Python object_detection.core.box_list_ops.boolean_mask() Examples

The following are 30 code examples of object_detection.core.box_list_ops.boolean_mask(). 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.core.box_list_ops , or try the search function .
Example #1
Source File: box_list_ops_test.py    From moveo_ros with MIT License 6 votes vote down vote up 
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 #2
Source File: box_list_ops_test.py    From HereIsWally with MIT License 6 votes vote down vote up 
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 #3
Source File: box_list_ops_test.py    From ros_people_object_detection_tensorflow with Apache License 2.0 6 votes vote down vote up 
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 #4
Source File: box_list_ops_test.py    From object_detector_app with MIT License 6 votes vote down vote up 
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 #5
Source File: faster_rcnn_meta_arch.py    From vehicle_counting_tensorflow with MIT License 6 votes vote down vote up 
def _get_refined_encodings_for_postitive_class(
      self, refined_box_encodings, flat_cls_targets_with_background,
      batch_size):
    # We only predict refined location encodings for the non background
    # classes, but we now pad it to make it compatible with the class
    # predictions
    refined_box_encodings_with_background = tf.pad(refined_box_encodings,
                                                   [[0, 0], [1, 0], [0, 0]])
    refined_box_encodings_masked_by_class_targets = (
        box_list_ops.boolean_mask(
            box_list.BoxList(
                tf.reshape(refined_box_encodings_with_background,
                           [-1, self._box_coder.code_size])),
            tf.reshape(tf.greater(flat_cls_targets_with_background, 0), [-1]),
            use_static_shapes=self._use_static_shapes,
            indicator_sum=batch_size * self.max_num_proposals
            if self._use_static_shapes else None).get())
    return tf.reshape(
        refined_box_encodings_masked_by_class_targets, [
            batch_size, self.max_num_proposals,
            self._box_coder.code_size
        ])
Example #6
Source File: box_list_ops_test.py    From Person-Detection-and-Tracking with MIT License 6 votes vote down vote up 
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
Source File: box_list_ops_test.py    From vehicle_counting_tensorflow with MIT License 6 votes vote down vote up 
def test_static_boolean_mask_with_field(self):

    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'))

    corners = np.array(
        [4 * [0.0], 4 * [1.0], 4 * [2.0], 4 * [3.0], 4 * [4.0]],
        dtype=np.float32)
    indicator = np.array([True, False, True, False, True], dtype=np.bool)
    weights = np.array([[.1], [.3], [.5], [.7], [.9]], dtype=np.float32)
    result_boxes, result_weights = self.execute(graph_fn,
                                                [corners, weights, indicator])
    expected_boxes = [4 * [0.0], 4 * [2.0], 4 * [4.0]]
    expected_weights = [[.1], [.5], [.9]]

    self.assertAllClose(result_boxes, expected_boxes)
    self.assertAllClose(result_weights, expected_weights)
Example #8
Source File: box_list_ops_test.py    From vehicle_counting_tensorflow with MIT License 6 votes vote down vote up 
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
Source File: box_list_ops_test.py    From garbage-object-detection-tensorflow with MIT License 6 votes vote down vote up 
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 #10
Source File: box_list_ops_test.py    From yolo_v2 with Apache License 2.0 6 votes vote down vote up 
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 #11
Source File: box_list_ops_test.py    From Traffic-Rule-Violation-Detection-System with MIT License 6 votes vote down vote up 
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 #12
Source File: box_list_ops_test.py    From Hands-On-Machine-Learning-with-OpenCV-4 with MIT License 6 votes vote down vote up 
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 #13
Source File: box_list_ops_test.py    From tensorflow with BSD 2-Clause "Simplified" License 6 votes vote down vote up 
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 #14
Source File: box_list_ops_test.py    From Gun-Detector with Apache License 2.0 6 votes vote down vote up 
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 #15
Source File: box_list_ops_test.py    From BMW-TensorFlow-Training-GUI with Apache License 2.0 6 votes vote down vote up 
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 #16
Source File: box_list_ops_test.py    From ros_tensorflow with Apache License 2.0 6 votes vote down vote up 
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 #17
Source File: box_list_ops_test.py    From hands-detection with MIT License 6 votes vote down vote up 
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 #18
Source File: box_list_ops_test.py    From object_detection_kitti with Apache License 2.0 6 votes vote down vote up 
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 #19
Source File: box_list_ops_test.py    From MBMD with MIT License 6 votes vote down vote up 
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 #20
Source File: box_list_ops_test.py    From Elphas with Apache License 2.0 6 votes vote down vote up 
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 #21
Source File: box_list_ops_test.py    From object_detection_with_tensorflow with MIT License 6 votes vote down vote up 
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 #22
Source File: box_list_ops_test.py    From monopsr with MIT License 6 votes vote down vote up 
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 #23
Source File: box_list_ops_test.py    From AniSeg with Apache License 2.0 6 votes vote down vote up 
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 #24
Source File: faster_rcnn_meta_arch.py    From MAX-Object-Detector with Apache License 2.0 6 votes vote down vote up 
def _get_refined_encodings_for_postitive_class(
      self, refined_box_encodings, flat_cls_targets_with_background,
      batch_size):
    # We only predict refined location encodings for the non background
    # classes, but we now pad it to make it compatible with the class
    # predictions
    refined_box_encodings_with_background = tf.pad(refined_box_encodings,
                                                   [[0, 0], [1, 0], [0, 0]])
    refined_box_encodings_masked_by_class_targets = (
        box_list_ops.boolean_mask(
            box_list.BoxList(
                tf.reshape(refined_box_encodings_with_background,
                           [-1, self._box_coder.code_size])),
            tf.reshape(tf.greater(flat_cls_targets_with_background, 0), [-1]),
            use_static_shapes=self._use_static_shapes,
            indicator_sum=batch_size * self.max_num_proposals
            if self._use_static_shapes else None).get())
    return tf.reshape(
        refined_box_encodings_masked_by_class_targets, [
            batch_size, self.max_num_proposals,
            self._box_coder.code_size
        ])
Example #25
Source File: box_list_ops_test.py    From MAX-Object-Detector with Apache License 2.0 6 votes vote down vote up 
def test_static_boolean_mask_with_field(self):

    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'))

    corners = np.array(
        [4 * [0.0], 4 * [1.0], 4 * [2.0], 4 * [3.0], 4 * [4.0]],
        dtype=np.float32)
    indicator = np.array([True, False, True, False, True], dtype=np.bool)
    weights = np.array([[.1], [.3], [.5], [.7], [.9]], dtype=np.float32)
    result_boxes, result_weights = self.execute(graph_fn,
                                                [corners, weights, indicator])
    expected_boxes = [4 * [0.0], 4 * [2.0], 4 * [4.0]]
    expected_weights = [[.1], [.5], [.9]]

    self.assertAllClose(result_boxes, expected_boxes)
    self.assertAllClose(result_weights, expected_weights)
Example #26
Source File: box_list_ops_test.py    From MAX-Object-Detector with Apache License 2.0 6 votes vote down vote up 
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 #27
Source File: box_list_ops_test.py    From Accident-Detection-on-Indian-Roads with GNU Affero General Public License v3.0 6 votes vote down vote up 
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 #28
Source File: faster_rcnn_meta_arch.py    From g-tensorflow-models with Apache License 2.0 6 votes vote down vote up 
def _get_refined_encodings_for_postitive_class(
      self, refined_box_encodings, flat_cls_targets_with_background,
      batch_size):
    # We only predict refined location encodings for the non background
    # classes, but we now pad it to make it compatible with the class
    # predictions
    refined_box_encodings_with_background = tf.pad(refined_box_encodings,
                                                   [[0, 0], [1, 0], [0, 0]])
    refined_box_encodings_masked_by_class_targets = (
        box_list_ops.boolean_mask(
            box_list.BoxList(
                tf.reshape(refined_box_encodings_with_background,
                           [-1, self._box_coder.code_size])),
            tf.reshape(tf.greater(flat_cls_targets_with_background, 0), [-1]),
            use_static_shapes=self._use_static_shapes,
            indicator_sum=batch_size * self.max_num_proposals
            if self._use_static_shapes else None).get())
    return tf.reshape(
        refined_box_encodings_masked_by_class_targets, [
            batch_size, self.max_num_proposals,
            self._box_coder.code_size
        ])
Example #29
Source File: box_list_ops_test.py    From g-tensorflow-models with Apache License 2.0 6 votes vote down vote up 
def test_static_boolean_mask_with_field(self):

    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'))

    corners = np.array(
        [4 * [0.0], 4 * [1.0], 4 * [2.0], 4 * [3.0], 4 * [4.0]],
        dtype=np.float32)
    indicator = np.array([True, False, True, False, True], dtype=np.bool)
    weights = np.array([[.1], [.3], [.5], [.7], [.9]], dtype=np.float32)
    result_boxes, result_weights = self.execute(graph_fn,
                                                [corners, weights, indicator])
    expected_boxes = [4 * [0.0], 4 * [2.0], 4 * [4.0]]
    expected_weights = [[.1], [.5], [.9]]

    self.assertAllClose(result_boxes, expected_boxes)
    self.assertAllClose(result_weights, expected_weights)
Example #30
Source File: box_list_ops_test.py    From g-tensorflow-models with Apache License 2.0 6 votes vote down vote up 
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)