本文整理匯總了Python中nets.mobilenet_v1.mobilenet_v1_base方法的典型用法代碼示例。如果您正苦於以下問題：Python mobilenet_v1.mobilenet_v1_base方法的具體用法？Python mobilenet_v1.mobilenet_v1_base怎麽用？Python mobilenet_v1.mobilenet_v1_base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.mobilenet_v1的用法示例。
在下文中一共展示了mobilenet_v1.mobilenet_v1_base方法的4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: testBuildBaseNetwork
# 需要導入模塊: from nets import mobilenet_v1 [as 別名]
# 或者: from nets.mobilenet_v1 import mobilenet_v1_base [as 別名]
def testBuildBaseNetwork(self):
batch_size = 5
height, width = 224, 224
inputs = tf.random_uniform((batch_size, height, width, 3))
net, end_points = mobilenet_v1.mobilenet_v1_base(inputs)
self.assertTrue(net.op.name.startswith('MobilenetV1/Conv2d_13'))
self.assertListEqual(net.get_shape().as_list(),
[batch_size, 7, 7, 1024])
expected_endpoints = ['Conv2d_0',
'Conv2d_1_depthwise', 'Conv2d_1_pointwise',
'Conv2d_2_depthwise', 'Conv2d_2_pointwise',
'Conv2d_3_depthwise', 'Conv2d_3_pointwise',
'Conv2d_4_depthwise', 'Conv2d_4_pointwise',
'Conv2d_5_depthwise', 'Conv2d_5_pointwise',
'Conv2d_6_depthwise', 'Conv2d_6_pointwise',
'Conv2d_7_depthwise', 'Conv2d_7_pointwise',
'Conv2d_8_depthwise', 'Conv2d_8_pointwise',
'Conv2d_9_depthwise', 'Conv2d_9_pointwise',
'Conv2d_10_depthwise', 'Conv2d_10_pointwise',
'Conv2d_11_depthwise', 'Conv2d_11_pointwise',
'Conv2d_12_depthwise', 'Conv2d_12_pointwise',
'Conv2d_13_depthwise', 'Conv2d_13_pointwise']
self.assertItemsEqual(end_points.keys(), expected_endpoints) 示例2: testBuildOnlyUptoFinalEndpoint
# 需要導入模塊: from nets import mobilenet_v1 [as 別名]
# 或者: from nets.mobilenet_v1 import mobilenet_v1_base [as 別名]
def testBuildOnlyUptoFinalEndpoint(self):
batch_size = 5
height, width = 224, 224
endpoints = ['Conv2d_0',
'Conv2d_1_depthwise', 'Conv2d_1_pointwise',
'Conv2d_2_depthwise', 'Conv2d_2_pointwise',
'Conv2d_3_depthwise', 'Conv2d_3_pointwise',
'Conv2d_4_depthwise', 'Conv2d_4_pointwise',
'Conv2d_5_depthwise', 'Conv2d_5_pointwise',
'Conv2d_6_depthwise', 'Conv2d_6_pointwise',
'Conv2d_7_depthwise', 'Conv2d_7_pointwise',
'Conv2d_8_depthwise', 'Conv2d_8_pointwise',
'Conv2d_9_depthwise', 'Conv2d_9_pointwise',
'Conv2d_10_depthwise', 'Conv2d_10_pointwise',
'Conv2d_11_depthwise', 'Conv2d_11_pointwise',
'Conv2d_12_depthwise', 'Conv2d_12_pointwise',
'Conv2d_13_depthwise', 'Conv2d_13_pointwise']
for index, endpoint in enumerate(endpoints):
with tf.Graph().as_default():
inputs = tf.random_uniform((batch_size, height, width, 3))
out_tensor, end_points = mobilenet_v1.mobilenet_v1_base(
inputs, final_endpoint=endpoint)
self.assertTrue(out_tensor.op.name.startswith(
'MobilenetV1/' + endpoint))
self.assertItemsEqual(endpoints[:index+1], end_points) 示例3: testBuildCustomNetworkUsingConvDefs
# 需要導入模塊: from nets import mobilenet_v1 [as 別名]
# 或者: from nets.mobilenet_v1 import mobilenet_v1_base [as 別名]
def testBuildCustomNetworkUsingConvDefs(self):
batch_size = 5
height, width = 224, 224
conv_defs = [
mobilenet_v1.Conv(kernel=[3, 3], stride=2, depth=32),
mobilenet_v1.DepthSepConv(kernel=[3, 3], stride=1, depth=64),
mobilenet_v1.DepthSepConv(kernel=[3, 3], stride=2, depth=128),
mobilenet_v1.DepthSepConv(kernel=[3, 3], stride=1, depth=512)
]
inputs = tf.random_uniform((batch_size, height, width, 3))
net, end_points = mobilenet_v1.mobilenet_v1_base(
inputs, final_endpoint='Conv2d_3_pointwise', conv_defs=conv_defs)
self.assertTrue(net.op.name.startswith('MobilenetV1/Conv2d_3'))
self.assertListEqual(net.get_shape().as_list(),
[batch_size, 56, 56, 512])
expected_endpoints = ['Conv2d_0',
'Conv2d_1_depthwise', 'Conv2d_1_pointwise',
'Conv2d_2_depthwise', 'Conv2d_2_pointwise',
'Conv2d_3_depthwise', 'Conv2d_3_pointwise']
self.assertItemsEqual(end_points.keys(), expected_endpoints) 示例4: testBuildOnlyUptoFinalEndpoint
# 需要導入模塊: from nets import mobilenet_v1 [as 別名]
# 或者: from nets.mobilenet_v1 import mobilenet_v1_base [as 別名]
def testBuildOnlyUptoFinalEndpoint(self):
batch_size = 5
height, width = 224, 224
endpoints = ['Conv2d_0',
'Conv2d_1_depthwise', 'Conv2d_1_pointwise',
'Conv2d_2_depthwise', 'Conv2d_2_pointwise',
'Conv2d_3_depthwise', 'Conv2d_3_pointwise',
'Conv2d_4_depthwise', 'Conv2d_4_pointwise',
'Conv2d_5_depthwise', 'Conv2d_5_pointwise',
'Conv2d_6_depthwise', 'Conv2d_6_pointwise',
'Conv2d_7_depthwise', 'Conv2d_7_pointwise',
'Conv2d_8_depthwise', 'Conv2d_8_pointwise',
'Conv2d_9_depthwise', 'Conv2d_9_pointwise',
'Conv2d_10_depthwise', 'Conv2d_10_pointwise',
'Conv2d_11_depthwise', 'Conv2d_11_pointwise',
'Conv2d_12_depthwise', 'Conv2d_12_pointwise',
'Conv2d_13_depthwise', 'Conv2d_13_pointwise']
for index, endpoint in enumerate(endpoints):
with tf.Graph().as_default():
inputs = tf.random_uniform((batch_size, height, width, 3))
out_tensor, end_points = mobilenet_v1.mobilenet_v1_base(
inputs, final_endpoint=endpoint)
self.assertTrue(out_tensor.op.name.startswith(
'MobilenetV1/' + endpoint))
self.assertItemsEqual(endpoints[:index+1], end_points.keys())