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Python vgg.vgg_a方法代码示例

本文整理汇总了Python中nets.vgg.vgg_a方法的典型用法代码示例。如果您正苦于以下问题:Python vgg.vgg_a方法的具体用法?Python vgg.vgg_a怎么用?Python vgg.vgg_a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.vgg的用法示例。


在下文中一共展示了vgg.vgg_a方法的9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: testEndPoints

# 需要导入模块: from nets import vgg [as 别名]
# 或者: from nets.vgg import vgg_a [as 别名]
def testEndPoints(self):
    batch_size = 5
    height, width = 224, 224
    num_classes = 1000
    with self.test_session():
      inputs = tf.random_uniform((batch_size, height, width, 3))
      _, end_points = vgg.vgg_a(inputs, num_classes)
      expected_names = ['vgg_a/conv1/conv1_1',
                        'vgg_a/pool1',
                        'vgg_a/conv2/conv2_1',
                        'vgg_a/pool2',
                        'vgg_a/conv3/conv3_1',
                        'vgg_a/conv3/conv3_2',
                        'vgg_a/pool3',
                        'vgg_a/conv4/conv4_1',
                        'vgg_a/conv4/conv4_2',
                        'vgg_a/pool4',
                        'vgg_a/conv5/conv5_1',
                        'vgg_a/conv5/conv5_2',
                        'vgg_a/pool5',
                        'vgg_a/fc6',
                        'vgg_a/fc7',
                        'vgg_a/fc8'
                       ]
      self.assertSetEqual(set(end_points.keys()), set(expected_names)) 
开发者ID:ringringyi,项目名称:DOTA_models,代码行数:27,代码来源:vgg_test.py

示例2: testNoClasses

# 需要导入模块: from nets import vgg [as 别名]
# 或者: from nets.vgg import vgg_a [as 别名]
def testNoClasses(self):
    batch_size = 5
    height, width = 224, 224
    num_classes = None
    with self.test_session():
      inputs = tf.random_uniform((batch_size, height, width, 3))
      net, end_points = vgg.vgg_a(inputs, num_classes)
      expected_names = ['vgg_a/conv1/conv1_1',
                        'vgg_a/pool1',
                        'vgg_a/conv2/conv2_1',
                        'vgg_a/pool2',
                        'vgg_a/conv3/conv3_1',
                        'vgg_a/conv3/conv3_2',
                        'vgg_a/pool3',
                        'vgg_a/conv4/conv4_1',
                        'vgg_a/conv4/conv4_2',
                        'vgg_a/pool4',
                        'vgg_a/conv5/conv5_1',
                        'vgg_a/conv5/conv5_2',
                        'vgg_a/pool5',
                        'vgg_a/fc6',
                        'vgg_a/fc7',
                       ]
      self.assertSetEqual(set(end_points.keys()), set(expected_names))
      self.assertTrue(net.op.name.startswith('vgg_a/fc7')) 
开发者ID:leimao,项目名称:DeepLab_v3,代码行数:27,代码来源:vgg_test.py

示例3: testTrainEvalWithReuse

# 需要导入模块: from nets import vgg [as 别名]
# 或者: from nets.vgg import vgg_a [as 别名]
def testTrainEvalWithReuse(self):
    train_batch_size = 2
    eval_batch_size = 1
    train_height, train_width = 224, 224
    eval_height, eval_width = 256, 256
    num_classes = 1000
    with self.test_session():
      train_inputs = tf.random_uniform(
          (train_batch_size, train_height, train_width, 3))
      logits, _ = vgg.vgg_a(train_inputs)
      self.assertListEqual(logits.get_shape().as_list(),
                           [train_batch_size, num_classes])
      tf.get_variable_scope().reuse_variables()
      eval_inputs = tf.random_uniform(
          (eval_batch_size, eval_height, eval_width, 3))
      logits, _ = vgg.vgg_a(eval_inputs, is_training=False,
                            spatial_squeeze=False)
      self.assertListEqual(logits.get_shape().as_list(),
                           [eval_batch_size, 2, 2, num_classes])
      logits = tf.reduce_mean(logits, [1, 2])
      predictions = tf.argmax(logits, 1)
      self.assertEquals(predictions.get_shape().as_list(), [eval_batch_size]) 
开发者ID:leimao,项目名称:DeepLab_v3,代码行数:24,代码来源:vgg_test.py

示例4: testBuild

# 需要导入模块: from nets import vgg [as 别名]
# 或者: from nets.vgg import vgg_a [as 别名]
def testBuild(self):
    batch_size = 5
    height, width = 224, 224
    num_classes = 1000
    with self.test_session():
      inputs = tf.random_uniform((batch_size, height, width, 3))
      logits, _ = vgg.vgg_a(inputs, num_classes)
      self.assertEquals(logits.op.name, 'vgg_a/fc8/squeezed')
      self.assertListEqual(logits.get_shape().as_list(),
                           [batch_size, num_classes]) 
开发者ID:ringringyi,项目名称:DOTA_models,代码行数:12,代码来源:vgg_test.py

示例5: testFullyConvolutional

# 需要导入模块: from nets import vgg [as 别名]
# 或者: from nets.vgg import vgg_a [as 别名]
def testFullyConvolutional(self):
    batch_size = 1
    height, width = 256, 256
    num_classes = 1000
    with self.test_session():
      inputs = tf.random_uniform((batch_size, height, width, 3))
      logits, _ = vgg.vgg_a(inputs, num_classes, spatial_squeeze=False)
      self.assertEquals(logits.op.name, 'vgg_a/fc8/BiasAdd')
      self.assertListEqual(logits.get_shape().as_list(),
                           [batch_size, 2, 2, num_classes]) 
开发者ID:ringringyi,项目名称:DOTA_models,代码行数:12,代码来源:vgg_test.py

示例6: testModelVariables

# 需要导入模块: from nets import vgg [as 别名]
# 或者: from nets.vgg import vgg_a [as 别名]
def testModelVariables(self):
    batch_size = 5
    height, width = 224, 224
    num_classes = 1000
    with self.test_session():
      inputs = tf.random_uniform((batch_size, height, width, 3))
      vgg.vgg_a(inputs, num_classes)
      expected_names = ['vgg_a/conv1/conv1_1/weights',
                        'vgg_a/conv1/conv1_1/biases',
                        'vgg_a/conv2/conv2_1/weights',
                        'vgg_a/conv2/conv2_1/biases',
                        'vgg_a/conv3/conv3_1/weights',
                        'vgg_a/conv3/conv3_1/biases',
                        'vgg_a/conv3/conv3_2/weights',
                        'vgg_a/conv3/conv3_2/biases',
                        'vgg_a/conv4/conv4_1/weights',
                        'vgg_a/conv4/conv4_1/biases',
                        'vgg_a/conv4/conv4_2/weights',
                        'vgg_a/conv4/conv4_2/biases',
                        'vgg_a/conv5/conv5_1/weights',
                        'vgg_a/conv5/conv5_1/biases',
                        'vgg_a/conv5/conv5_2/weights',
                        'vgg_a/conv5/conv5_2/biases',
                        'vgg_a/fc6/weights',
                        'vgg_a/fc6/biases',
                        'vgg_a/fc7/weights',
                        'vgg_a/fc7/biases',
                        'vgg_a/fc8/weights',
                        'vgg_a/fc8/biases',
                       ]
      model_variables = [v.op.name for v in slim.get_model_variables()]
      self.assertSetEqual(set(model_variables), set(expected_names)) 
开发者ID:ringringyi,项目名称:DOTA_models,代码行数:34,代码来源:vgg_test.py

示例7: testEvaluation

# 需要导入模块: from nets import vgg [as 别名]
# 或者: from nets.vgg import vgg_a [as 别名]
def testEvaluation(self):
    batch_size = 2
    height, width = 224, 224
    num_classes = 1000
    with self.test_session():
      eval_inputs = tf.random_uniform((batch_size, height, width, 3))
      logits, _ = vgg.vgg_a(eval_inputs, is_training=False)
      self.assertListEqual(logits.get_shape().as_list(),
                           [batch_size, num_classes])
      predictions = tf.argmax(logits, 1)
      self.assertListEqual(predictions.get_shape().as_list(), [batch_size]) 
开发者ID:ringringyi,项目名称:DOTA_models,代码行数:13,代码来源:vgg_test.py

示例8: testForward

# 需要导入模块: from nets import vgg [as 别名]
# 或者: from nets.vgg import vgg_a [as 别名]
def testForward(self):
    batch_size = 1
    height, width = 224, 224
    with self.test_session() as sess:
      inputs = tf.random_uniform((batch_size, height, width, 3))
      logits, _ = vgg.vgg_a(inputs)
      sess.run(tf.global_variables_initializer())
      output = sess.run(logits)
      self.assertTrue(output.any()) 
开发者ID:ringringyi,项目名称:DOTA_models,代码行数:11,代码来源:vgg_test.py

示例9: testGlobalPool

# 需要导入模块: from nets import vgg [as 别名]
# 或者: from nets.vgg import vgg_a [as 别名]
def testGlobalPool(self):
    batch_size = 1
    height, width = 256, 256
    num_classes = 1000
    with self.test_session():
      inputs = tf.random_uniform((batch_size, height, width, 3))
      logits, _ = vgg.vgg_a(inputs, num_classes, spatial_squeeze=False,
                            global_pool=True)
      self.assertEquals(logits.op.name, 'vgg_a/fc8/BiasAdd')
      self.assertListEqual(logits.get_shape().as_list(),
                           [batch_size, 1, 1, num_classes]) 
开发者ID:leimao,项目名称:DeepLab_v3,代码行数:13,代码来源:vgg_test.py


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