Python boolean_mask Examples

Example #1

 def graph_fn():
   corners = tf.constant(
       [4 * [0.0], 4 * [1.0], 4 * [2.0], 4 * [3.0], 4 * [4.0]])
   indicator = tf.constant([True, False, True, False, True], tf.bool)
   boxes = box_list.BoxList(corners)
   subset = box_list_ops.boolean_mask(boxes, indicator)
   return subset.get()

Example #2

 def graph_fn(corners, weights, indicator):
   boxes = box_list.BoxList(corners)
   boxes.add_field('weights', weights)
   subset = box_list_ops.boolean_mask(
       boxes,
       indicator, ['weights'],
       use_static_shapes=True,
       indicator_sum=3)
   return (subset.get_field('boxes'), subset.get_field('weights'))

Example #3

File: box_list_ops_test.py Project: Exscotticus/models

 def graph_fn(corners, weights, indicator):
   boxes = box_list.BoxList(corners)
   boxes.add_field('weights', weights)
   subset = box_list_ops.boolean_mask(
       boxes,
       indicator, ['weights'],
       use_static_shapes=True,
       indicator_sum=3)
   return (subset.get_field('boxes'), subset.get_field('weights'))

Example #4

File: box_list_ops_test.py Project: jonathangenty0801/Object-detection

 def test_boolean_mask(self):
     corners = tf.constant(
         [4 * [0.0], 4 * [1.0], 4 * [2.0], 4 * [3.0], 4 * [4.0]])
     indicator = tf.constant([True, False, True, False, True], tf.bool)
     expected_subset = [4 * [0.0], 4 * [2.0], 4 * [4.0]]
     boxes = box_list.BoxList(corners)
     subset = box_list_ops.boolean_mask(boxes, indicator)
     with self.test_session() as sess:
         subset_output = sess.run(subset.get())
         self.assertAllClose(subset_output, expected_subset)

Example #5

File: box_list_ops_test.py Project: Exscotticus/models

 def test_boolean_mask(self):
   corners = tf.constant(
       [4 * [0.0], 4 * [1.0], 4 * [2.0], 4 * [3.0], 4 * [4.0]])
   indicator = tf.constant([True, False, True, False, True], tf.bool)
   expected_subset = [4 * [0.0], 4 * [2.0], 4 * [4.0]]
   boxes = box_list.BoxList(corners)
   subset = box_list_ops.boolean_mask(boxes, indicator)
   with self.test_session() as sess:
     subset_output = sess.run(subset.get())
     self.assertAllClose(subset_output, expected_subset)

Example #6

File: box_list_ops_test.py Project: jonathangenty0801/Object-detection

    def test_boolean_mask_with_field(self):
        corners = tf.constant(
            [4 * [0.0], 4 * [1.0], 4 * [2.0], 4 * [3.0], 4 * [4.0]])
        indicator = tf.constant([True, False, True, False, True], tf.bool)
        weights = tf.constant([[.1], [.3], [.5], [.7], [.9]], tf.float32)
        expected_subset = [4 * [0.0], 4 * [2.0], 4 * [4.0]]
        expected_weights = [[.1], [.5], [.9]]

        boxes = box_list.BoxList(corners)
        boxes.add_field('weights', weights)
        subset = box_list_ops.boolean_mask(boxes, indicator, ['weights'])
        with self.test_session() as sess:
            subset_output, weights_output = sess.run(
                [subset.get(), subset.get_field('weights')])
            self.assertAllClose(subset_output, expected_subset)
            self.assertAllClose(weights_output, expected_weights)

Example #7

File: box_list_ops_test.py Project: forging2012/models

  def test_boolean_mask_with_field(self):
    corners = tf.constant(
        [4 * [0.0], 4 * [1.0], 4 * [2.0], 4 * [3.0], 4 * [4.0]])
    indicator = tf.constant([True, False, True, False, True], tf.bool)
    weights = tf.constant([[.1], [.3], [.5], [.7], [.9]], tf.float32)
    expected_subset = [4 * [0.0], 4 * [2.0], 4 * [4.0]]
    expected_weights = [[.1], [.5], [.9]]

    boxes = box_list.BoxList(corners)
    boxes.add_field('weights', weights)
    subset = box_list_ops.boolean_mask(boxes, indicator, ['weights'])
    with self.test_session() as sess:
      subset_output, weights_output = sess.run(
          [subset.get(), subset.get_field('weights')])
      self.assertAllClose(subset_output, expected_subset)
      self.assertAllClose(weights_output, expected_weights)

Example #8

File: box_list_ops_test.py Project: Exscotticus/models

  def test_dynamic_boolean_mask_with_field(self):
    corners = tf.placeholder(tf.float32, [None, 4])
    indicator = tf.placeholder(tf.bool, [None])
    weights = tf.placeholder(tf.float32, [None, 1])
    expected_subset = [4 * [0.0], 4 * [2.0], 4 * [4.0]]
    expected_weights = [[.1], [.5], [.9]]

    boxes = box_list.BoxList(corners)
    boxes.add_field('weights', weights)
    subset = box_list_ops.boolean_mask(boxes, indicator, ['weights'])
    with self.test_session() as sess:
      subset_output, weights_output = sess.run(
          [subset.get(), subset.get_field('weights')],
          feed_dict={
              corners:
                  np.array(
                      [4 * [0.0], 4 * [1.0], 4 * [2.0], 4 * [3.0], 4 * [4.0]]),
              indicator:
                  np.array([True, False, True, False, True]).astype(np.bool),
              weights:
                  np.array([[.1], [.3], [.5], [.7], [.9]])
          })
      self.assertAllClose(subset_output, expected_subset)
      self.assertAllClose(weights_output, expected_weights)

Example #9

File: box_list_ops_test.py Project: connorlee77/tf-object-detection

  def test_dynamic_boolean_mask_with_field(self):
    corners = tf.placeholder(tf.float32, [None, 4])
    indicator = tf.placeholder(tf.bool, [None])
    weights = tf.placeholder(tf.float32, [None, 1])
    expected_subset = [4 * [0.0], 4 * [2.0], 4 * [4.0]]
    expected_weights = [[.1], [.5], [.9]]

    boxes = box_list.BoxList(corners)
    boxes.add_field('weights', weights)
    subset = box_list_ops.boolean_mask(boxes, indicator, ['weights'])
    with self.test_session() as sess:
      subset_output, weights_output = sess.run(
          [subset.get(), subset.get_field('weights')],
          feed_dict={
              corners:
                  np.array(
                      [4 * [0.0], 4 * [1.0], 4 * [2.0], 4 * [3.0], 4 * [4.0]]),
              indicator:
                  np.array([True, False, True, False, True]).astype(np.bool),
              weights:
                  np.array([[.1], [.3], [.5], [.7], [.9]])
          })
      self.assertAllClose(subset_output, expected_subset)
      self.assertAllClose(weights_output, expected_weights)