Python nets.mobilenet.mobilenet_v2.mobilenet_base() Examples

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Example #1
Source File: mobilenet_v2_test.py    From BMW-TensorFlow-Training-GUI with Apache License 2.0 5 votes vote down vote up
def testWithOutputStride16AndExplicitPadding(self):
    tf.reset_default_graph()
    out, _ = mobilenet.mobilenet_base(
        tf.placeholder(tf.float32, (10, 224, 224, 16)),
        conv_defs=mobilenet_v2.V2_DEF,
        output_stride=16,
        use_explicit_padding=True)
    self.assertEqual(out.get_shape().as_list()[1:3], [14, 14]) 
Example #2
Source File: mobilenet_v2_test.py    From g-tensorflow-models with Apache License 2.0 5 votes vote down vote up
def testWithOutputStride8AndExplicitPadding(self):
    tf.reset_default_graph()
    out, _ = mobilenet.mobilenet_base(
        tf.placeholder(tf.float32, (10, 224, 224, 16)),
        conv_defs=mobilenet_v2.V2_DEF,
        output_stride=8,
        use_explicit_padding=True,
        scope='MobilenetV2')
    self.assertEqual(out.get_shape().as_list()[1:3], [28, 28]) 
Example #3
Source File: mobilenet_v2_test.py    From MAX-Object-Detector with Apache License 2.0 5 votes vote down vote up
def testWithOutputStride16(self):
    tf.reset_default_graph()
    out, _ = mobilenet.mobilenet_base(
        tf.placeholder(tf.float32, (10, 224, 224, 16)),
        conv_defs=mobilenet_v2.V2_DEF,
        output_stride=16)
    self.assertEqual(out.get_shape().as_list()[1:3], [14, 14]) 
Example #4
Source File: feature_extractor.py    From g-tensorflow-models with Apache License 2.0 5 votes vote down vote up
def _mobilenet_v2(net,
                  depth_multiplier,
                  output_stride,
                  reuse=None,
                  scope=None,
                  final_endpoint=None):
  """Auxiliary function to add support for 'reuse' to mobilenet_v2.

  Args:
    net: Input tensor of shape [batch_size, height, width, channels].
    depth_multiplier: Float multiplier for the depth (number of channels)
      for all convolution ops. The value must be greater than zero. Typical
      usage will be to set this value in (0, 1) to reduce the number of
      parameters or computation cost of the model.
    output_stride: An integer that specifies the requested ratio of input to
      output spatial resolution. If not None, then we invoke atrous convolution
      if necessary to prevent the network from reducing the spatial resolution
      of the activation maps. Allowed values are 8 (accurate fully convolutional
      mode), 16 (fast fully convolutional mode), 32 (classification mode).
    reuse: Reuse model variables.
    scope: Optional variable scope.
    final_endpoint: The endpoint to construct the network up to.

  Returns:
    Features extracted by MobileNetv2.
  """
  with tf.variable_scope(
      scope, 'MobilenetV2', [net], reuse=reuse) as scope:
    return mobilenet_v2.mobilenet_base(
        net,
        conv_defs=mobilenet_v2.V2_DEF,
        depth_multiplier=depth_multiplier,
        min_depth=8 if depth_multiplier == 1.0 else 1,
        divisible_by=8 if depth_multiplier == 1.0 else 1,
        final_endpoint=final_endpoint or _MOBILENET_V2_FINAL_ENDPOINT,
        output_stride=output_stride,
        scope=scope)


# A map from network name to network function. 
Example #5
Source File: mobilenet_v2_test.py    From models with Apache License 2.0 5 votes vote down vote up
def testWithOutputStride8(self):
    out, _ = mobilenet.mobilenet_base(
        tf.placeholder(tf.float32, (10, 224, 224, 16)),
        conv_defs=mobilenet_v2.V2_DEF,
        output_stride=8,
        scope='MobilenetV2')
    self.assertEqual(out.get_shape().as_list()[1:3], [28, 28]) 
Example #6
Source File: mobilenet_v2_test.py    From g-tensorflow-models with Apache License 2.0 5 votes vote down vote up
def testWithOutputStride16AndExplicitPadding(self):
    tf.reset_default_graph()
    out, _ = mobilenet.mobilenet_base(
        tf.placeholder(tf.float32, (10, 224, 224, 16)),
        conv_defs=mobilenet_v2.V2_DEF,
        output_stride=16,
        use_explicit_padding=True)
    self.assertEqual(out.get_shape().as_list()[1:3], [14, 14]) 
Example #7
Source File: mobilenet_v2_test.py    From g-tensorflow-models with Apache License 2.0 5 votes vote down vote up
def testMobilenetBase(self):
    tf.reset_default_graph()
    # Verifies that mobilenet_base returns pre-pooling layer.
    with slim.arg_scope((mobilenet.depth_multiplier,), min_depth=32):
      net, _ = mobilenet_v2.mobilenet_base(
          tf.placeholder(tf.float32, (10, 224, 224, 16)),
          conv_defs=mobilenet_v2.V2_DEF, depth_multiplier=0.1)
      self.assertEqual(net.get_shape().as_list(), [10, 7, 7, 128]) 
Example #8
Source File: mobilenet_v2_test.py    From g-tensorflow-models with Apache License 2.0 5 votes vote down vote up
def testWithOutputStride8(self):
    out, _ = mobilenet.mobilenet_base(
        tf.placeholder(tf.float32, (10, 224, 224, 16)),
        conv_defs=mobilenet_v2.V2_DEF,
        output_stride=8,
        scope='MobilenetV2')
    self.assertEqual(out.get_shape().as_list()[1:3], [28, 28]) 
Example #9
Source File: mobilenet_v2_test.py    From MAX-Object-Detector with Apache License 2.0 5 votes vote down vote up
def testWithOutputStride16AndExplicitPadding(self):
    tf.reset_default_graph()
    out, _ = mobilenet.mobilenet_base(
        tf.placeholder(tf.float32, (10, 224, 224, 16)),
        conv_defs=mobilenet_v2.V2_DEF,
        output_stride=16,
        use_explicit_padding=True)
    self.assertEqual(out.get_shape().as_list()[1:3], [14, 14]) 
Example #10
Source File: mobilenet_v2_test.py    From MAX-Object-Detector with Apache License 2.0 5 votes vote down vote up
def testWithOutputStride8AndExplicitPadding(self):
    tf.reset_default_graph()
    out, _ = mobilenet.mobilenet_base(
        tf.placeholder(tf.float32, (10, 224, 224, 16)),
        conv_defs=mobilenet_v2.V2_DEF,
        output_stride=8,
        use_explicit_padding=True,
        scope='MobilenetV2')
    self.assertEqual(out.get_shape().as_list()[1:3], [28, 28]) 
Example #11
Source File: mobilenet_v2_test.py    From g-tensorflow-models with Apache License 2.0 5 votes vote down vote up
def testWithOutputStride16(self):
    tf.reset_default_graph()
    out, _ = mobilenet.mobilenet_base(
        tf.placeholder(tf.float32, (10, 224, 224, 16)),
        conv_defs=mobilenet_v2.V2_DEF,
        output_stride=16)
    self.assertEqual(out.get_shape().as_list()[1:3], [14, 14]) 
Example #12
Source File: mobilenet_v2_test.py    From MAX-Image-Segmenter with Apache License 2.0 5 votes vote down vote up
def testWithOutputStride8AndExplicitPadding(self):
    tf.reset_default_graph()
    out, _ = mobilenet.mobilenet_base(
        tf.placeholder(tf.float32, (10, 224, 224, 16)),
        conv_defs=mobilenet_v2.V2_DEF,
        output_stride=8,
        use_explicit_padding=True,
        scope='MobilenetV2')
    self.assertEqual(out.get_shape().as_list()[1:3], [28, 28]) 
Example #13
Source File: mobilenet_v2_test.py    From MAX-Image-Segmenter with Apache License 2.0 5 votes vote down vote up
def testWithOutputStride16(self):
    tf.reset_default_graph()
    out, _ = mobilenet.mobilenet_base(
        tf.placeholder(tf.float32, (10, 224, 224, 16)),
        conv_defs=mobilenet_v2.V2_DEF,
        output_stride=16)
    self.assertEqual(out.get_shape().as_list()[1:3], [14, 14]) 
Example #14
Source File: mobilenet_v2_test.py    From MAX-Image-Segmenter with Apache License 2.0 5 votes vote down vote up
def testMobilenetBase(self):
    tf.reset_default_graph()
    # Verifies that mobilenet_base returns pre-pooling layer.
    with slim.arg_scope((mobilenet.depth_multiplier,), min_depth=32):
      net, _ = mobilenet_v2.mobilenet_base(
          tf.placeholder(tf.float32, (10, 224, 224, 16)),
          conv_defs=mobilenet_v2.V2_DEF, depth_multiplier=0.1)
      self.assertEqual(net.get_shape().as_list(), [10, 7, 7, 128]) 
Example #15
Source File: mobilenet_v2_test.py    From MAX-Image-Segmenter with Apache License 2.0 5 votes vote down vote up
def testWithOutputStride8(self):
    out, _ = mobilenet.mobilenet_base(
        tf.placeholder(tf.float32, (10, 224, 224, 16)),
        conv_defs=mobilenet_v2.V2_DEF,
        output_stride=8,
        scope='MobilenetV2')
    self.assertEqual(out.get_shape().as_list()[1:3], [28, 28]) 
Example #16
Source File: mobilenet_v2_test.py    From MAX-Image-Segmenter with Apache License 2.0 5 votes vote down vote up
def testWithOutputStride16AndExplicitPadding(self):
    tf.reset_default_graph()
    out, _ = mobilenet.mobilenet_base(
        tf.placeholder(tf.float32, (10, 224, 224, 16)),
        conv_defs=mobilenet_v2.V2_DEF,
        output_stride=16,
        use_explicit_padding=True)
    self.assertEqual(out.get_shape().as_list()[1:3], [14, 14]) 
Example #17
Source File: mobilenet_v2_test.py    From BMW-TensorFlow-Training-GUI with Apache License 2.0 5 votes vote down vote up
def testWithOutputStride8AndExplicitPadding(self):
    tf.reset_default_graph()
    out, _ = mobilenet.mobilenet_base(
        tf.placeholder(tf.float32, (10, 224, 224, 16)),
        conv_defs=mobilenet_v2.V2_DEF,
        output_stride=8,
        use_explicit_padding=True,
        scope='MobilenetV2')
    self.assertEqual(out.get_shape().as_list()[1:3], [28, 28]) 
Example #18
Source File: mobilenet_v2_test.py    From BMW-TensorFlow-Training-GUI with Apache License 2.0 5 votes vote down vote up
def testWithOutputStride16(self):
    tf.reset_default_graph()
    out, _ = mobilenet.mobilenet_base(
        tf.placeholder(tf.float32, (10, 224, 224, 16)),
        conv_defs=mobilenet_v2.V2_DEF,
        output_stride=16)
    self.assertEqual(out.get_shape().as_list()[1:3], [14, 14]) 
Example #19
Source File: mobilenet_v2_test.py    From BMW-TensorFlow-Training-GUI with Apache License 2.0 5 votes vote down vote up
def testMobilenetBase(self):
    tf.reset_default_graph()
    # Verifies that mobilenet_base returns pre-pooling layer.
    with slim.arg_scope((mobilenet.depth_multiplier,), min_depth=32):
      net, _ = mobilenet_v2.mobilenet_base(
          tf.placeholder(tf.float32, (10, 224, 224, 16)),
          conv_defs=mobilenet_v2.V2_DEF, depth_multiplier=0.1)
      self.assertEqual(net.get_shape().as_list(), [10, 7, 7, 128]) 
Example #20
Source File: mobilenet_v2_test.py    From BMW-TensorFlow-Training-GUI with Apache License 2.0 5 votes vote down vote up
def testWithOutputStride8(self):
    out, _ = mobilenet.mobilenet_base(
        tf.placeholder(tf.float32, (10, 224, 224, 16)),
        conv_defs=mobilenet_v2.V2_DEF,
        output_stride=8,
        scope='MobilenetV2')
    self.assertEqual(out.get_shape().as_list()[1:3], [28, 28]) 
Example #21
Source File: mobilenet_v2_test.py    From Gun-Detector with Apache License 2.0 5 votes vote down vote up
def testWithOutputStride16AndExplicitPadding(self):
    tf.reset_default_graph()
    out, _ = mobilenet.mobilenet_base(
        tf.placeholder(tf.float32, (10, 224, 224, 16)),
        conv_defs=mobilenet_v2.V2_DEF,
        output_stride=16,
        use_explicit_padding=True)
    self.assertEqual(out.get_shape().as_list()[1:3], [14, 14]) 
Example #22
Source File: mobilenet_v2_test.py    From Gun-Detector with Apache License 2.0 5 votes vote down vote up
def testWithOutputStride8AndExplicitPadding(self):
    tf.reset_default_graph()
    out, _ = mobilenet.mobilenet_base(
        tf.placeholder(tf.float32, (10, 224, 224, 16)),
        conv_defs=mobilenet_v2.V2_DEF,
        output_stride=8,
        use_explicit_padding=True,
        scope='MobilenetV2')
    self.assertEqual(out.get_shape().as_list()[1:3], [28, 28]) 
Example #23
Source File: mobilenet_v2_test.py    From Gun-Detector with Apache License 2.0 5 votes vote down vote up
def testWithOutputStride16(self):
    tf.reset_default_graph()
    out, _ = mobilenet.mobilenet_base(
        tf.placeholder(tf.float32, (10, 224, 224, 16)),
        conv_defs=mobilenet_v2.V2_DEF,
        output_stride=16)
    self.assertEqual(out.get_shape().as_list()[1:3], [14, 14]) 
Example #24
Source File: mobilenet_v2_test.py    From Gun-Detector with Apache License 2.0 5 votes vote down vote up
def testMobilenetBase(self):
    tf.reset_default_graph()
    # Verifies that mobilenet_base returns pre-pooling layer.
    with slim.arg_scope((mobilenet.depth_multiplier,), min_depth=32):
      net, _ = mobilenet_v2.mobilenet_base(
          tf.placeholder(tf.float32, (10, 224, 224, 16)),
          conv_defs=mobilenet_v2.V2_DEF, depth_multiplier=0.1)
      self.assertEqual(net.get_shape().as_list(), [10, 7, 7, 128]) 
Example #25
Source File: mobilenet_v2_test.py    From Gun-Detector with Apache License 2.0 5 votes vote down vote up
def testWithOutputStride8(self):
    out, _ = mobilenet.mobilenet_base(
        tf.placeholder(tf.float32, (10, 224, 224, 16)),
        conv_defs=mobilenet_v2.V2_DEF,
        output_stride=8,
        scope='MobilenetV2')
    self.assertEqual(out.get_shape().as_list()[1:3], [28, 28]) 
Example #26
Source File: mobilenet_v2_test.py    From CBAM-tensorflow-slim with MIT License 5 votes vote down vote up
def testWithOutputStride16AndExplicitPadding(self):
    tf.reset_default_graph()
    out, _ = mobilenet.mobilenet_base(
        tf.placeholder(tf.float32, (10, 224, 224, 16)),
        conv_defs=mobilenet_v2.V2_DEF,
        output_stride=16,
        use_explicit_padding=True)
    self.assertEqual(out.get_shape().as_list()[1:3], [14, 14]) 
Example #27
Source File: mobilenet_v2_test.py    From CBAM-tensorflow-slim with MIT License 5 votes vote down vote up
def testWithOutputStride8AndExplicitPadding(self):
    tf.reset_default_graph()
    out, _ = mobilenet.mobilenet_base(
        tf.placeholder(tf.float32, (10, 224, 224, 16)),
        conv_defs=mobilenet_v2.V2_DEF,
        output_stride=8,
        use_explicit_padding=True,
        scope='MobilenetV2')
    self.assertEqual(out.get_shape().as_list()[1:3], [28, 28]) 
Example #28
Source File: mobilenet_v2_test.py    From CBAM-tensorflow-slim with MIT License 5 votes vote down vote up
def testWithOutputStride16(self):
    tf.reset_default_graph()
    out, _ = mobilenet.mobilenet_base(
        tf.placeholder(tf.float32, (10, 224, 224, 16)),
        conv_defs=mobilenet_v2.V2_DEF,
        output_stride=16)
    self.assertEqual(out.get_shape().as_list()[1:3], [14, 14]) 
Example #29
Source File: mobilenet_v2_test.py    From CBAM-tensorflow-slim with MIT License 5 votes vote down vote up
def testMobilenetBase(self):
    tf.reset_default_graph()
    # Verifies that mobilenet_base returns pre-pooling layer.
    with slim.arg_scope((mobilenet.depth_multiplier,), min_depth=32):
      net, _ = mobilenet_v2.mobilenet_base(
          tf.placeholder(tf.float32, (10, 224, 224, 16)),
          conv_defs=mobilenet_v2.V2_DEF, depth_multiplier=0.1)
      self.assertEqual(net.get_shape().as_list(), [10, 7, 7, 128]) 
Example #30
Source File: mobilenet_v2_test.py    From DeepLab_v3 with MIT License 5 votes vote down vote up
def testWithOutputStride8(self):
    out, _ = mobilenet.mobilenet_base(
        tf.placeholder(tf.float32, (10, 224, 224, 16)),
        conv_defs=mobilenet_v2.V2_DEF,
        output_stride=8,
        scope='MobilenetV2')
    self.assertEqual(out.get_shape().as_list()[1:3], [28, 28])