这里的源码是从train.py开始看的。之后还有eval.py

train.py

在trian.py中config文件，被分成三分

  model_config = configs['model']
  train_config = configs['train_config']
  input_config = configs['train_input_config']

moedel_config是构建模型的文件。

  model_fn = functools.partial(
      model_builder.build,
      model_config=model_config,
      is_training=True)

在model_bulider.py中build会选择模型种类

def build(model_config, is_training):
  """Builds a DetectionModel based on the model config.

  Args:
    model_config: A model.proto object containing the config for the desired
      DetectionModel.
    is_training: True if this model is being built for training purposes.

  Returns:
    DetectionModel based on the config.

  Raises:
    ValueError: On invalid meta architecture or model.
  """
  if not isinstance(model_config, model_pb2.DetectionModel):
    raise ValueError('model_config not of type model_pb2.DetectionModel.')
  meta_architecture = model_config.WhichOneof('model')
  if meta_architecture == 'ssd':
    return _build_ssd_model(model_config.ssd, is_training)
  if meta_architecture == 'faster_rcnn':
    return _build_faster_rcnn_model(model_config.faster_rcnn, is_training)
  raise ValueError('Unknown meta architecture: {}'.format(meta_architecture))

如果你选择faster-rcnn,在model_builder.py中这些都是构建faster-rcnn模型的参数

如果你有兴趣,在protos/model_pb2.py有很多model_config的默认值

这时候模型已经构建完了

回到train.py中

  train_config = configs['train_config']

发现这是对trainer.py进行的配置文件，在trainer.py的train函数中，如下：

在protos/train_pb2.py中的默认配置如下：

_descriptor.FieldDescriptor(
      name='batch_size', full_name='object_detection.protos.TrainConfig.batch_size', index=0,
      number=1, type=13, cpp_type=3, label=1,
      has_default_value=True, default_value=32,
      message_type=None, enum_type=None, containing_type=None,
      is_extension=False, extension_scope=None,
      options=None),
    _descriptor.FieldDescriptor(
      name='data_augmentation_options', full_name='object_detection.protos.TrainConfig.data_augmentation_options', index=1,
      number=2, type=11, cpp_type=10, label=3,
      has_default_value=False, default_value=[],
      message_type=None, enum_type=None, containing_type=None,
      is_extension=False, extension_scope=None,
      options=None),
    _descriptor.FieldDescriptor(
      name='sync_replicas', full_name='object_detection.protos.TrainConfig.sync_replicas', index=2,
      number=3, type=8, cpp_type=7, label=1,
      has_default_value=True, default_value=False,
      message_type=None, enum_type=None, containing_type=None,
      is_extension=False, extension_scope=None,
      options=None),
    _descriptor.FieldDescriptor(
      name='keep_checkpoint_every_n_hours', full_name='object_detection.protos.TrainConfig.keep_checkpoint_every_n_hours', index=3,
      number=4, type=13, cpp_type=3, label=1,
      has_default_value=True, default_value=1000,
      message_type=None, enum_type=None, containing_type=None,
      is_extension=False, extension_scope=None,
      options=None),
    _descriptor.FieldDescriptor(
      name='optimizer', full_name='object_detection.protos.TrainConfig.optimizer', index=4,
      number=5, type=11, cpp_type=10, label=1,
      has_default_value=False, default_value=None,
      message_type=None, enum_type=None, containing_type=None,
      is_extension=False, extension_scope=None,
      options=None),
    _descriptor.FieldDescriptor(
      name='gradient_clipping_by_norm', full_name='object_detection.protos.TrainConfig.gradient_clipping_by_norm', index=5,
      number=6, type=2, cpp_type=6, label=1,
      has_default_value=True, default_value=0,
      message_type=None, enum_type=None, containing_type=None,
      is_extension=False, extension_scope=None,
      options=None),
    _descriptor.FieldDescriptor(
      name='fine_tune_checkpoint', full_name='object_detection.protos.TrainConfig.fine_tune_checkpoint', index=6,
      number=7, type=9, cpp_type=9, label=1,
      has_default_value=True, default_value=_b("").decode('utf-8'),
      message_type=None, enum_type=None, containing_type=None,
      is_extension=False, extension_scope=None,
      options=None),
    _descriptor.FieldDescriptor(
      name='from_detection_checkpoint', full_name='object_detection.protos.TrainConfig.from_detection_checkpoint', index=7,
      number=8, type=8, cpp_type=7, label=1,
      has_default_value=True, default_value=False,
      message_type=None, enum_type=None, containing_type=None,
      is_extension=False, extension_scope=None,
      options=None),
    _descriptor.FieldDescriptor(
      name='num_steps', full_name='object_detection.protos.TrainConfig.num_steps', index=8,
      number=9, type=13, cpp_type=3, label=1,
      has_default_value=True, default_value=0,
      message_type=None, enum_type=None, containing_type=None,
      is_extension=False, extension_scope=None,
      options=None),
    _descriptor.FieldDescriptor(
      name='startup_delay_steps', full_name='object_detection.protos.TrainConfig.startup_delay_steps', index=9,
      number=10, type=2, cpp_type=6, label=1,
      has_default_value=True, default_value=15,
      message_type=None, enum_type=None, containing_type=None,
      is_extension=False, extension_scope=None,
      options=None),
    _descriptor.FieldDescriptor(
      name='bias_grad_multiplier', full_name='object_detection.protos.TrainConfig.bias_grad_multiplier', index=10,
      number=11, type=2, cpp_type=6, label=1,
      has_default_value=True, default_value=0,
      message_type=None, enum_type=None, containing_type=None,
      is_extension=False, extension_scope=None,
      options=None),
    _descriptor.FieldDescriptor(
      name='freeze_variables', full_name='object_detection.protos.TrainConfig.freeze_variables', index=11,
      number=12, type=9, cpp_type=9, label=3,
      has_default_value=False, default_value=[],
      message_type=None, enum_type=None, containing_type=None,
      is_extension=False, extension_scope=None,
      options=None),
    _descriptor.FieldDescriptor(
      name='replicas_to_aggregate', full_name='object_detection.protos.TrainConfig.replicas_to_aggregate', index=12,
      number=13, type=5, cpp_type=1, label=1,
      has_default_value=True, default_value=1,
      message_type=None, enum_type=None, containing_type=None,
      is_extension=False, extension_scope=None,
      options=None),
    _descriptor.FieldDescriptor(
      name='batch_queue_capacity', full_name='object_detection.protos.TrainConfig.batch_queue_capacity', index=13,
      number=14, type=5, cpp_type=1, label=1,
      has_default_value=True, default_value=150,
      message_type=None, enum_type=None, containing_type=None,
      is_extension=False, extension_scope=None,
      options=None),
    _descriptor.FieldDescriptor(
      name='num_batch_queue_threads', full_name='object_detection.protos.TrainConfig.num_batch_queue_threads', index=14,
      number=15, type=5, cpp_type=1, label=1,
      has_default_value=True, default_value=8,
      message_type=None, enum_type=None, containing_type=None,
      is_extension=False, extension_scope=None,
      options=None),
    _descriptor.FieldDescriptor(
      name='prefetch_queue_capacity', full_name='object_detection.protos.TrainConfig.prefetch_queue_capacity', index=15,
      number=16, type=5, cpp_type=1, label=1,
      has_default_value=True, default_value=5,
      message_type=None, enum_type=None, containing_type=None,
      is_extension=False, extension_scope=None,
      options=None),
    _descriptor.FieldDescriptor(
      name='merge_multiple_label_boxes', full_name='object_detection.protos.TrainConfig.merge_multiple_label_boxes', index=16,
      number=17, type=8, cpp_type=7, label=1,
      has_default_value=True, default_value=False,
      message_type=None, enum_type=None, containing_type=None,
      is_extension=False, extension_scope=None,
      options=None),

再看input_config

 input_config = configs['train_input_config']

在builder/input_reader_builder中

input_reader_pb2中默认值：

    _descriptor.FieldDescriptor(
      name='label_map_path', full_name='object_detection.protos.InputReader.label_map_path', index=0,
      number=1, type=9, cpp_type=9, label=1,
      has_default_value=True, default_value=_b("").decode('utf-8'),
      message_type=None, enum_type=None, containing_type=None,
      is_extension=False, extension_scope=None,
      options=None),
    _descriptor.FieldDescriptor(
      name='shuffle', full_name='object_detection.protos.InputReader.shuffle', index=1,
      number=2, type=8, cpp_type=7, label=1,
      has_default_value=True, default_value=True,
      message_type=None, enum_type=None, containing_type=None,
      is_extension=False, extension_scope=None,
      options=None),
    _descriptor.FieldDescriptor(
      name='queue_capacity', full_name='object_detection.protos.InputReader.queue_capacity', index=2,
      number=3, type=13, cpp_type=3, label=1,
      has_default_value=True, default_value=2000,
      message_type=None, enum_type=None, containing_type=None,
      is_extension=False, extension_scope=None,
      options=None),
    _descriptor.FieldDescriptor(
      name='min_after_dequeue', full_name='object_detection.protos.InputReader.min_after_dequeue', index=3,
      number=4, type=13, cpp_type=3, label=1,
      has_default_value=True, default_value=1000,
      message_type=None, enum_type=None, containing_type=None,
      is_extension=False, extension_scope=None,
      options=None),
    _descriptor.FieldDescriptor(
      name='num_epochs', full_name='object_detection.protos.InputReader.num_epochs', index=4,
      number=5, type=13, cpp_type=3, label=1,
      has_default_value=True, default_value=0,
      message_type=None, enum_type=None, containing_type=None,
      is_extension=False, extension_scope=None,
      options=None),
    _descriptor.FieldDescriptor(
      name='num_readers', full_name='object_detection.protos.InputReader.num_readers', index=5,
      number=6, type=13, cpp_type=3, label=1,
      has_default_value=True, default_value=8,
      message_type=None, enum_type=None, containing_type=None,
      is_extension=False, extension_scope=None,
      options=None),
    _descriptor.FieldDescriptor(
      name='load_instance_masks', full_name='object_detection.protos.InputReader.load_instance_masks', index=6,
      number=7, type=8, cpp_type=7, label=1,
      has_default_value=True, default_value=False,
      message_type=None, enum_type=None, containing_type=None,
      is_extension=False, extension_scope=None,
      options=None),
    _descriptor.FieldDescriptor(
      name='tf_record_input_reader', full_name='object_detection.protos.InputReader.tf_record_input_reader', index=7,
      number=8, type=11, cpp_type=10, label=1,
      has_default_value=False, default_value=None,
      message_type=None, enum_type=None, containing_type=None,
      is_extension=False, extension_scope=None,
      options=None),
    _descriptor.FieldDescriptor(
      name='external_input_reader', full_name='object_detection.protos.InputReader.external_input_reader', index=8,
      number=9, type=11, cpp_type=10, label=1,
      has_default_value=False, default_value=None,
      message_type=None, enum_type=None, containing_type=None,
      is_extension=False, extension_scope=None,
      options=None),

value.py

在value.py中也是被分为三个部分

  model_config = configs['model']
  eval_config = configs['eval_config']
  if FLAGS.eval_training_data:
    input_config = configs['train_input_config']
  else:
    input_config = configs['eval_input_config']

这里

eval_config = configs['eval_config']

为新增的一个配置文件，进行计算评估用的一个文件。

evaluator.py文件使用了这里的config文件参数

文件开头的几种分数评估方式。

EVAL_METRICS_CLASS_DICT = {
    'pascal_voc_metrics':
        object_detection_evaluation.PascalDetectionEvaluator,
    'weighted_pascal_voc_metrics':
        object_detection_evaluation.WeightedPascalDetectionEvaluator,
    'open_images_metrics':
        object_detection_evaluation.OpenImagesDetectionEvaluator
}

eval_pb2.py文件中的eval_config的默认值。

_descriptor.FieldDescriptor(
      name='num_visualizations', full_name='object_detection.protos.EvalConfig.num_visualizations', index=0,
      number=1, type=13, cpp_type=3, label=1,
      has_default_value=True, default_value=10,
      message_type=None, enum_type=None, containing_type=None,
      is_extension=False, extension_scope=None,
      options=None),
    _descriptor.FieldDescriptor(
      name='num_examples', full_name='object_detection.protos.EvalConfig.num_examples', index=1,
      number=2, type=13, cpp_type=3, label=1,
      has_default_value=True, default_value=5000,
      message_type=None, enum_type=None, containing_type=None,
      is_extension=False, extension_scope=None,
      options=None),
    _descriptor.FieldDescriptor(
      name='eval_interval_secs', full_name='object_detection.protos.EvalConfig.eval_interval_secs', index=2,
      number=3, type=13, cpp_type=3, label=1,
      has_default_value=True, default_value=300,
      message_type=None, enum_type=None, containing_type=None,
      is_extension=False, extension_scope=None,
      options=None),
    _descriptor.FieldDescriptor(
      name='max_evals', full_name='object_detection.protos.EvalConfig.max_evals', index=3,
      number=4, type=13, cpp_type=3, label=1,
      has_default_value=True, default_value=0,
      message_type=None, enum_type=None, containing_type=None,
      is_extension=False, extension_scope=None,
      options=None),
    _descriptor.FieldDescriptor(
      name='save_graph', full_name='object_detection.protos.EvalConfig.save_graph', index=4,
      number=5, type=8, cpp_type=7, label=1,
      has_default_value=True, default_value=False,
      message_type=None, enum_type=None, containing_type=None,
      is_extension=False, extension_scope=None,
      options=None),
    _descriptor.FieldDescriptor(
      name='visualization_export_dir', full_name='object_detection.protos.EvalConfig.visualization_export_dir', index=5,
      number=6, type=9, cpp_type=9, label=1,
      has_default_value=True, default_value=_b("").decode('utf-8'),
      message_type=None, enum_type=None, containing_type=None,
      is_extension=False, extension_scope=None,
      options=None),
    _descriptor.FieldDescriptor(
      name='eval_master', full_name='object_detection.protos.EvalConfig.eval_master', index=6,
      number=7, type=9, cpp_type=9, label=1,
      has_default_value=True, default_value=_b("").decode('utf-8'),
      message_type=None, enum_type=None, containing_type=None,
      is_extension=False, extension_scope=None,
      options=None),
    _descriptor.FieldDescriptor(
      name='metrics_set', full_name='object_detection.protos.EvalConfig.metrics_set', index=7,
      number=8, type=9, cpp_type=9, label=1,
      has_default_value=True, default_value=_b("pascal_voc_metrics").decode('utf-8'),
      message_type=None, enum_type=None, containing_type=None,
      is_extension=False, extension_scope=None,
      options=None),
    _descriptor.FieldDescriptor(
      name='export_path', full_name='object_detection.protos.EvalConfig.export_path', index=8,
      number=9, type=9, cpp_type=9, label=1,
      has_default_value=True, default_value=_b("").decode('utf-8'),
      message_type=None, enum_type=None, containing_type=None,
      is_extension=False, extension_scope=None,
      options=None),
    _descriptor.FieldDescriptor(
      name='ignore_groundtruth', full_name='object_detection.protos.EvalConfig.ignore_groundtruth', index=9,
      number=10, type=8, cpp_type=7, label=1,
      has_default_value=True, default_value=False,
      message_type=None, enum_type=None, containing_type=None,
      is_extension=False, extension_scope=None,
      options=None),
    _descriptor.FieldDescriptor(
      name='use_moving_averages', full_name='object_detection.protos.EvalConfig.use_moving_averages', index=10,
      number=11, type=8, cpp_type=7, label=1,
      has_default_value=True, default_value=False,
      message_type=None, enum_type=None, containing_type=None,
      is_extension=False, extension_scope=None,
      options=None),
    _descriptor.FieldDescriptor(
      name='eval_instance_masks', full_name='object_detection.protos.EvalConfig.eval_instance_masks', index=11,
      number=12, type=8, cpp_type=7, label=1,
      has_default_value=True, default_value=False,
      message_type=None, enum_type=None, containing_type=None,
      is_extension=False, extension_scope=None,
      options=None)

所有的超参数的默认值都可以在config文件中进行修改。