Python nets.inception.inception_v3_base() Examples

The following are 30 code examples of nets.inception.inception_v3_base(). 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.inception , or try the search function .
Example #1
Source File: inception_v3_test.py    From Hands-On-Machine-Learning-with-OpenCV-4 with MIT License 6 votes vote down vote up 
def testBuildOnlyUptoFinalEndpoint(self):
    batch_size = 5
    height, width = 299, 299
    endpoints = ['Conv2d_1a_3x3', 'Conv2d_2a_3x3', 'Conv2d_2b_3x3',
                 'MaxPool_3a_3x3', 'Conv2d_3b_1x1', 'Conv2d_4a_3x3',
                 'MaxPool_5a_3x3', 'Mixed_5b', 'Mixed_5c', 'Mixed_5d',
                 'Mixed_6a', 'Mixed_6b', 'Mixed_6c', 'Mixed_6d',
                 'Mixed_6e', 'Mixed_7a', 'Mixed_7b', 'Mixed_7c']

    for index, endpoint in enumerate(endpoints):
      with tf.Graph().as_default():
        inputs = tf.random_uniform((batch_size, height, width, 3))
        out_tensor, end_points = inception.inception_v3_base(
            inputs, final_endpoint=endpoint)
        self.assertTrue(out_tensor.op.name.startswith(
            'InceptionV3/' + endpoint))
        self.assertItemsEqual(endpoints[:index+1], end_points)
Example #2
Source File: inception_v3_test.py    From DeepLab_v3 with MIT License 6 votes vote down vote up 
def testBuildBaseNetwork(self):
    batch_size = 5
    height, width = 299, 299

    inputs = tf.random_uniform((batch_size, height, width, 3))
    final_endpoint, end_points = inception.inception_v3_base(inputs)
    self.assertTrue(final_endpoint.op.name.startswith(
        'InceptionV3/Mixed_7c'))
    self.assertListEqual(final_endpoint.get_shape().as_list(),
                         [batch_size, 8, 8, 2048])
    expected_endpoints = ['Conv2d_1a_3x3', 'Conv2d_2a_3x3', 'Conv2d_2b_3x3',
                          'MaxPool_3a_3x3', 'Conv2d_3b_1x1', 'Conv2d_4a_3x3',
                          'MaxPool_5a_3x3', 'Mixed_5b', 'Mixed_5c', 'Mixed_5d',
                          'Mixed_6a', 'Mixed_6b', 'Mixed_6c', 'Mixed_6d',
                          'Mixed_6e', 'Mixed_7a', 'Mixed_7b', 'Mixed_7c']
    self.assertItemsEqual(end_points.keys(), expected_endpoints)
Example #3
Source File: inception_v3_test.py    From R2CNN-Plus-Plus_Tensorflow with MIT License 6 votes vote down vote up 
def testBuildOnlyUptoFinalEndpoint(self):
    batch_size = 5
    height, width = 299, 299
    endpoints = ['Conv2d_1a_3x3', 'Conv2d_2a_3x3', 'Conv2d_2b_3x3',
                 'MaxPool_3a_3x3', 'Conv2d_3b_1x1', 'Conv2d_4a_3x3',
                 'MaxPool_5a_3x3', 'Mixed_5b', 'Mixed_5c', 'Mixed_5d',
                 'Mixed_6a', 'Mixed_6b', 'Mixed_6c', 'Mixed_6d',
                 'Mixed_6e', 'Mixed_7a', 'Mixed_7b', 'Mixed_7c']

    for index, endpoint in enumerate(endpoints):
      with tf.Graph().as_default():
        inputs = tf.random_uniform((batch_size, height, width, 3))
        out_tensor, end_points = inception.inception_v3_base(
            inputs, final_endpoint=endpoint)
        self.assertTrue(out_tensor.op.name.startswith(
            'InceptionV3/' + endpoint))
        self.assertItemsEqual(endpoints[:index+1], end_points)
Example #4
Source File: inception_v3_test.py    From ctw-baseline with MIT License 6 votes vote down vote up 
def testBuildOnlyUptoFinalEndpoint(self):
    batch_size = 5
    height, width = 299, 299
    endpoints = ['Conv2d_1a_3x3', 'Conv2d_2a_3x3', 'Conv2d_2b_3x3',
                 'MaxPool_3a_3x3', 'Conv2d_3b_1x1', 'Conv2d_4a_3x3',
                 'MaxPool_5a_3x3', 'Mixed_5b', 'Mixed_5c', 'Mixed_5d',
                 'Mixed_6a', 'Mixed_6b', 'Mixed_6c', 'Mixed_6d',
                 'Mixed_6e', 'Mixed_7a', 'Mixed_7b', 'Mixed_7c']

    for index, endpoint in enumerate(endpoints):
      with tf.Graph().as_default():
        inputs = tf.random_uniform((batch_size, height, width, 3))
        out_tensor, end_points = inception.inception_v3_base(
            inputs, final_endpoint=endpoint)
        self.assertTrue(out_tensor.op.name.startswith(
            'InceptionV3/' + endpoint))
        self.assertItemsEqual(endpoints[:index+1], end_points)
Example #5
Source File: inception_v3_test.py    From CVTron with Apache License 2.0 6 votes vote down vote up 
def testBuildBaseNetwork(self):
    batch_size = 5
    height, width = 299, 299

    inputs = tf.random_uniform((batch_size, height, width, 3))
    final_endpoint, end_points = inception.inception_v3_base(inputs)
    self.assertTrue(final_endpoint.op.name.startswith(
        'InceptionV3/Mixed_7c'))
    self.assertListEqual(final_endpoint.get_shape().as_list(),
                         [batch_size, 8, 8, 2048])
    expected_endpoints = ['Conv2d_1a_3x3', 'Conv2d_2a_3x3', 'Conv2d_2b_3x3',
                          'MaxPool_3a_3x3', 'Conv2d_3b_1x1', 'Conv2d_4a_3x3',
                          'MaxPool_5a_3x3', 'Mixed_5b', 'Mixed_5c', 'Mixed_5d',
                          'Mixed_6a', 'Mixed_6b', 'Mixed_6c', 'Mixed_6d',
                          'Mixed_6e', 'Mixed_7a', 'Mixed_7b', 'Mixed_7c']
    self.assertItemsEqual(end_points.keys(), expected_endpoints)
Example #6
Source File: inception_v3_test.py    From CVTron with Apache License 2.0 6 votes vote down vote up 
def testBuildOnlyUptoFinalEndpoint(self):
    batch_size = 5
    height, width = 299, 299
    endpoints = ['Conv2d_1a_3x3', 'Conv2d_2a_3x3', 'Conv2d_2b_3x3',
                 'MaxPool_3a_3x3', 'Conv2d_3b_1x1', 'Conv2d_4a_3x3',
                 'MaxPool_5a_3x3', 'Mixed_5b', 'Mixed_5c', 'Mixed_5d',
                 'Mixed_6a', 'Mixed_6b', 'Mixed_6c', 'Mixed_6d',
                 'Mixed_6e', 'Mixed_7a', 'Mixed_7b', 'Mixed_7c']

    for index, endpoint in enumerate(endpoints):
      with tf.Graph().as_default():
        inputs = tf.random_uniform((batch_size, height, width, 3))
        out_tensor, end_points = inception.inception_v3_base(
            inputs, final_endpoint=endpoint)
        self.assertTrue(out_tensor.op.name.startswith(
            'InceptionV3/' + endpoint))
        self.assertItemsEqual(endpoints[:index+1], end_points.keys())
Example #7
Source File: inception_v3_test.py    From edafa with MIT License 6 votes vote down vote up 
def testBuildBaseNetwork(self):
    batch_size = 5
    height, width = 299, 299

    inputs = tf.random_uniform((batch_size, height, width, 3))
    final_endpoint, end_points = inception.inception_v3_base(inputs)
    self.assertTrue(final_endpoint.op.name.startswith(
        'InceptionV3/Mixed_7c'))
    self.assertListEqual(final_endpoint.get_shape().as_list(),
                         [batch_size, 8, 8, 2048])
    expected_endpoints = ['Conv2d_1a_3x3', 'Conv2d_2a_3x3', 'Conv2d_2b_3x3',
                          'MaxPool_3a_3x3', 'Conv2d_3b_1x1', 'Conv2d_4a_3x3',
                          'MaxPool_5a_3x3', 'Mixed_5b', 'Mixed_5c', 'Mixed_5d',
                          'Mixed_6a', 'Mixed_6b', 'Mixed_6c', 'Mixed_6d',
                          'Mixed_6e', 'Mixed_7a', 'Mixed_7b', 'Mixed_7c']
    self.assertItemsEqual(end_points.keys(), expected_endpoints)
Example #8
Source File: inception_v3_test.py    From edafa with MIT License 6 votes vote down vote up 
def testBuildOnlyUptoFinalEndpoint(self):
    batch_size = 5
    height, width = 299, 299
    endpoints = ['Conv2d_1a_3x3', 'Conv2d_2a_3x3', 'Conv2d_2b_3x3',
                 'MaxPool_3a_3x3', 'Conv2d_3b_1x1', 'Conv2d_4a_3x3',
                 'MaxPool_5a_3x3', 'Mixed_5b', 'Mixed_5c', 'Mixed_5d',
                 'Mixed_6a', 'Mixed_6b', 'Mixed_6c', 'Mixed_6d',
                 'Mixed_6e', 'Mixed_7a', 'Mixed_7b', 'Mixed_7c']

    for index, endpoint in enumerate(endpoints):
      with tf.Graph().as_default():
        inputs = tf.random_uniform((batch_size, height, width, 3))
        out_tensor, end_points = inception.inception_v3_base(
            inputs, final_endpoint=endpoint)
        self.assertTrue(out_tensor.op.name.startswith(
            'InceptionV3/' + endpoint))
        self.assertItemsEqual(endpoints[:index+1], end_points.keys())
Example #9
Source File: inception_v3_test.py    From cv-tricks.com with MIT License 6 votes vote down vote up 
def testBuildBaseNetwork(self):
    batch_size = 5
    height, width = 299, 299

    inputs = tf.random_uniform((batch_size, height, width, 3))
    final_endpoint, end_points = inception.inception_v3_base(inputs)
    self.assertTrue(final_endpoint.op.name.startswith(
        'InceptionV3/Mixed_7c'))
    self.assertListEqual(final_endpoint.get_shape().as_list(),
                         [batch_size, 8, 8, 2048])
    expected_endpoints = ['Conv2d_1a_3x3', 'Conv2d_2a_3x3', 'Conv2d_2b_3x3',
                          'MaxPool_3a_3x3', 'Conv2d_3b_1x1', 'Conv2d_4a_3x3',
                          'MaxPool_5a_3x3', 'Mixed_5b', 'Mixed_5c', 'Mixed_5d',
                          'Mixed_6a', 'Mixed_6b', 'Mixed_6c', 'Mixed_6d',
                          'Mixed_6e', 'Mixed_7a', 'Mixed_7b', 'Mixed_7c']
    self.assertItemsEqual(end_points.keys(), expected_endpoints)
Example #10
Source File: inception_v3_test.py    From cv-tricks.com with MIT License 6 votes vote down vote up 
def testBuildOnlyUptoFinalEndpoint(self):
    batch_size = 5
    height, width = 299, 299
    endpoints = ['Conv2d_1a_3x3', 'Conv2d_2a_3x3', 'Conv2d_2b_3x3',
                 'MaxPool_3a_3x3', 'Conv2d_3b_1x1', 'Conv2d_4a_3x3',
                 'MaxPool_5a_3x3', 'Mixed_5b', 'Mixed_5c', 'Mixed_5d',
                 'Mixed_6a', 'Mixed_6b', 'Mixed_6c', 'Mixed_6d',
                 'Mixed_6e', 'Mixed_7a', 'Mixed_7b', 'Mixed_7c']

    for index, endpoint in enumerate(endpoints):
      with tf.Graph().as_default():
        inputs = tf.random_uniform((batch_size, height, width, 3))
        out_tensor, end_points = inception.inception_v3_base(
            inputs, final_endpoint=endpoint)
        self.assertTrue(out_tensor.op.name.startswith(
            'InceptionV3/' + endpoint))
        self.assertItemsEqual(endpoints[:index+1], end_points)
Example #11
Source File: inception_v3_test.py    From garbage-object-detection-tensorflow with MIT License 6 votes vote down vote up 
def testBuildBaseNetwork(self):
    batch_size = 5
    height, width = 299, 299

    inputs = tf.random_uniform((batch_size, height, width, 3))
    final_endpoint, end_points = inception.inception_v3_base(inputs)
    self.assertTrue(final_endpoint.op.name.startswith(
        'InceptionV3/Mixed_7c'))
    self.assertListEqual(final_endpoint.get_shape().as_list(),
                         [batch_size, 8, 8, 2048])
    expected_endpoints = ['Conv2d_1a_3x3', 'Conv2d_2a_3x3', 'Conv2d_2b_3x3',
                          'MaxPool_3a_3x3', 'Conv2d_3b_1x1', 'Conv2d_4a_3x3',
                          'MaxPool_5a_3x3', 'Mixed_5b', 'Mixed_5c', 'Mixed_5d',
                          'Mixed_6a', 'Mixed_6b', 'Mixed_6c', 'Mixed_6d',
                          'Mixed_6e', 'Mixed_7a', 'Mixed_7b', 'Mixed_7c']
    self.assertItemsEqual(end_points.keys(), expected_endpoints)
Example #12
Source File: inception_v3_test.py    From garbage-object-detection-tensorflow with MIT License 6 votes vote down vote up 
def testBuildOnlyUptoFinalEndpoint(self):
    batch_size = 5
    height, width = 299, 299
    endpoints = ['Conv2d_1a_3x3', 'Conv2d_2a_3x3', 'Conv2d_2b_3x3',
                 'MaxPool_3a_3x3', 'Conv2d_3b_1x1', 'Conv2d_4a_3x3',
                 'MaxPool_5a_3x3', 'Mixed_5b', 'Mixed_5c', 'Mixed_5d',
                 'Mixed_6a', 'Mixed_6b', 'Mixed_6c', 'Mixed_6d',
                 'Mixed_6e', 'Mixed_7a', 'Mixed_7b', 'Mixed_7c']

    for index, endpoint in enumerate(endpoints):
      with tf.Graph().as_default():
        inputs = tf.random_uniform((batch_size, height, width, 3))
        out_tensor, end_points = inception.inception_v3_base(
            inputs, final_endpoint=endpoint)
        self.assertTrue(out_tensor.op.name.startswith(
            'InceptionV3/' + endpoint))
        self.assertItemsEqual(endpoints[:index+1], end_points)
Example #13
Source File: inception_v3_test.py    From yolo_v2 with Apache License 2.0 6 votes vote down vote up 
def testBuildBaseNetwork(self):
    batch_size = 5
    height, width = 299, 299

    inputs = tf.random_uniform((batch_size, height, width, 3))
    final_endpoint, end_points = inception.inception_v3_base(inputs)
    self.assertTrue(final_endpoint.op.name.startswith(
        'InceptionV3/Mixed_7c'))
    self.assertListEqual(final_endpoint.get_shape().as_list(),
                         [batch_size, 8, 8, 2048])
    expected_endpoints = ['Conv2d_1a_3x3', 'Conv2d_2a_3x3', 'Conv2d_2b_3x3',
                          'MaxPool_3a_3x3', 'Conv2d_3b_1x1', 'Conv2d_4a_3x3',
                          'MaxPool_5a_3x3', 'Mixed_5b', 'Mixed_5c', 'Mixed_5d',
                          'Mixed_6a', 'Mixed_6b', 'Mixed_6c', 'Mixed_6d',
                          'Mixed_6e', 'Mixed_7a', 'Mixed_7b', 'Mixed_7c']
    self.assertItemsEqual(end_points.keys(), expected_endpoints)
Example #14
Source File: inception_v3_test.py    From yolo_v2 with Apache License 2.0 6 votes vote down vote up 
def testBuildOnlyUptoFinalEndpoint(self):
    batch_size = 5
    height, width = 299, 299
    endpoints = ['Conv2d_1a_3x3', 'Conv2d_2a_3x3', 'Conv2d_2b_3x3',
                 'MaxPool_3a_3x3', 'Conv2d_3b_1x1', 'Conv2d_4a_3x3',
                 'MaxPool_5a_3x3', 'Mixed_5b', 'Mixed_5c', 'Mixed_5d',
                 'Mixed_6a', 'Mixed_6b', 'Mixed_6c', 'Mixed_6d',
                 'Mixed_6e', 'Mixed_7a', 'Mixed_7b', 'Mixed_7c']

    for index, endpoint in enumerate(endpoints):
      with tf.Graph().as_default():
        inputs = tf.random_uniform((batch_size, height, width, 3))
        out_tensor, end_points = inception.inception_v3_base(
            inputs, final_endpoint=endpoint)
        self.assertTrue(out_tensor.op.name.startswith(
            'InceptionV3/' + endpoint))
        self.assertItemsEqual(endpoints[:index+1], end_points)
Example #15
Source File: inception_v3_test.py    From Hands-On-Machine-Learning-with-OpenCV-4 with MIT License 6 votes vote down vote up 
def testBuildBaseNetwork(self):
    batch_size = 5
    height, width = 299, 299

    inputs = tf.random_uniform((batch_size, height, width, 3))
    final_endpoint, end_points = inception.inception_v3_base(inputs)
    self.assertTrue(final_endpoint.op.name.startswith(
        'InceptionV3/Mixed_7c'))
    self.assertListEqual(final_endpoint.get_shape().as_list(),
                         [batch_size, 8, 8, 2048])
    expected_endpoints = ['Conv2d_1a_3x3', 'Conv2d_2a_3x3', 'Conv2d_2b_3x3',
                          'MaxPool_3a_3x3', 'Conv2d_3b_1x1', 'Conv2d_4a_3x3',
                          'MaxPool_5a_3x3', 'Mixed_5b', 'Mixed_5c', 'Mixed_5d',
                          'Mixed_6a', 'Mixed_6b', 'Mixed_6c', 'Mixed_6d',
                          'Mixed_6e', 'Mixed_7a', 'Mixed_7b', 'Mixed_7c']
    self.assertItemsEqual(end_points.keys(), expected_endpoints)
Example #16
Source File: inception_v3_test.py    From DOTA_models with Apache License 2.0 6 votes vote down vote up 
def testBuildOnlyUptoFinalEndpoint(self):
    batch_size = 5
    height, width = 299, 299
    endpoints = ['Conv2d_1a_3x3', 'Conv2d_2a_3x3', 'Conv2d_2b_3x3',
                 'MaxPool_3a_3x3', 'Conv2d_3b_1x1', 'Conv2d_4a_3x3',
                 'MaxPool_5a_3x3', 'Mixed_5b', 'Mixed_5c', 'Mixed_5d',
                 'Mixed_6a', 'Mixed_6b', 'Mixed_6c', 'Mixed_6d',
                 'Mixed_6e', 'Mixed_7a', 'Mixed_7b', 'Mixed_7c']

    for index, endpoint in enumerate(endpoints):
      with tf.Graph().as_default():
        inputs = tf.random_uniform((batch_size, height, width, 3))
        out_tensor, end_points = inception.inception_v3_base(
            inputs, final_endpoint=endpoint)
        self.assertTrue(out_tensor.op.name.startswith(
            'InceptionV3/' + endpoint))
        self.assertItemsEqual(endpoints[:index+1], end_points)
Example #17
Source File: inception_v3_test.py    From RetinaNet_Tensorflow_Rotation with MIT License 6 votes vote down vote up 
def testBuildBaseNetwork(self):
    batch_size = 5
    height, width = 299, 299

    inputs = tf.random_uniform((batch_size, height, width, 3))
    final_endpoint, end_points = inception.inception_v3_base(inputs)
    self.assertTrue(final_endpoint.op.name.startswith(
        'InceptionV3/Mixed_7c'))
    self.assertListEqual(final_endpoint.get_shape().as_list(),
                         [batch_size, 8, 8, 2048])
    expected_endpoints = ['Conv2d_1a_3x3', 'Conv2d_2a_3x3', 'Conv2d_2b_3x3',
                          'MaxPool_3a_3x3', 'Conv2d_3b_1x1', 'Conv2d_4a_3x3',
                          'MaxPool_5a_3x3', 'Mixed_5b', 'Mixed_5c', 'Mixed_5d',
                          'Mixed_6a', 'Mixed_6b', 'Mixed_6c', 'Mixed_6d',
                          'Mixed_6e', 'Mixed_7a', 'Mixed_7b', 'Mixed_7c']
    self.assertItemsEqual(end_points.keys(), expected_endpoints)
Example #18
Source File: inception_v3_test.py    From RetinaNet_Tensorflow_Rotation with MIT License 6 votes vote down vote up 
def testBuildOnlyUptoFinalEndpoint(self):
    batch_size = 5
    height, width = 299, 299
    endpoints = ['Conv2d_1a_3x3', 'Conv2d_2a_3x3', 'Conv2d_2b_3x3',
                 'MaxPool_3a_3x3', 'Conv2d_3b_1x1', 'Conv2d_4a_3x3',
                 'MaxPool_5a_3x3', 'Mixed_5b', 'Mixed_5c', 'Mixed_5d',
                 'Mixed_6a', 'Mixed_6b', 'Mixed_6c', 'Mixed_6d',
                 'Mixed_6e', 'Mixed_7a', 'Mixed_7b', 'Mixed_7c']

    for index, endpoint in enumerate(endpoints):
      with tf.Graph().as_default():
        inputs = tf.random_uniform((batch_size, height, width, 3))
        out_tensor, end_points = inception.inception_v3_base(
            inputs, final_endpoint=endpoint)
        self.assertTrue(out_tensor.op.name.startswith(
            'InceptionV3/' + endpoint))
        self.assertItemsEqual(endpoints[:index+1], end_points)
Example #19
Source File: inception_v3_test.py    From CBAM-tensorflow-slim with MIT License 6 votes vote down vote up 
def testBuildBaseNetwork(self):
    batch_size = 5
    height, width = 299, 299

    inputs = tf.random_uniform((batch_size, height, width, 3))
    final_endpoint, end_points = inception.inception_v3_base(inputs)
    self.assertTrue(final_endpoint.op.name.startswith(
        'InceptionV3/Mixed_7c'))
    self.assertListEqual(final_endpoint.get_shape().as_list(),
                         [batch_size, 8, 8, 2048])
    expected_endpoints = ['Conv2d_1a_3x3', 'Conv2d_2a_3x3', 'Conv2d_2b_3x3',
                          'MaxPool_3a_3x3', 'Conv2d_3b_1x1', 'Conv2d_4a_3x3',
                          'MaxPool_5a_3x3', 'Mixed_5b', 'Mixed_5c', 'Mixed_5d',
                          'Mixed_6a', 'Mixed_6b', 'Mixed_6c', 'Mixed_6d',
                          'Mixed_6e', 'Mixed_7a', 'Mixed_7b', 'Mixed_7c']
    self.assertItemsEqual(end_points.keys(), expected_endpoints)
Example #20
Source File: inception_v3_test.py    From CBAM-tensorflow-slim with MIT License 6 votes vote down vote up 
def testBuildOnlyUptoFinalEndpoint(self):
    batch_size = 5
    height, width = 299, 299
    endpoints = ['Conv2d_1a_3x3', 'Conv2d_2a_3x3', 'Conv2d_2b_3x3',
                 'MaxPool_3a_3x3', 'Conv2d_3b_1x1', 'Conv2d_4a_3x3',
                 'MaxPool_5a_3x3', 'Mixed_5b', 'Mixed_5c', 'Mixed_5d',
                 'Mixed_6a', 'Mixed_6b', 'Mixed_6c', 'Mixed_6d',
                 'Mixed_6e', 'Mixed_7a', 'Mixed_7b', 'Mixed_7c']

    for index, endpoint in enumerate(endpoints):
      with tf.Graph().as_default():
        inputs = tf.random_uniform((batch_size, height, width, 3))
        out_tensor, end_points = inception.inception_v3_base(
            inputs, final_endpoint=endpoint)
        self.assertTrue(out_tensor.op.name.startswith(
            'InceptionV3/' + endpoint))
        self.assertItemsEqual(endpoints[:index+1], end_points.keys())
Example #21
Source File: inception_v3_test.py    From Gun-Detector with Apache License 2.0 6 votes vote down vote up 
def testBuildBaseNetwork(self):
    batch_size = 5
    height, width = 299, 299

    inputs = tf.random_uniform((batch_size, height, width, 3))
    final_endpoint, end_points = inception.inception_v3_base(inputs)
    self.assertTrue(final_endpoint.op.name.startswith(
        'InceptionV3/Mixed_7c'))
    self.assertListEqual(final_endpoint.get_shape().as_list(),
                         [batch_size, 8, 8, 2048])
    expected_endpoints = ['Conv2d_1a_3x3', 'Conv2d_2a_3x3', 'Conv2d_2b_3x3',
                          'MaxPool_3a_3x3', 'Conv2d_3b_1x1', 'Conv2d_4a_3x3',
                          'MaxPool_5a_3x3', 'Mixed_5b', 'Mixed_5c', 'Mixed_5d',
                          'Mixed_6a', 'Mixed_6b', 'Mixed_6c', 'Mixed_6d',
                          'Mixed_6e', 'Mixed_7a', 'Mixed_7b', 'Mixed_7c']
    self.assertItemsEqual(end_points.keys(), expected_endpoints)
Example #22
Source File: inception_v3_test.py    From Gun-Detector with Apache License 2.0 6 votes vote down vote up 
def testBuildOnlyUptoFinalEndpoint(self):
    batch_size = 5
    height, width = 299, 299
    endpoints = ['Conv2d_1a_3x3', 'Conv2d_2a_3x3', 'Conv2d_2b_3x3',
                 'MaxPool_3a_3x3', 'Conv2d_3b_1x1', 'Conv2d_4a_3x3',
                 'MaxPool_5a_3x3', 'Mixed_5b', 'Mixed_5c', 'Mixed_5d',
                 'Mixed_6a', 'Mixed_6b', 'Mixed_6c', 'Mixed_6d',
                 'Mixed_6e', 'Mixed_7a', 'Mixed_7b', 'Mixed_7c']

    for index, endpoint in enumerate(endpoints):
      with tf.Graph().as_default():
        inputs = tf.random_uniform((batch_size, height, width, 3))
        out_tensor, end_points = inception.inception_v3_base(
            inputs, final_endpoint=endpoint)
        self.assertTrue(out_tensor.op.name.startswith(
            'InceptionV3/' + endpoint))
        self.assertItemsEqual(endpoints[:index+1], end_points.keys())
Example #23
Source File: inception_v3_test.py    From Creative-Adversarial-Networks with MIT License 6 votes vote down vote up 
def testBuildBaseNetwork(self):
    batch_size = 5
    height, width = 299, 299

    inputs = tf.random_uniform((batch_size, height, width, 3))
    final_endpoint, end_points = inception.inception_v3_base(inputs)
    self.assertTrue(final_endpoint.op.name.startswith(
        'InceptionV3/Mixed_7c'))
    self.assertListEqual(final_endpoint.get_shape().as_list(),
                         [batch_size, 8, 8, 2048])
    expected_endpoints = ['Conv2d_1a_3x3', 'Conv2d_2a_3x3', 'Conv2d_2b_3x3',
                          'MaxPool_3a_3x3', 'Conv2d_3b_1x1', 'Conv2d_4a_3x3',
                          'MaxPool_5a_3x3', 'Mixed_5b', 'Mixed_5c', 'Mixed_5d',
                          'Mixed_6a', 'Mixed_6b', 'Mixed_6c', 'Mixed_6d',
                          'Mixed_6e', 'Mixed_7a', 'Mixed_7b', 'Mixed_7c']
    self.assertItemsEqual(end_points.keys(), expected_endpoints)
Example #24
Source File: inception_v3_test.py    From Creative-Adversarial-Networks with MIT License 6 votes vote down vote up 
def testBuildOnlyUptoFinalEndpoint(self):
    batch_size = 5
    height, width = 299, 299
    endpoints = ['Conv2d_1a_3x3', 'Conv2d_2a_3x3', 'Conv2d_2b_3x3',
                 'MaxPool_3a_3x3', 'Conv2d_3b_1x1', 'Conv2d_4a_3x3',
                 'MaxPool_5a_3x3', 'Mixed_5b', 'Mixed_5c', 'Mixed_5d',
                 'Mixed_6a', 'Mixed_6b', 'Mixed_6c', 'Mixed_6d',
                 'Mixed_6e', 'Mixed_7a', 'Mixed_7b', 'Mixed_7c']

    for index, endpoint in enumerate(endpoints):
      with tf.Graph().as_default():
        inputs = tf.random_uniform((batch_size, height, width, 3))
        out_tensor, end_points = inception.inception_v3_base(
            inputs, final_endpoint=endpoint)
        self.assertTrue(out_tensor.op.name.startswith(
            'InceptionV3/' + endpoint))
        self.assertItemsEqual(endpoints[:index+1], end_points)
Example #25
Source File: inception_v3_test.py    From BMW-TensorFlow-Training-GUI with Apache License 2.0 6 votes vote down vote up 
def testBuildBaseNetwork(self):
    batch_size = 5
    height, width = 299, 299

    inputs = tf.random_uniform((batch_size, height, width, 3))
    final_endpoint, end_points = inception.inception_v3_base(inputs)
    self.assertTrue(final_endpoint.op.name.startswith(
        'InceptionV3/Mixed_7c'))
    self.assertListEqual(final_endpoint.get_shape().as_list(),
                         [batch_size, 8, 8, 2048])
    expected_endpoints = ['Conv2d_1a_3x3', 'Conv2d_2a_3x3', 'Conv2d_2b_3x3',
                          'MaxPool_3a_3x3', 'Conv2d_3b_1x1', 'Conv2d_4a_3x3',
                          'MaxPool_5a_3x3', 'Mixed_5b', 'Mixed_5c', 'Mixed_5d',
                          'Mixed_6a', 'Mixed_6b', 'Mixed_6c', 'Mixed_6d',
                          'Mixed_6e', 'Mixed_7a', 'Mixed_7b', 'Mixed_7c']
    self.assertItemsEqual(end_points.keys(), expected_endpoints)
Example #26
Source File: inception_v3_test.py    From BMW-TensorFlow-Training-GUI with Apache License 2.0 6 votes vote down vote up 
def testBuildOnlyUptoFinalEndpoint(self):
    batch_size = 5
    height, width = 299, 299
    endpoints = ['Conv2d_1a_3x3', 'Conv2d_2a_3x3', 'Conv2d_2b_3x3',
                 'MaxPool_3a_3x3', 'Conv2d_3b_1x1', 'Conv2d_4a_3x3',
                 'MaxPool_5a_3x3', 'Mixed_5b', 'Mixed_5c', 'Mixed_5d',
                 'Mixed_6a', 'Mixed_6b', 'Mixed_6c', 'Mixed_6d',
                 'Mixed_6e', 'Mixed_7a', 'Mixed_7b', 'Mixed_7c']

    for index, endpoint in enumerate(endpoints):
      with tf.Graph().as_default():
        inputs = tf.random_uniform((batch_size, height, width, 3))
        out_tensor, end_points = inception.inception_v3_base(
            inputs, final_endpoint=endpoint)
        self.assertTrue(out_tensor.op.name.startswith(
            'InceptionV3/' + endpoint))
        self.assertItemsEqual(endpoints[:index+1], end_points.keys())
Example #27
Source File: inception_v3_test.py    From ICPR_TextDection with GNU General Public License v3.0 6 votes vote down vote up 
def testBuildBaseNetwork(self):
    batch_size = 5
    height, width = 299, 299

    inputs = tf.random_uniform((batch_size, height, width, 3))
    final_endpoint, end_points = inception.inception_v3_base(inputs)
    self.assertTrue(final_endpoint.op.name.startswith(
        'InceptionV3/Mixed_7c'))
    self.assertListEqual(final_endpoint.get_shape().as_list(),
                         [batch_size, 8, 8, 2048])
    expected_endpoints = ['Conv2d_1a_3x3', 'Conv2d_2a_3x3', 'Conv2d_2b_3x3',
                          'MaxPool_3a_3x3', 'Conv2d_3b_1x1', 'Conv2d_4a_3x3',
                          'MaxPool_5a_3x3', 'Mixed_5b', 'Mixed_5c', 'Mixed_5d',
                          'Mixed_6a', 'Mixed_6b', 'Mixed_6c', 'Mixed_6d',
                          'Mixed_6e', 'Mixed_7a', 'Mixed_7b', 'Mixed_7c']
    self.assertItemsEqual(end_points.keys(), expected_endpoints)
Example #28
Source File: inception_v3_test.py    From ICPR_TextDection with GNU General Public License v3.0 6 votes vote down vote up 
def testBuildOnlyUptoFinalEndpoint(self):
    batch_size = 5
    height, width = 299, 299
    endpoints = ['Conv2d_1a_3x3', 'Conv2d_2a_3x3', 'Conv2d_2b_3x3',
                 'MaxPool_3a_3x3', 'Conv2d_3b_1x1', 'Conv2d_4a_3x3',
                 'MaxPool_5a_3x3', 'Mixed_5b', 'Mixed_5c', 'Mixed_5d',
                 'Mixed_6a', 'Mixed_6b', 'Mixed_6c', 'Mixed_6d',
                 'Mixed_6e', 'Mixed_7a', 'Mixed_7b', 'Mixed_7c']

    for index, endpoint in enumerate(endpoints):
      with tf.Graph().as_default():
        inputs = tf.random_uniform((batch_size, height, width, 3))
        out_tensor, end_points = inception.inception_v3_base(
            inputs, final_endpoint=endpoint)
        self.assertTrue(out_tensor.op.name.startswith(
            'InceptionV3/' + endpoint))
        self.assertItemsEqual(endpoints[:index+1], end_points.keys())
Example #29
Source File: inception_v3_test.py    From terngrad with Apache License 2.0 6 votes vote down vote up 
def testBuildBaseNetwork(self):
    batch_size = 5
    height, width = 299, 299

    inputs = tf.random_uniform((batch_size, height, width, 3))
    final_endpoint, end_points = inception.inception_v3_base(inputs)
    self.assertTrue(final_endpoint.op.name.startswith(
        'InceptionV3/Mixed_7c'))
    self.assertListEqual(final_endpoint.get_shape().as_list(),
                         [batch_size, 8, 8, 2048])
    expected_endpoints = ['Conv2d_1a_3x3', 'Conv2d_2a_3x3', 'Conv2d_2b_3x3',
                          'MaxPool_3a_3x3', 'Conv2d_3b_1x1', 'Conv2d_4a_3x3',
                          'MaxPool_5a_3x3', 'Mixed_5b', 'Mixed_5c', 'Mixed_5d',
                          'Mixed_6a', 'Mixed_6b', 'Mixed_6c', 'Mixed_6d',
                          'Mixed_6e', 'Mixed_7a', 'Mixed_7b', 'Mixed_7c']
    self.assertItemsEqual(end_points.keys(), expected_endpoints)
Example #30
Source File: inception_v3_test.py    From terngrad with Apache License 2.0 6 votes vote down vote up 
def testBuildOnlyUptoFinalEndpoint(self):
    batch_size = 5
    height, width = 299, 299
    endpoints = ['Conv2d_1a_3x3', 'Conv2d_2a_3x3', 'Conv2d_2b_3x3',
                 'MaxPool_3a_3x3', 'Conv2d_3b_1x1', 'Conv2d_4a_3x3',
                 'MaxPool_5a_3x3', 'Mixed_5b', 'Mixed_5c', 'Mixed_5d',
                 'Mixed_6a', 'Mixed_6b', 'Mixed_6c', 'Mixed_6d',
                 'Mixed_6e', 'Mixed_7a', 'Mixed_7b', 'Mixed_7c']

    for index, endpoint in enumerate(endpoints):
      with tf.Graph().as_default():
        inputs = tf.random_uniform((batch_size, height, width, 3))
        out_tensor, end_points = inception.inception_v3_base(
            inputs, final_endpoint=endpoint)
        self.assertTrue(out_tensor.op.name.startswith(
            'InceptionV3/' + endpoint))
        self.assertItemsEqual(endpoints[:index+1], end_points)