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Python resnet_utils.Block方法代码示例

本文整理汇总了Python中nets.resnet_utils.Block方法的典型用法代码示例。如果您正苦于以下问题:Python resnet_utils.Block方法的具体用法?Python resnet_utils.Block怎么用?Python resnet_utils.Block使用的例子?那么, 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nets.resnet_utils的用法示例。


在下文中一共展示了resnet_utils.Block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: resnet_v2_block

# 需要导入模块: from nets import resnet_utils [as 别名]
# 或者: from nets.resnet_utils import Block [as 别名]
def resnet_v2_block(scope, base_depth, num_units, stride):
  """Helper function for creating a resnet_v2 bottleneck block.

  Args:
    scope: The scope of the block.
    base_depth: The depth of the bottleneck layer for each unit.
    num_units: The number of units in the block.
    stride: The stride of the block, implemented as a stride in the last unit.
      All other units have stride=1.

  Returns:
    A resnet_v2 bottleneck block.
  """
  return resnet_utils.Block(scope, bottleneck, [{
      'depth': base_depth * 4,
      'depth_bottleneck': base_depth,
      'stride': 1
  }] * (num_units - 1) + [{
      'depth': base_depth * 4,
      'depth_bottleneck': base_depth,
      'stride': stride
  }]) 
开发者ID:ringringyi,项目名称:DOTA_models,代码行数:24,代码来源:resnet_v2.py

示例2: resnet_v1_block

# 需要导入模块: from nets import resnet_utils [as 别名]
# 或者: from nets.resnet_utils import Block [as 别名]
def resnet_v1_block(scope, base_depth, num_units, stride):
  """Helper function for creating a resnet_v1 bottleneck block.

  Args:
    scope: The scope of the block.
    base_depth: The depth of the bottleneck layer for each unit.
    num_units: The number of units in the block.
    stride: The stride of the block, implemented as a stride in the last unit.
      All other units have stride=1.

  Returns:
    A resnet_v1 bottleneck block.
  """
  return resnet_utils.Block(scope, bottleneck, [{
      'depth': base_depth * 4,
      'depth_bottleneck': base_depth,
      'stride': 1
  }] * (num_units - 1) + [{
      'depth': base_depth * 4,
      'depth_bottleneck': base_depth,
      'stride': stride
  }]) 
开发者ID:ringringyi,项目名称:DOTA_models,代码行数:24,代码来源:resnet_v1.py

示例3: resnet_v1_50

# 需要导入模块: from nets import resnet_utils [as 别名]
# 或者: from nets.resnet_utils import Block [as 别名]
def resnet_v1_50(inputs,
                 num_classes=None,
                 is_training=True,
                 global_pool=True,
                 output_stride=None,
                 reuse=None,
                 scope='resnet_v1_50'):
  """ResNet-50 model of [1]. See resnet_v1() for arg and return description."""
  blocks = [
      resnet_utils.Block(
          'block1', bottleneck, [(256, 64, 1)] * 2 + [(256, 64, 2)]),
      resnet_utils.Block(
          'block2', bottleneck, [(512, 128, 1)] * 3 + [(512, 128, 2)]),
      resnet_utils.Block(
          'block3', bottleneck, [(1024, 256, 1)] * 5 + [(1024, 256, 2)]),
      resnet_utils.Block(
          'block4', bottleneck, [(2048, 512, 1)] * 3)
  ]
  return resnet_v1(inputs, blocks, num_classes, is_training,
                   global_pool=global_pool, output_stride=output_stride,
                   include_root_block=True, reuse=reuse, scope=scope) 
开发者ID:rayanelleuch,项目名称:Speed-accuracy-trade-offs-for-modern-convolutional-object-detectors,代码行数:23,代码来源:resnet_v1.py

示例4: resnet_v1_101

# 需要导入模块: from nets import resnet_utils [as 别名]
# 或者: from nets.resnet_utils import Block [as 别名]
def resnet_v1_101(inputs,
                  num_classes=None,
                  is_training=True,
                  global_pool=True,
                  output_stride=None,
                  reuse=None,
                  scope='resnet_v1_101'):
  """ResNet-101 model of [1]. See resnet_v1() for arg and return description."""
  blocks = [
      resnet_utils.Block(
          'block1', bottleneck, [(256, 64, 1)] * 2 + [(256, 64, 2)]),
      resnet_utils.Block(
          'block2', bottleneck, [(512, 128, 1)] * 3 + [(512, 128, 2)]),
      resnet_utils.Block(
          'block3', bottleneck, [(1024, 256, 1)] * 22 + [(1024, 256, 2)]),
      resnet_utils.Block(
          'block4', bottleneck, [(2048, 512, 1)] * 3)
  ]
  return resnet_v1(inputs, blocks, num_classes, is_training,
                   global_pool=global_pool, output_stride=output_stride,
                   include_root_block=True, reuse=reuse, scope=scope) 
开发者ID:rayanelleuch,项目名称:Speed-accuracy-trade-offs-for-modern-convolutional-object-detectors,代码行数:23,代码来源:resnet_v1.py

示例5: resnet_v1_152

# 需要导入模块: from nets import resnet_utils [as 别名]
# 或者: from nets.resnet_utils import Block [as 别名]
def resnet_v1_152(inputs,
                  num_classes=None,
                  is_training=True,
                  global_pool=True,
                  output_stride=None,
                  reuse=None,
                  scope='resnet_v1_152'):
  """ResNet-152 model of [1]. See resnet_v1() for arg and return description."""
  blocks = [
      resnet_utils.Block(
          'block1', bottleneck, [(256, 64, 1)] * 2 + [(256, 64, 2)]),
      resnet_utils.Block(
          'block2', bottleneck, [(512, 128, 1)] * 7 + [(512, 128, 2)]),
      resnet_utils.Block(
          'block3', bottleneck, [(1024, 256, 1)] * 35 + [(1024, 256, 2)]),
      resnet_utils.Block(
          'block4', bottleneck, [(2048, 512, 1)] * 3)]
  return resnet_v1(inputs, blocks, num_classes, is_training,
                   global_pool=global_pool, output_stride=output_stride,
                   include_root_block=True, reuse=reuse, scope=scope) 
开发者ID:rayanelleuch,项目名称:Speed-accuracy-trade-offs-for-modern-convolutional-object-detectors,代码行数:22,代码来源:resnet_v1.py

示例6: resnet_v1_200

# 需要导入模块: from nets import resnet_utils [as 别名]
# 或者: from nets.resnet_utils import Block [as 别名]
def resnet_v1_200(inputs,
                  num_classes=None,
                  is_training=True,
                  global_pool=True,
                  output_stride=None,
                  reuse=None,
                  scope='resnet_v1_200'):
  """ResNet-200 model of [2]. See resnet_v1() for arg and return description."""
  blocks = [
      resnet_utils.Block(
          'block1', bottleneck, [(256, 64, 1)] * 2 + [(256, 64, 2)]),
      resnet_utils.Block(
          'block2', bottleneck, [(512, 128, 1)] * 23 + [(512, 128, 2)]),
      resnet_utils.Block(
          'block3', bottleneck, [(1024, 256, 1)] * 35 + [(1024, 256, 2)]),
      resnet_utils.Block(
          'block4', bottleneck, [(2048, 512, 1)] * 3)]
  return resnet_v1(inputs, blocks, num_classes, is_training,
                   global_pool=global_pool, output_stride=output_stride,
                   include_root_block=True, reuse=reuse, scope=scope) 
开发者ID:rayanelleuch,项目名称:Speed-accuracy-trade-offs-for-modern-convolutional-object-detectors,代码行数:22,代码来源:resnet_v1.py


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