Python object_detection.utils.static_shape.get_depth() Examples

The following are 30 code examples of object_detection.utils.static_shape.get_depth(). 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 object_detection.utils.static_shape , or try the search function .
Example #1
Source File: static_shape_test.py    From Elphas with Apache License 2.0 5 votes vote down vote up 
def test_die_on_tensor_shape_with_rank_three(self):
    tensor_shape = tf.TensorShape(dims=[32, 299, 384])
    with self.assertRaises(ValueError):
      static_shape.get_batch_size(tensor_shape)
      static_shape.get_height(tensor_shape)
      static_shape.get_width(tensor_shape)
      static_shape.get_depth(tensor_shape)
Example #2
Source File: static_shape_test.py    From AniSeg with Apache License 2.0 5 votes vote down vote up 
def test_return_correct_depth(self):
    tensor_shape = tf.TensorShape(dims=[32, 299, 384, 3])
    self.assertEqual(3, static_shape.get_depth(tensor_shape))
Example #3
Source File: static_shape_test.py    From monopsr with MIT License 5 votes vote down vote up 
def test_die_on_tensor_shape_with_rank_three(self):
        tensor_shape = tf.TensorShape(dims=[32, 299, 384])
        with self.assertRaises(ValueError):
            static_shape.get_batch_size(tensor_shape)
            static_shape.get_height(tensor_shape)
            static_shape.get_width(tensor_shape)
            static_shape.get_depth(tensor_shape)
Example #4
Source File: static_shape_test.py    From monopsr with MIT License 5 votes vote down vote up 
def test_return_correct_depth(self):
        tensor_shape = tf.TensorShape(dims=[32, 299, 384, 3])
        self.assertEqual(3, static_shape.get_depth(tensor_shape))
Example #5
Source File: static_shape_test.py    From open-solution-googleai-object-detection with MIT License 5 votes vote down vote up 
def test_return_correct_depth(self):
    tensor_shape = tf.TensorShape(dims=[32, 299, 384, 3])
    self.assertEqual(3, static_shape.get_depth(tensor_shape))
Example #6
Source File: static_shape_test.py    From open-solution-googleai-object-detection with MIT License 5 votes vote down vote up 
def test_die_on_tensor_shape_with_rank_three(self):
    tensor_shape = tf.TensorShape(dims=[32, 299, 384])
    with self.assertRaises(ValueError):
      static_shape.get_batch_size(tensor_shape)
      static_shape.get_height(tensor_shape)
      static_shape.get_width(tensor_shape)
      static_shape.get_depth(tensor_shape)
Example #7
Source File: static_shape_test.py    From g-tensorflow-models with Apache License 2.0 5 votes vote down vote up 
def test_return_correct_depth(self):
    tensor_shape = tf.TensorShape(dims=[32, 299, 384, 3])
    self.assertEqual(3, static_shape.get_depth(tensor_shape))
Example #8
Source File: static_shape_test.py    From g-tensorflow-models with Apache License 2.0 5 votes vote down vote up 
def test_die_on_tensor_shape_with_rank_three(self):
    tensor_shape = tf.TensorShape(dims=[32, 299, 384])
    with self.assertRaises(ValueError):
      static_shape.get_batch_size(tensor_shape)
      static_shape.get_height(tensor_shape)
      static_shape.get_width(tensor_shape)
      static_shape.get_depth(tensor_shape)
Example #9
Source File: convolutional_keras_box_predictor.py    From g-tensorflow-models with Apache License 2.0 5 votes vote down vote up 
def build(self, input_shapes):
    """Creates the variables of the layer."""
    if len(input_shapes) != len(self._prediction_heads[BOX_ENCODINGS]):
      raise ValueError('This box predictor was constructed with %d heads,'
                       'but there are %d inputs.' %
                       (len(self._prediction_heads[BOX_ENCODINGS]),
                        len(input_shapes)))
    for stack_index, input_shape in enumerate(input_shapes):
      net = []

      # Add additional conv layers before the class predictor.
      features_depth = static_shape.get_depth(input_shape)
      depth = max(min(features_depth, self._max_depth), self._min_depth)
      tf.logging.info(
          'depth of additional conv before box predictor: {}'.format(depth))

      if depth > 0 and self._num_layers_before_predictor > 0:
        for i in range(self._num_layers_before_predictor):
          net.append(keras.Conv2D(depth, [1, 1],
                                  name='SharedConvolutions_%d/Conv2d_%d_1x1_%d'
                                  % (stack_index, i, depth),
                                  padding='SAME',
                                  **self._conv_hyperparams.params()))
          net.append(self._conv_hyperparams.build_batch_norm(
              training=(self._is_training and not self._freeze_batchnorm),
              name='SharedConvolutions_%d/Conv2d_%d_1x1_%d_norm'
              % (stack_index, i, depth)))
          net.append(self._conv_hyperparams.build_activation_layer(
              name='SharedConvolutions_%d/Conv2d_%d_1x1_%d_activation'
              % (stack_index, i, depth),
          ))
      # Until certain bugs are fixed in checkpointable lists,
      # this net must be appended only once it's been filled with layers
      self._shared_nets.append(net)
    self.built = True
Example #10
Source File: static_shape_test.py    From models with Apache License 2.0 5 votes vote down vote up 
def test_return_correct_depth(self):
    tensor_shape = tf.TensorShape(dims=[32, 299, 384, 3])
    self.assertEqual(3, static_shape.get_depth(tensor_shape))
Example #11
Source File: static_shape_test.py    From models with Apache License 2.0 5 votes vote down vote up 
def test_die_on_tensor_shape_with_rank_three(self):
    tensor_shape = tf.TensorShape(dims=[32, 299, 384])
    with self.assertRaises(ValueError):
      static_shape.get_batch_size(tensor_shape)
      static_shape.get_height(tensor_shape)
      static_shape.get_width(tensor_shape)
      static_shape.get_depth(tensor_shape)
Example #12
Source File: convolutional_keras_box_predictor.py    From models with Apache License 2.0 5 votes vote down vote up 
def build(self, input_shapes):
    """Creates the variables of the layer."""
    if len(input_shapes) != len(self._prediction_heads[BOX_ENCODINGS]):
      raise ValueError('This box predictor was constructed with %d heads,'
                       'but there are %d inputs.' %
                       (len(self._prediction_heads[BOX_ENCODINGS]),
                        len(input_shapes)))
    for stack_index, input_shape in enumerate(input_shapes):
      net = []

      # Add additional conv layers before the class predictor.
      features_depth = static_shape.get_depth(input_shape)
      depth = max(min(features_depth, self._max_depth), self._min_depth)
      tf.logging.info(
          'depth of additional conv before box predictor: {}'.format(depth))

      if depth > 0 and self._num_layers_before_predictor > 0:
        for i in range(self._num_layers_before_predictor):
          net.append(keras.Conv2D(depth, [1, 1],
                                  name='SharedConvolutions_%d/Conv2d_%d_1x1_%d'
                                  % (stack_index, i, depth),
                                  padding='SAME',
                                  **self._conv_hyperparams.params()))
          net.append(self._conv_hyperparams.build_batch_norm(
              training=(self._is_training and not self._freeze_batchnorm),
              name='SharedConvolutions_%d/Conv2d_%d_1x1_%d_norm'
              % (stack_index, i, depth)))
          net.append(self._conv_hyperparams.build_activation_layer(
              name='SharedConvolutions_%d/Conv2d_%d_1x1_%d_activation'
              % (stack_index, i, depth),
          ))
      # Until certain bugs are fixed in checkpointable lists,
      # this net must be appended only once it's been filled with layers
      self._shared_nets.append(net)
    self.built = True
Example #13
Source File: convolutional_keras_box_predictor.py    From MAX-Object-Detector with Apache License 2.0 5 votes vote down vote up 
def build(self, input_shapes):
    """Creates the variables of the layer."""
    if len(input_shapes) != len(self._prediction_heads[BOX_ENCODINGS]):
      raise ValueError('This box predictor was constructed with %d heads,'
                       'but there are %d inputs.' %
                       (len(self._prediction_heads[BOX_ENCODINGS]),
                        len(input_shapes)))
    for stack_index, input_shape in enumerate(input_shapes):
      net = []

      # Add additional conv layers before the class predictor.
      features_depth = static_shape.get_depth(input_shape)
      depth = max(min(features_depth, self._max_depth), self._min_depth)
      tf.logging.info(
          'depth of additional conv before box predictor: {}'.format(depth))

      if depth > 0 and self._num_layers_before_predictor > 0:
        for i in range(self._num_layers_before_predictor):
          net.append(keras.Conv2D(depth, [1, 1],
                                  name='SharedConvolutions_%d/Conv2d_%d_1x1_%d'
                                  % (stack_index, i, depth),
                                  padding='SAME',
                                  **self._conv_hyperparams.params()))
          net.append(self._conv_hyperparams.build_batch_norm(
              training=(self._is_training and not self._freeze_batchnorm),
              name='SharedConvolutions_%d/Conv2d_%d_1x1_%d_norm'
              % (stack_index, i, depth)))
          net.append(self._conv_hyperparams.build_activation_layer(
              name='SharedConvolutions_%d/Conv2d_%d_1x1_%d_activation'
              % (stack_index, i, depth),
          ))
      # Until certain bugs are fixed in checkpointable lists,
      # this net must be appended only once it's been filled with layers
      self._shared_nets.append(net)
    self.built = True
Example #14
Source File: static_shape_test.py    From object_detection_with_tensorflow with MIT License 5 votes vote down vote up 
def test_die_on_tensor_shape_with_rank_three(self):
    tensor_shape = tf.TensorShape(dims=[32, 299, 384])
    with self.assertRaises(ValueError):
      static_shape.get_batch_size(tensor_shape)
      static_shape.get_height(tensor_shape)
      static_shape.get_width(tensor_shape)
      static_shape.get_depth(tensor_shape)
Example #15
Source File: static_shape_test.py    From object_detection_with_tensorflow with MIT License 5 votes vote down vote up 
def test_return_correct_depth(self):
    tensor_shape = tf.TensorShape(dims=[32, 299, 384, 3])
    self.assertEqual(3, static_shape.get_depth(tensor_shape))
Example #16
Source File: static_shape_test.py    From object_detection_with_tensorflow with MIT License 5 votes vote down vote up 
def test_return_correct_depth(self):
    tensor_shape = tf.TensorShape(dims=[32, 299, 384, 3])
    self.assertEqual(3, static_shape.get_depth(tensor_shape))
Example #17
Source File: static_shape_test.py    From Elphas with Apache License 2.0 5 votes vote down vote up 
def test_return_correct_depth(self):
    tensor_shape = tf.TensorShape(dims=[32, 299, 384, 3])
    self.assertEqual(3, static_shape.get_depth(tensor_shape))
Example #18
Source File: static_shape_test.py    From MBMD with MIT License 5 votes vote down vote up 
def test_die_on_tensor_shape_with_rank_three(self):
    tensor_shape = tf.TensorShape(dims=[32, 299, 384])
    with self.assertRaises(ValueError):
      static_shape.get_batch_size(tensor_shape)
      static_shape.get_height(tensor_shape)
      static_shape.get_width(tensor_shape)
      static_shape.get_depth(tensor_shape)
Example #19
Source File: static_shape_test.py    From MBMD with MIT License 5 votes vote down vote up 
def test_return_correct_depth(self):
    tensor_shape = tf.TensorShape(dims=[32, 299, 384, 3])
    self.assertEqual(3, static_shape.get_depth(tensor_shape))
Example #20
Source File: static_shape_test.py    From object_detection_kitti with Apache License 2.0 5 votes vote down vote up 
def test_die_on_tensor_shape_with_rank_three(self):
    tensor_shape = tf.TensorShape(dims=[32, 299, 384])
    with self.assertRaises(ValueError):
      static_shape.get_batch_size(tensor_shape)
      static_shape.get_height(tensor_shape)
      static_shape.get_width(tensor_shape)
      static_shape.get_depth(tensor_shape)
Example #21
Source File: static_shape_test.py    From object_detection_kitti with Apache License 2.0 5 votes vote down vote up 
def test_return_correct_depth(self):
    tensor_shape = tf.TensorShape(dims=[32, 299, 384, 3])
    self.assertEqual(3, static_shape.get_depth(tensor_shape))
Example #22
Source File: static_shape_test.py    From Live-feed-object-device-identification-using-Tensorflow-and-OpenCV with Apache License 2.0 5 votes vote down vote up 
def test_die_on_tensor_shape_with_rank_three(self):
    tensor_shape = tf.TensorShape(dims=[32, 299, 384])
    with self.assertRaises(ValueError):
      static_shape.get_batch_size(tensor_shape)
      static_shape.get_height(tensor_shape)
      static_shape.get_width(tensor_shape)
      static_shape.get_depth(tensor_shape)
Example #23
Source File: static_shape_test.py    From Live-feed-object-device-identification-using-Tensorflow-and-OpenCV with Apache License 2.0 5 votes vote down vote up 
def test_return_correct_depth(self):
    tensor_shape = tf.TensorShape(dims=[32, 299, 384, 3])
    self.assertEqual(3, static_shape.get_depth(tensor_shape))
Example #24
Source File: static_shape_test.py    From hands-detection with MIT License 5 votes vote down vote up 
def test_die_on_tensor_shape_with_rank_three(self):
    tensor_shape = tf.TensorShape(dims=[32, 299, 384])
    with self.assertRaises(ValueError):
      static_shape.get_batch_size(tensor_shape)
      static_shape.get_height(tensor_shape)
      static_shape.get_width(tensor_shape)
      static_shape.get_depth(tensor_shape)
Example #25
Source File: static_shape_test.py    From hands-detection with MIT License 5 votes vote down vote up 
def test_return_correct_depth(self):
    tensor_shape = tf.TensorShape(dims=[32, 299, 384, 3])
    self.assertEqual(3, static_shape.get_depth(tensor_shape))
Example #26
Source File: static_shape_test.py    From moveo_ros with MIT License 5 votes vote down vote up 
def test_die_on_tensor_shape_with_rank_three(self):
    tensor_shape = tf.TensorShape(dims=[32, 299, 384])
    with self.assertRaises(ValueError):
      static_shape.get_batch_size(tensor_shape)
      static_shape.get_height(tensor_shape)
      static_shape.get_width(tensor_shape)
      static_shape.get_depth(tensor_shape)
Example #27
Source File: static_shape_test.py    From moveo_ros with MIT License 5 votes vote down vote up 
def test_return_correct_depth(self):
    tensor_shape = tf.TensorShape(dims=[32, 299, 384, 3])
    self.assertEqual(3, static_shape.get_depth(tensor_shape))
Example #28
Source File: static_shape_test.py    From BMW-TensorFlow-Training-GUI with Apache License 2.0 5 votes vote down vote up 
def test_die_on_tensor_shape_with_rank_three(self):
    tensor_shape = tf.TensorShape(dims=[32, 299, 384])
    with self.assertRaises(ValueError):
      static_shape.get_batch_size(tensor_shape)
      static_shape.get_height(tensor_shape)
      static_shape.get_width(tensor_shape)
      static_shape.get_depth(tensor_shape)
Example #29
Source File: static_shape_test.py    From BMW-TensorFlow-Training-GUI with Apache License 2.0 5 votes vote down vote up 
def test_return_correct_depth(self):
    tensor_shape = tf.TensorShape(dims=[32, 299, 384, 3])
    self.assertEqual(3, static_shape.get_depth(tensor_shape))
Example #30
Source File: static_shape_test.py    From ros_tensorflow with Apache License 2.0 5 votes vote down vote up 
def test_die_on_tensor_shape_with_rank_three(self):
    tensor_shape = tf.TensorShape(dims=[32, 299, 384])
    with self.assertRaises(ValueError):
      static_shape.get_batch_size(tensor_shape)
      static_shape.get_height(tensor_shape)
      static_shape.get_width(tensor_shape)
      static_shape.get_depth(tensor_shape)