項目名稱:Person-Detection-and-Tracking,代碼行數:18,代碼來源:config_util_test.py

示例5: create_pipeline_proto_from_configs

# 需要導入模塊: from object_detection.utils import config_util [as 別名]
# 或者: from object_detection.utils.config_util import create_pipeline_proto_from_configs [as 別名]
def create_pipeline_proto_from_configs(configs):
  """Creates a pipeline_pb2.TrainEvalPipelineConfig from configs dictionary.

  This function nearly performs the inverse operation of
  get_configs_from_pipeline_file(). Instead of returning a file path, it returns
  a `TrainEvalPipelineConfig` object.

  Args:
    configs: Dictionary of configs. See get_configs_from_pipeline_file().

  Returns:
    A fully populated pipeline_pb2.TrainEvalPipelineConfig.
  """
  pipeline_config = config_util.create_pipeline_proto_from_configs(configs)
  if "lstm_model" in configs:
    pipeline_config.Extensions[internal_pipeline_pb2.lstm_model].CopyFrom(
        configs["lstm_model"])
  return pipeline_config 
開發者ID:generalized-iou,項目名稱:g-tensorflow-models,代碼行數:20,代碼來源:config_util.py


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