Python resnet_v1.resnet_v1方法代碼示例

本文整理匯總了Python中nets.resnet_v1.resnet_v1方法的典型用法代碼示例。如果您正苦於以下問題：Python resnet_v1.resnet_v1方法的具體用法？Python resnet_v1.resnet_v1怎麽用？Python resnet_v1.resnet_v1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類nets.resnet_v1的用法示例。

在下文中一共展示了resnet_v1.resnet_v1方法的7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: _resnet_small

# 需要導入模塊: from nets import resnet_v1 [as 別名]
# 或者: from nets.resnet_v1 import resnet_v1 [as 別名]
def _resnet_small(self,
                    inputs,
                    num_classes=None,
                    is_training=True,
                    global_pool=True,
                    output_stride=None,
                    include_root_block=True,
                    reuse=None,
                    scope='resnet_v1_small'):
    """A shallow and thin ResNet v1 for faster tests."""
    block = resnet_v1.resnet_v1_block
    blocks = [
        block('block1', base_depth=1, num_units=3, stride=2),
        block('block2', base_depth=2, num_units=3, stride=2),
        block('block3', base_depth=4, num_units=3, stride=2),
        block('block4', base_depth=8, num_units=2, stride=1),
    ]
    return resnet_v1.resnet_v1(inputs, blocks, num_classes,
                               is_training=is_training,
                               global_pool=global_pool,
                               output_stride=output_stride,
                               include_root_block=include_root_block,
                               reuse=reuse,
                               scope=scope)

開發者ID:DetectionTeamUCAS，項目名稱:R2CNN_Faster-RCNN_Tensorflow，代碼行數:26，代碼來源:resnet_v1_test.py

示例2: testEndPointsV1

# 需要導入模塊: from nets import resnet_v1 [as 別名]
# 或者: from nets.resnet_v1 import resnet_v1 [as 別名]
def testEndPointsV1(self):
    """Test the end points of a tiny v1 bottleneck network."""
    bottleneck = resnet_v1.bottleneck
    blocks = [resnet_utils.Block('block1', bottleneck, [(4, 1, 1), (4, 1, 2)]),
              resnet_utils.Block('block2', bottleneck, [(8, 2, 1), (8, 2, 1)])]
    inputs = create_test_input(2, 32, 16, 3)
    with slim.arg_scope(resnet_utils.resnet_arg_scope()):
      _, end_points = self._resnet_plain(inputs, blocks, scope='tiny')
    expected = [
        'tiny/block1/unit_1/bottleneck_v1/shortcut',
        'tiny/block1/unit_1/bottleneck_v1/conv1',
        'tiny/block1/unit_1/bottleneck_v1/conv2',
        'tiny/block1/unit_1/bottleneck_v1/conv3',
        'tiny/block1/unit_2/bottleneck_v1/conv1',
        'tiny/block1/unit_2/bottleneck_v1/conv2',
        'tiny/block1/unit_2/bottleneck_v1/conv3',
        'tiny/block2/unit_1/bottleneck_v1/shortcut',
        'tiny/block2/unit_1/bottleneck_v1/conv1',
        'tiny/block2/unit_1/bottleneck_v1/conv2',
        'tiny/block2/unit_1/bottleneck_v1/conv3',
        'tiny/block2/unit_2/bottleneck_v1/conv1',
        'tiny/block2/unit_2/bottleneck_v1/conv2',
        'tiny/block2/unit_2/bottleneck_v1/conv3']
    self.assertItemsEqual(expected, end_points)

開發者ID:wenwei202，項目名稱:terngrad，代碼行數:26，代碼來源:resnet_v1_test.py

示例3: testEndPointsV1

# 需要導入模塊: from nets import resnet_v1 [as 別名]
# 或者: from nets.resnet_v1 import resnet_v1 [as 別名]
def testEndPointsV1(self):
    """Test the end points of a tiny v1 bottleneck network."""
    blocks = [
        resnet_v1.resnet_v1_block(
            'block1', base_depth=1, num_units=2, stride=2),
        resnet_v1.resnet_v1_block(
            'block2', base_depth=2, num_units=2, stride=1),
    ]
    inputs = create_test_input(2, 32, 16, 3)
    with slim.arg_scope(resnet_utils.resnet_arg_scope()):
      _, end_points = self._resnet_plain(inputs, blocks, scope='tiny')
    expected = [
        'tiny/block1/unit_1/bottleneck_v1/shortcut',
        'tiny/block1/unit_1/bottleneck_v1/conv1',
        'tiny/block1/unit_1/bottleneck_v1/conv2',
        'tiny/block1/unit_1/bottleneck_v1/conv3',
        'tiny/block1/unit_2/bottleneck_v1/conv1',
        'tiny/block1/unit_2/bottleneck_v1/conv2',
        'tiny/block1/unit_2/bottleneck_v1/conv3',
        'tiny/block2/unit_1/bottleneck_v1/shortcut',
        'tiny/block2/unit_1/bottleneck_v1/conv1',
        'tiny/block2/unit_1/bottleneck_v1/conv2',
        'tiny/block2/unit_1/bottleneck_v1/conv3',
        'tiny/block2/unit_2/bottleneck_v1/conv1',
        'tiny/block2/unit_2/bottleneck_v1/conv2',
        'tiny/block2/unit_2/bottleneck_v1/conv3']
    self.assertItemsEqual(expected, end_points)

開發者ID:ringringyi，項目名稱:DOTA_models，代碼行數:29，代碼來源:resnet_v1_test.py

示例4: _resnet_small

# 需要導入模塊: from nets import resnet_v1 [as 別名]
# 或者: from nets.resnet_v1 import resnet_v1 [as 別名]
def _resnet_small(self,
                    inputs,
                    num_classes=None,
                    is_training=True,
                    global_pool=True,
                    output_stride=None,
                    include_root_block=True,
                    spatial_squeeze=True,
                    reuse=None,
                    scope='resnet_v1_small'):
    """A shallow and thin ResNet v1 for faster tests."""
    block = resnet_v1.resnet_v1_block
    blocks = [
        block('block1', base_depth=1, num_units=3, stride=2),
        block('block2', base_depth=2, num_units=3, stride=2),
        block('block3', base_depth=4, num_units=3, stride=2),
        block('block4', base_depth=8, num_units=2, stride=1),
    ]
    return resnet_v1.resnet_v1(inputs, blocks, num_classes,
                               is_training=is_training,
                               global_pool=global_pool,
                               output_stride=output_stride,
                               include_root_block=include_root_block,
                               spatial_squeeze=spatial_squeeze,
                               reuse=reuse,
                               scope=scope)

開發者ID:ringringyi，項目名稱:DOTA_models，代碼行數:28，代碼來源:resnet_v1_test.py

示例5: testEndPointsV1

# 需要導入模塊: from nets import resnet_v1 [as 別名]
# 或者: from nets.resnet_v1 import resnet_v1 [as 別名]
def testEndPointsV1(self):
    """Test the end points of a tiny v1 bottleneck network."""
    blocks = [
        resnet_v1.resnet_v1_block(
            'block1', base_depth=1, num_units=2, stride=2),
        resnet_v1.resnet_v1_block(
            'block2', base_depth=2, num_units=2, stride=1),
    ]
    inputs = create_test_input(2, 32, 16, 3)
    with slim.arg_scope(resnet_utils.resnet_arg_scope()):
      _, end_points = self._resnet_plain(inputs, blocks, scope='tiny')
    expected = [
        'tiny/block1/unit_1/bottleneck_v1/shortcut',
        'tiny/block1/unit_1/bottleneck_v1/conv1',
        'tiny/block1/unit_1/bottleneck_v1/conv2',
        'tiny/block1/unit_1/bottleneck_v1/conv3',
        'tiny/block1/unit_2/bottleneck_v1/conv1',
        'tiny/block1/unit_2/bottleneck_v1/conv2',
        'tiny/block1/unit_2/bottleneck_v1/conv3',
        'tiny/block2/unit_1/bottleneck_v1/shortcut',
        'tiny/block2/unit_1/bottleneck_v1/conv1',
        'tiny/block2/unit_1/bottleneck_v1/conv2',
        'tiny/block2/unit_1/bottleneck_v1/conv3',
        'tiny/block2/unit_2/bottleneck_v1/conv1',
        'tiny/block2/unit_2/bottleneck_v1/conv2',
        'tiny/block2/unit_2/bottleneck_v1/conv3']
    self.assertItemsEqual(expected, end_points.keys())

開發者ID:leimao，項目名稱:DeepLab_v3，代碼行數:29，代碼來源:resnet_v1_test.py

示例6: testEndPointsV1

# 需要導入模塊: from nets import resnet_v1 [as 別名]
# 或者: from nets.resnet_v1 import resnet_v1 [as 別名]
def testEndPointsV1(self):
    """Test the end points of a tiny v1 bottleneck network."""
    blocks = [
        resnet_v1.resnet_v1_block(
            'block1', base_depth=1, num_units=2, stride=2),
        resnet_v1.resnet_v1_block(
            'block2', base_depth=2, num_units=2, stride=1),
    ]
    inputs = create_test_input(2, 32, 16, 3)
    with slim.arg_scope(resnet_utils.resnet_arg_scope()):
      _, end_points = self._resnet_plain(inputs, blocks, scope='tiny')
    expected = [
        'tiny/block1/unit_1/bottleneck_v1/shortcut',
        'tiny/block1/unit_1/bottleneck_v1/conv1',
        'tiny/block1/unit_1/bottleneck_v1/conv2',
        'tiny/block1/unit_1/bottleneck_v1/conv3',
        'tiny/block1/unit_2/bottleneck_v1/conv1',
        'tiny/block1/unit_2/bottleneck_v1/conv2',
        'tiny/block1/unit_2/bottleneck_v1/conv3',
        'tiny/block2/unit_1/bottleneck_v1/shortcut',
        'tiny/block2/unit_1/bottleneck_v1/conv1',
        'tiny/block2/unit_1/bottleneck_v1/conv2',
        'tiny/block2/unit_1/bottleneck_v1/conv3',
        'tiny/block2/unit_2/bottleneck_v1/conv1',
        'tiny/block2/unit_2/bottleneck_v1/conv2',
        'tiny/block2/unit_2/bottleneck_v1/conv3']
    self.assertItemsEqual(expected, list(end_points.keys()))

開發者ID:google-research，項目名稱:morph-net，代碼行數:29，代碼來源:resnet_v1_test.py

示例7: testMinBaseDepth

# 需要導入模塊: from nets import resnet_v1 [as 別名]
# 或者: from nets.resnet_v1 import resnet_v1 [as 別名]
def testMinBaseDepth(self):
    resnets = [
        resnet_v1.resnet_v1_50, resnet_v1.resnet_v1_101,
        resnet_v1.resnet_v1_152, resnet_v1.resnet_v1_200
    ]
    resnet_names = [
        'resnet_v1_50', 'resnet_v1_101', 'resnet_v1_152', 'resnet_v1_200'
    ]
    for resnet, resnet_name in zip(resnets, resnet_names):
      min_base_depth = 5
      global_pool = True
      num_classes = 10
      inputs = create_test_input(2, 224, 224, 3)
      with slim.arg_scope(resnet_utils.resnet_arg_scope()):
        _, end_points = resnet(
            inputs,
            num_classes,
            global_pool=global_pool,
            min_base_depth=min_base_depth,
            depth_multiplier=0,
            scope=resnet_name)
        for block in ['block1', 'block2', 'block3', 'block4']:
          block_name = resnet_name + '/' + block
          self.assertTrue(block_name in end_points)
          self.assertEqual(
              len(end_points[block_name].get_shape().as_list()), 4)
          # The output depth is 4 times base_depth.
          depth_expected = min_base_depth * 4
          self.assertEqual(
              end_points[block_name].get_shape().as_list()[3], depth_expected)

開發者ID:google-research，項目名稱:morph-net，代碼行數:32，代碼來源:resnet_v1_test.py

注：本文中的nets.resnet_v1.resnet_v1方法示例由純淨天空整理自Github/MSDocs等開源代碼及文檔管理平台，相關代碼片段篩選自各路編程大神貢獻的開源項目，源碼版權歸原作者所有，傳播和使用請參考對應項目的License；未經允許，請勿轉載。