Python nets.nets_factory.networks_map() Examples

The following are 25 code examples of nets.nets_factory.networks_map(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module nets.nets_factory , or try the search function .
Example #1
Source File: nets_factory_test.py    From MobileNet with Apache License 2.0 5 votes vote down vote up 
def testGetNetworkFn(self):
    batch_size = 5
    num_classes = 1000
    for net in nets_factory.networks_map:
      with self.test_session():
        net_fn = nets_factory.get_network_fn(net, num_classes)
        # Most networks use 224 as their default_image_size
        image_size = getattr(net_fn, 'default_image_size', 224)
        inputs = tf.random_uniform((batch_size, image_size, image_size, 3))
        logits, end_points = net_fn(inputs)
        self.assertTrue(isinstance(logits, tf.Tensor))
        self.assertTrue(isinstance(end_points, dict))
        self.assertEqual(logits.get_shape().as_list()[0], batch_size)
        self.assertEqual(logits.get_shape().as_list()[-1], num_classes)
Example #2
Source File: nets_factory_test.py    From motion-rcnn with MIT License 5 votes vote down vote up 
def testGetNetworkFn(self):
    batch_size = 5
    num_classes = 1000
    for net in nets_factory.networks_map:
      with self.test_session():
        net_fn = nets_factory.get_network_fn(net, num_classes)
        # Most networks use 224 as their default_image_size
        image_size = getattr(net_fn, 'default_image_size', 224)
        inputs = tf.random_uniform((batch_size, image_size, image_size, 3))
        logits, end_points = net_fn(inputs)
        self.assertTrue(isinstance(logits, tf.Tensor))
        self.assertTrue(isinstance(end_points, dict))
        self.assertEqual(logits.get_shape().as_list()[0], batch_size)
        self.assertEqual(logits.get_shape().as_list()[-1], num_classes)
Example #3
Source File: nets_factory_test.py    From Non-Targeted-Adversarial-Attacks with Apache License 2.0 5 votes vote down vote up 
def testGetNetworkFn(self):
    batch_size = 5
    num_classes = 1000
    for net in nets_factory.networks_map:
      with self.test_session():
        net_fn = nets_factory.get_network_fn(net, num_classes)
        # Most networks use 224 as their default_image_size
        image_size = getattr(net_fn, 'default_image_size', 224)
        inputs = tf.random_uniform((batch_size, image_size, image_size, 3))
        logits, end_points = net_fn(inputs)
        self.assertTrue(isinstance(logits, tf.Tensor))
        self.assertTrue(isinstance(end_points, dict))
        self.assertEqual(logits.get_shape().as_list()[0], batch_size)
        self.assertEqual(logits.get_shape().as_list()[-1], num_classes)
Example #4
Source File: nets_factory_test.py    From HumanRecognition with MIT License 5 votes vote down vote up 
def testGetNetworkFn(self):
    batch_size = 5
    num_classes = 1000
    for net in nets_factory.networks_map:
      with self.test_session():
        net_fn = nets_factory.get_network_fn(net, num_classes)
        # Most networks use 224 as their default_image_size
        image_size = getattr(net_fn, 'default_image_size', 224)
        inputs = tf.random_uniform((batch_size, image_size, image_size, 3))
        logits, end_points = net_fn(inputs)
        self.assertTrue(isinstance(logits, tf.Tensor))
        self.assertTrue(isinstance(end_points, dict))
        self.assertEqual(logits.get_shape().as_list()[0], batch_size)
        self.assertEqual(logits.get_shape().as_list()[-1], num_classes)
Example #5
Source File: nets_factory_test.py    From Optical-Flow-Guided-Feature with MIT License 5 votes vote down vote up 
def testGetNetworkFn(self):
    batch_size = 5
    num_classes = 1000
    for net in nets_factory.networks_map:
      with self.test_session():
        net_fn = nets_factory.get_network_fn(net, num_classes)
        # Most networks use 224 as their default_image_size
        image_size = getattr(net_fn, 'default_image_size', 224)
        inputs = tf.random_uniform((batch_size, image_size, image_size, 3))
        logits, end_points = net_fn(inputs)
        self.assertTrue(isinstance(logits, tf.Tensor))
        self.assertTrue(isinstance(end_points, dict))
        self.assertEqual(logits.get_shape().as_list()[0], batch_size)
        self.assertEqual(logits.get_shape().as_list()[-1], num_classes)
Example #6
Source File: nets_factory_test.py    From hands-detection with MIT License 5 votes vote down vote up 
def testGetNetworkFn(self):
    batch_size = 5
    num_classes = 1000
    for net in nets_factory.networks_map:
      with self.test_session():
        net_fn = nets_factory.get_network_fn(net, num_classes)
        # Most networks use 224 as their default_image_size
        image_size = getattr(net_fn, 'default_image_size', 224)
        inputs = tf.random_uniform((batch_size, image_size, image_size, 3))
        logits, end_points = net_fn(inputs)
        self.assertTrue(isinstance(logits, tf.Tensor))
        self.assertTrue(isinstance(end_points, dict))
        self.assertEqual(logits.get_shape().as_list()[0], batch_size)
        self.assertEqual(logits.get_shape().as_list()[-1], num_classes)
Example #7
Source File: nets_factory_test.py    From ECO-pytorch with BSD 2-Clause "Simplified" License 5 votes vote down vote up 
def testGetNetworkFn(self):
    batch_size = 5
    num_classes = 1000
    for net in nets_factory.networks_map:
      with self.test_session():
        net_fn = nets_factory.get_network_fn(net, num_classes)
        # Most networks use 224 as their default_image_size
        image_size = getattr(net_fn, 'default_image_size', 224)
        inputs = tf.random_uniform((batch_size, image_size, image_size, 3))
        logits, end_points = net_fn(inputs)
        self.assertTrue(isinstance(logits, tf.Tensor))
        self.assertTrue(isinstance(end_points, dict))
        self.assertEqual(logits.get_shape().as_list()[0], batch_size)
        self.assertEqual(logits.get_shape().as_list()[-1], num_classes)
Example #8
Source File: nets_factory_test.py    From Action_Recognition_Zoo with MIT License 5 votes vote down vote up 
def testGetNetworkFn(self):
    batch_size = 5
    num_classes = 1000
    for net in nets_factory.networks_map:
      with self.test_session():
        net_fn = nets_factory.get_network_fn(net, num_classes)
        # Most networks use 224 as their default_image_size
        image_size = getattr(net_fn, 'default_image_size', 224)
        inputs = tf.random_uniform((batch_size, image_size, image_size, 3))
        logits, end_points = net_fn(inputs)
        self.assertTrue(isinstance(logits, tf.Tensor))
        self.assertTrue(isinstance(end_points, dict))
        self.assertEqual(logits.get_shape().as_list()[0], batch_size)
        self.assertEqual(logits.get_shape().as_list()[-1], num_classes)
Example #9
Source File: nets_factory_test.py    From Translation-Invariant-Attacks with Apache License 2.0 5 votes vote down vote up 
def testGetNetworkFn(self):
    batch_size = 5
    num_classes = 1000
    for net in nets_factory.networks_map:
      with self.test_session():
        net_fn = nets_factory.get_network_fn(net, num_classes)
        # Most networks use 224 as their default_image_size
        image_size = getattr(net_fn, 'default_image_size', 224)
        inputs = tf.random_uniform((batch_size, image_size, image_size, 3))
        logits, end_points = net_fn(inputs)
        self.assertTrue(isinstance(logits, tf.Tensor))
        self.assertTrue(isinstance(end_points, dict))
        self.assertEqual(logits.get_shape().as_list()[0], batch_size)
        self.assertEqual(logits.get_shape().as_list()[-1], num_classes)
Example #10
Source File: nets_factory_test.py    From tf_classification with MIT License 5 votes vote down vote up 
def testGetNetworkFn(self):
    batch_size = 5
    num_classes = 1000
    for net in nets_factory.networks_map:
      with self.test_session():
        net_fn = nets_factory.get_network_fn(net, num_classes)
        # Most networks use 224 as their default_image_size
        image_size = getattr(net_fn, 'default_image_size', 224)
        inputs = tf.random_uniform((batch_size, image_size, image_size, 3))
        logits, end_points = net_fn(inputs)
        self.assertTrue(isinstance(logits, tf.Tensor))
        self.assertTrue(isinstance(end_points, dict))
        self.assertEqual(logits.get_shape().as_list()[0], batch_size)
        self.assertEqual(logits.get_shape().as_list()[-1], num_classes)
Example #11
Source File: nets_factory_test.py    From Targeted-Adversarial-Attack with Apache License 2.0 5 votes vote down vote up 
def testGetNetworkFn(self):
    batch_size = 5
    num_classes = 1000
    for net in nets_factory.networks_map:
      with self.test_session():
        net_fn = nets_factory.get_network_fn(net, num_classes)
        # Most networks use 224 as their default_image_size
        image_size = getattr(net_fn, 'default_image_size', 224)
        inputs = tf.random_uniform((batch_size, image_size, image_size, 3))
        logits, end_points = net_fn(inputs)
        self.assertTrue(isinstance(logits, tf.Tensor))
        self.assertTrue(isinstance(end_points, dict))
        self.assertEqual(logits.get_shape().as_list()[0], batch_size)
        self.assertEqual(logits.get_shape().as_list()[-1], num_classes)
Example #12
Source File: nets_factory_test.py    From tumblr-emotions with Apache License 2.0 5 votes vote down vote up 
def testGetNetworkFn(self):
    batch_size = 5
    num_classes = 1000
    for net in nets_factory.networks_map:
      with self.test_session():
        net_fn = nets_factory.get_network_fn(net, num_classes)
        # Most networks use 224 as their default_image_size
        image_size = getattr(net_fn, 'default_image_size', 224)
        inputs = tf.random_uniform((batch_size, image_size, image_size, 3))
        logits, end_points = net_fn(inputs)
        self.assertTrue(isinstance(logits, tf.Tensor))
        self.assertTrue(isinstance(end_points, dict))
        self.assertEqual(logits.get_shape().as_list()[0], batch_size)
        self.assertEqual(logits.get_shape().as_list()[-1], num_classes)
Example #13
Source File: nets_factory_test.py    From tensorflow_yolo2 with MIT License 5 votes vote down vote up 
def testGetNetworkFn(self):
    batch_size = 5
    num_classes = 1000
    for net in nets_factory.networks_map:
      with self.test_session():
        net_fn = nets_factory.get_network_fn(net, num_classes)
        # Most networks use 224 as their default_image_size
        image_size = getattr(net_fn, 'default_image_size', 224)
        inputs = tf.random_uniform((batch_size, image_size, image_size, 3))
        logits, end_points = net_fn(inputs)
        self.assertTrue(isinstance(logits, tf.Tensor))
        self.assertTrue(isinstance(end_points, dict))
        self.assertEqual(logits.get_shape().as_list()[0], batch_size)
        self.assertEqual(logits.get_shape().as_list()[-1], num_classes)
Example #14
Source File: nets_factory_test.py    From DOTA_models with Apache License 2.0 5 votes vote down vote up 
def testGetNetworkFn(self):
    batch_size = 5
    num_classes = 1000
    for net in nets_factory.networks_map:
      with self.test_session():
        net_fn = nets_factory.get_network_fn(net, num_classes)
        # Most networks use 224 as their default_image_size
        image_size = getattr(net_fn, 'default_image_size', 224)
        inputs = tf.random_uniform((batch_size, image_size, image_size, 3))
        logits, end_points = net_fn(inputs)
        self.assertTrue(isinstance(logits, tf.Tensor))
        self.assertTrue(isinstance(end_points, dict))
        self.assertEqual(logits.get_shape().as_list()[0], batch_size)
        self.assertEqual(logits.get_shape().as_list()[-1], num_classes)
Example #15
Source File: nets_factory_test.py    From hops-tensorflow with Apache License 2.0 5 votes vote down vote up 
def testGetNetworkFn(self):
    batch_size = 5
    num_classes = 1000
    for net in nets_factory.networks_map:
      with self.test_session():
        net_fn = nets_factory.get_network_fn(net, num_classes)
        # Most networks use 224 as their default_image_size
        image_size = getattr(net_fn, 'default_image_size', 224)
        inputs = tf.random_uniform((batch_size, image_size, image_size, 3))
        logits, end_points = net_fn(inputs)
        self.assertTrue(isinstance(logits, tf.Tensor))
        self.assertTrue(isinstance(end_points, dict))
        self.assertEqual(logits.get_shape().as_list()[0], batch_size)
        self.assertEqual(logits.get_shape().as_list()[-1], num_classes)
Example #16
Source File: nets_factory_test.py    From terngrad with Apache License 2.0 5 votes vote down vote up 
def testGetNetworkFn(self):
    batch_size = 5
    num_classes = 1000
    for net in nets_factory.networks_map:
      with self.test_session():
        net_fn = nets_factory.get_network_fn(net, num_classes)
        # Most networks use 224 as their default_image_size
        image_size = getattr(net_fn, 'default_image_size', 224)
        inputs = tf.random_uniform((batch_size, image_size, image_size, 3))
        logits, end_points = net_fn(inputs)
        self.assertTrue(isinstance(logits, tf.Tensor))
        self.assertTrue(isinstance(end_points, dict))
        self.assertEqual(logits.get_shape().as_list()[0], batch_size)
        self.assertEqual(logits.get_shape().as_list()[-1], num_classes)
Example #17
Source File: nets_factory_test.py    From 3D-convolutional-speaker-recognition with Apache License 2.0 5 votes vote down vote up 
def testGetNetworkFn(self):
    batch_size = 5
    num_classes = 1000
    for net in nets_factory.networks_map:
      with self.test_session():
        net_fn = nets_factory.get_network_fn(net, num_classes)
        # Most networks use 224 as their default_image_size
        image_size = getattr(net_fn, 'default_image_size', 224)
        inputs = tf.random_uniform((batch_size, image_size, image_size, 3))
        logits, end_points = net_fn(inputs)
        self.assertTrue(isinstance(logits, tf.Tensor))
        self.assertTrue(isinstance(end_points, dict))
        self.assertEqual(logits.get_shape().as_list()[0], batch_size)
        self.assertEqual(logits.get_shape().as_list()[-1], num_classes)
Example #18
Source File: nets_factory_test.py    From 3D-convolutional-speaker-recognition with Apache License 2.0 5 votes vote down vote up 
def testGetNetworkFn(self):
    batch_size = 5
    num_classes = 1000
    for net in nets_factory.networks_map:
      with self.test_session():
        net_fn = nets_factory.get_network_fn(net, num_classes)
        # Most networks use 224 as their default_image_size
        image_size = getattr(net_fn, 'default_image_size', 224)
        inputs = tf.random_uniform((batch_size, image_size, image_size, 3))
        logits, end_points = net_fn(inputs)
        self.assertTrue(isinstance(logits, tf.Tensor))
        self.assertTrue(isinstance(end_points, dict))
        self.assertEqual(logits.get_shape().as_list()[0], batch_size)
        self.assertEqual(logits.get_shape().as_list()[-1], num_classes)
Example #19
Source File: nets_factory_test.py    From 3D-convolutional-speaker-recognition with Apache License 2.0 5 votes vote down vote up 
def testGetNetworkFn(self):
    batch_size = 5
    num_classes = 1000
    for net in nets_factory.networks_map:
      with self.test_session():
        net_fn = nets_factory.get_network_fn(net, num_classes)
        # Most networks use 224 as their default_image_size
        image_size = getattr(net_fn, 'default_image_size', 224)
        inputs = tf.random_uniform((batch_size, image_size, image_size, 3))
        logits, end_points = net_fn(inputs)
        self.assertTrue(isinstance(logits, tf.Tensor))
        self.assertTrue(isinstance(end_points, dict))
        self.assertEqual(logits.get_shape().as_list()[0], batch_size)
        self.assertEqual(logits.get_shape().as_list()[-1], num_classes)
Example #20
Source File: nets_factory_test.py    From RetinaNet_Tensorflow_Rotation with MIT License 5 votes vote down vote up 
def testGetNetworkFn(self):
    batch_size = 5
    num_classes = 1000
    for net in nets_factory.networks_map:
      with self.test_session():
        net_fn = nets_factory.get_network_fn(net, num_classes)
        # Most networks use 224 as their default_image_size
        image_size = getattr(net_fn, 'default_image_size', 224)
        inputs = tf.random_uniform((batch_size, image_size, image_size, 3))
        logits, end_points = net_fn(inputs)
        self.assertTrue(isinstance(logits, tf.Tensor))
        self.assertTrue(isinstance(end_points, dict))
        self.assertEqual(logits.get_shape().as_list()[0], batch_size)
        self.assertEqual(logits.get_shape().as_list()[-1], num_classes)
Example #21
Source File: nets_factory_test.py    From tensorflow-litterbox with Apache License 2.0 5 votes vote down vote up 
def testGetNetworkFn(self):
    batch_size = 5
    num_classes = 1000
    for net in nets_factory.networks_map:
      with self.test_session():
        net_fn = nets_factory.get_network_fn(net, num_classes)
        # Most networks use 224 as their default_image_size
        image_size = getattr(net_fn, 'default_image_size', 224)
        inputs = tf.random_uniform((batch_size, image_size, image_size, 3))
        logits, end_points = net_fn(inputs)
        self.assertTrue(isinstance(logits, tf.Tensor))
        self.assertTrue(isinstance(end_points, dict))
        self.assertEqual(logits.get_shape().as_list()[0], batch_size)
        self.assertEqual(logits.get_shape().as_list()[-1], num_classes)
Example #22
Source File: nets_factory_test.py    From cv-tricks.com with MIT License 5 votes vote down vote up 
def testGetNetworkFn(self):
    batch_size = 5
    num_classes = 1000
    for net in nets_factory.networks_map:
      with self.test_session():
        net_fn = nets_factory.get_network_fn(net, num_classes)
        # Most networks use 224 as their default_image_size
        image_size = getattr(net_fn, 'default_image_size', 224)
        inputs = tf.random_uniform((batch_size, image_size, image_size, 3))
        logits, end_points = net_fn(inputs)
        self.assertTrue(isinstance(logits, tf.Tensor))
        self.assertTrue(isinstance(end_points, dict))
        self.assertEqual(logits.get_shape().as_list()[0], batch_size)
        self.assertEqual(logits.get_shape().as_list()[-1], num_classes)
Example #23
Source File: nets_factory_test.py    From R3Det_Tensorflow with MIT License 5 votes vote down vote up 
def testGetNetworkFn(self):
    batch_size = 5
    num_classes = 1000
    for net in nets_factory.networks_map:
      with self.test_session():
        net_fn = nets_factory.get_network_fn(net, num_classes)
        # Most networks use 224 as their default_image_size
        image_size = getattr(net_fn, 'default_image_size', 224)
        inputs = tf.random_uniform((batch_size, image_size, image_size, 3))
        logits, end_points = net_fn(inputs)
        self.assertTrue(isinstance(logits, tf.Tensor))
        self.assertTrue(isinstance(end_points, dict))
        self.assertEqual(logits.get_shape().as_list()[0], batch_size)
        self.assertEqual(logits.get_shape().as_list()[-1], num_classes)
Example #24
Source File: nets_factory_test.py    From R2CNN-Plus-Plus_Tensorflow with MIT License 5 votes vote down vote up 
def testGetNetworkFn(self):
    batch_size = 5
    num_classes = 1000
    for net in nets_factory.networks_map:
      with self.test_session():
        net_fn = nets_factory.get_network_fn(net, num_classes)
        # Most networks use 224 as their default_image_size
        image_size = getattr(net_fn, 'default_image_size', 224)
        inputs = tf.random_uniform((batch_size, image_size, image_size, 3))
        logits, end_points = net_fn(inputs)
        self.assertTrue(isinstance(logits, tf.Tensor))
        self.assertTrue(isinstance(end_points, dict))
        self.assertEqual(logits.get_shape().as_list()[0], batch_size)
        self.assertEqual(logits.get_shape().as_list()[-1], num_classes)
Example #25
Source File: nets_factory_test.py    From R2CNN_Faster-RCNN_Tensorflow with MIT License 5 votes vote down vote up 
def testGetNetworkFn(self):
    batch_size = 5
    num_classes = 1000
    for net in nets_factory.networks_map:
      with self.test_session():
        net_fn = nets_factory.get_network_fn(net, num_classes)
        # Most networks use 224 as their default_image_size
        image_size = getattr(net_fn, 'default_image_size', 224)
        inputs = tf.random_uniform((batch_size, image_size, image_size, 3))
        logits, end_points = net_fn(inputs)
        self.assertTrue(isinstance(logits, tf.Tensor))
        self.assertTrue(isinstance(end_points, dict))
        self.assertEqual(logits.get_shape().as_list()[0], batch_size)
        self.assertEqual(logits.get_shape().as_list()[-1], num_classes)