Python object_detection.core.keypoint_ops.clip_to_window() Examples

The following are 30 code examples of object_detection.core.keypoint_ops.clip_to_window(). 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.keypoint_ops , or try the search function .
Example #1
Source File: keypoint_ops_test.py    From hands-detection with MIT License 6 votes vote down vote up 
def test_clip_to_window(self):
    keypoints = tf.constant([
        [[0.25, 0.5], [0.75, 0.75]],
        [[0.5, 0.0], [1.0, 1.0]]
    ])
    window = tf.constant([0.25, 0.25, 0.75, 0.75])

    expected_keypoints = tf.constant([
        [[0.25, 0.5], [0.75, 0.75]],
        [[0.5, 0.25], [0.75, 0.75]]
    ])
    output = keypoint_ops.clip_to_window(keypoints, window)

    with self.test_session() as sess:
      output_, expected_keypoints_ = sess.run([output, expected_keypoints])
      self.assertAllClose(output_, expected_keypoints_)
Example #2
Source File: keypoint_ops_test.py    From multilabel-image-classification-tensorflow with MIT License 6 votes vote down vote up 
def test_clip_to_window(self):
    keypoints = tf.constant([
        [[0.25, 0.5], [0.75, 0.75]],
        [[0.5, 0.0], [1.0, 1.0]]
    ])
    window = tf.constant([0.25, 0.25, 0.75, 0.75])

    expected_keypoints = tf.constant([
        [[0.25, 0.5], [0.75, 0.75]],
        [[0.5, 0.25], [0.75, 0.75]]
    ])
    output = keypoint_ops.clip_to_window(keypoints, window)

    with self.test_session() as sess:
      output_, expected_keypoints_ = sess.run([output, expected_keypoints])
      self.assertAllClose(output_, expected_keypoints_)
Example #3
Source File: keypoint_ops_test.py    From mtl-ssl with Apache License 2.0 6 votes vote down vote up 
def test_clip_to_window(self):
    keypoints = tf.constant([
        [[0.25, 0.5], [0.75, 0.75]],
        [[0.5, 0.0], [1.0, 1.0]]
    ])
    window = tf.constant([0.25, 0.25, 0.75, 0.75])

    expected_keypoints = tf.constant([
        [[0.25, 0.5], [0.75, 0.75]],
        [[0.5, 0.25], [0.75, 0.75]]
    ])
    output = keypoint_ops.clip_to_window(keypoints, window)

    with self.test_session() as sess:
      output_, expected_keypoints_ = sess.run([output, expected_keypoints])
      self.assertAllClose(output_, expected_keypoints_)
Example #4
Source File: keypoint_ops_test.py    From motion-rcnn with MIT License 6 votes vote down vote up 
def test_clip_to_window(self):
    keypoints = tf.constant([
        [[0.25, 0.5], [0.75, 0.75]],
        [[0.5, 0.0], [1.0, 1.0]]
    ])
    window = tf.constant([0.25, 0.25, 0.75, 0.75])

    expected_keypoints = tf.constant([
        [[0.25, 0.5], [0.75, 0.75]],
        [[0.5, 0.25], [0.75, 0.75]]
    ])
    output = keypoint_ops.clip_to_window(keypoints, window)

    with self.test_session() as sess:
      output_, expected_keypoints_ = sess.run([output, expected_keypoints])
      self.assertAllClose(output_, expected_keypoints_)
Example #5
Source File: keypoint_ops_test.py    From models with Apache License 2.0 6 votes vote down vote up 
def test_clip_to_window(self):
    def graph_fn():
      keypoints = tf.constant([
          [[0.25, 0.5], [0.75, 0.75]],
          [[0.5, 0.0], [1.0, 1.0]]
      ])
      window = tf.constant([0.25, 0.25, 0.75, 0.75])

      expected_keypoints = tf.constant([
          [[0.25, 0.5], [0.75, 0.75]],
          [[0.5, 0.25], [0.75, 0.75]]
      ])
      output = keypoint_ops.clip_to_window(keypoints, window)
      return output, expected_keypoints
    output, expected_keypoints = self.execute(graph_fn, [])
    self.assertAllClose(output, expected_keypoints)
Example #6
Source File: keypoint_ops_test.py    From g-tensorflow-models with Apache License 2.0 6 votes vote down vote up 
def test_clip_to_window(self):
    keypoints = tf.constant([
        [[0.25, 0.5], [0.75, 0.75]],
        [[0.5, 0.0], [1.0, 1.0]]
    ])
    window = tf.constant([0.25, 0.25, 0.75, 0.75])

    expected_keypoints = tf.constant([
        [[0.25, 0.5], [0.75, 0.75]],
        [[0.5, 0.25], [0.75, 0.75]]
    ])
    output = keypoint_ops.clip_to_window(keypoints, window)

    with self.test_session() as sess:
      output_, expected_keypoints_ = sess.run([output, expected_keypoints])
      self.assertAllClose(output_, expected_keypoints_)
Example #7
Source File: keypoint_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_clip_to_window(self):
    keypoints = tf.constant([
        [[0.25, 0.5], [0.75, 0.75]],
        [[0.5, 0.0], [1.0, 1.0]]
    ])
    window = tf.constant([0.25, 0.25, 0.75, 0.75])

    expected_keypoints = tf.constant([
        [[0.25, 0.5], [0.75, 0.75]],
        [[0.5, 0.25], [0.75, 0.75]]
    ])
    output = keypoint_ops.clip_to_window(keypoints, window)

    with self.test_session() as sess:
      output_, expected_keypoints_ = sess.run([output, expected_keypoints])
      self.assertAllClose(output_, expected_keypoints_)
Example #8
Source File: keypoint_ops_test.py    From MAX-Object-Detector with Apache License 2.0 6 votes vote down vote up 
def test_clip_to_window(self):
    keypoints = tf.constant([
        [[0.25, 0.5], [0.75, 0.75]],
        [[0.5, 0.0], [1.0, 1.0]]
    ])
    window = tf.constant([0.25, 0.25, 0.75, 0.75])

    expected_keypoints = tf.constant([
        [[0.25, 0.5], [0.75, 0.75]],
        [[0.5, 0.25], [0.75, 0.75]]
    ])
    output = keypoint_ops.clip_to_window(keypoints, window)

    with self.test_session() as sess:
      output_, expected_keypoints_ = sess.run([output, expected_keypoints])
      self.assertAllClose(output_, expected_keypoints_)
Example #9
Source File: keypoint_ops_test.py    From AniSeg with Apache License 2.0 6 votes vote down vote up 
def test_clip_to_window(self):
    keypoints = tf.constant([
        [[0.25, 0.5], [0.75, 0.75]],
        [[0.5, 0.0], [1.0, 1.0]]
    ])
    window = tf.constant([0.25, 0.25, 0.75, 0.75])

    expected_keypoints = tf.constant([
        [[0.25, 0.5], [0.75, 0.75]],
        [[0.5, 0.25], [0.75, 0.75]]
    ])
    output = keypoint_ops.clip_to_window(keypoints, window)

    with self.test_session() as sess:
      output_, expected_keypoints_ = sess.run([output, expected_keypoints])
      self.assertAllClose(output_, expected_keypoints_)
Example #10
Source File: keypoint_ops_test.py    From object_detection_with_tensorflow with MIT License 6 votes vote down vote up 
def test_clip_to_window(self):
    keypoints = tf.constant([
        [[0.25, 0.5], [0.75, 0.75]],
        [[0.5, 0.0], [1.0, 1.0]]
    ])
    window = tf.constant([0.25, 0.25, 0.75, 0.75])

    expected_keypoints = tf.constant([
        [[0.25, 0.5], [0.75, 0.75]],
        [[0.5, 0.25], [0.75, 0.75]]
    ])
    output = keypoint_ops.clip_to_window(keypoints, window)

    with self.test_session() as sess:
      output_, expected_keypoints_ = sess.run([output, expected_keypoints])
      self.assertAllClose(output_, expected_keypoints_)
Example #11
Source File: keypoint_ops_test.py    From object_detection_with_tensorflow with MIT License 6 votes vote down vote up 
def test_clip_to_window(self):
    keypoints = tf.constant([
        [[0.25, 0.5], [0.75, 0.75]],
        [[0.5, 0.0], [1.0, 1.0]]
    ])
    window = tf.constant([0.25, 0.25, 0.75, 0.75])

    expected_keypoints = tf.constant([
        [[0.25, 0.5], [0.75, 0.75]],
        [[0.5, 0.25], [0.75, 0.75]]
    ])
    output = keypoint_ops.clip_to_window(keypoints, window)

    with self.test_session() as sess:
      output_, expected_keypoints_ = sess.run([output, expected_keypoints])
      self.assertAllClose(output_, expected_keypoints_)
Example #12
Source File: keypoint_ops_test.py    From Elphas with Apache License 2.0 6 votes vote down vote up 
def test_clip_to_window(self):
    keypoints = tf.constant([
        [[0.25, 0.5], [0.75, 0.75]],
        [[0.5, 0.0], [1.0, 1.0]]
    ])
    window = tf.constant([0.25, 0.25, 0.75, 0.75])

    expected_keypoints = tf.constant([
        [[0.25, 0.5], [0.75, 0.75]],
        [[0.5, 0.25], [0.75, 0.75]]
    ])
    output = keypoint_ops.clip_to_window(keypoints, window)

    with self.test_session() as sess:
      output_, expected_keypoints_ = sess.run([output, expected_keypoints])
      self.assertAllClose(output_, expected_keypoints_)
Example #13
Source File: keypoint_ops_test.py    From MBMD with MIT License 6 votes vote down vote up 
def test_clip_to_window(self):
    keypoints = tf.constant([
        [[0.25, 0.5], [0.75, 0.75]],
        [[0.5, 0.0], [1.0, 1.0]]
    ])
    window = tf.constant([0.25, 0.25, 0.75, 0.75])

    expected_keypoints = tf.constant([
        [[0.25, 0.5], [0.75, 0.75]],
        [[0.5, 0.25], [0.75, 0.75]]
    ])
    output = keypoint_ops.clip_to_window(keypoints, window)

    with self.test_session() as sess:
      output_, expected_keypoints_ = sess.run([output, expected_keypoints])
      self.assertAllClose(output_, expected_keypoints_)
Example #14
Source File: keypoint_ops_test.py    From object_detection_kitti with Apache License 2.0 6 votes vote down vote up 
def test_clip_to_window(self):
    keypoints = tf.constant([
        [[0.25, 0.5], [0.75, 0.75]],
        [[0.5, 0.0], [1.0, 1.0]]
    ])
    window = tf.constant([0.25, 0.25, 0.75, 0.75])

    expected_keypoints = tf.constant([
        [[0.25, 0.5], [0.75, 0.75]],
        [[0.5, 0.25], [0.75, 0.75]]
    ])
    output = keypoint_ops.clip_to_window(keypoints, window)

    with self.test_session() as sess:
      output_, expected_keypoints_ = sess.run([output, expected_keypoints])
      self.assertAllClose(output_, expected_keypoints_)
Example #15
Source File: keypoint_ops_test.py    From DOTA_models with Apache License 2.0 6 votes vote down vote up 
def test_clip_to_window(self):
    keypoints = tf.constant([
        [[0.25, 0.5], [0.75, 0.75]],
        [[0.5, 0.0], [1.0, 1.0]]
    ])
    window = tf.constant([0.25, 0.25, 0.75, 0.75])

    expected_keypoints = tf.constant([
        [[0.25, 0.5], [0.75, 0.75]],
        [[0.5, 0.25], [0.75, 0.75]]
    ])
    output = keypoint_ops.clip_to_window(keypoints, window)

    with self.test_session() as sess:
      output_, expected_keypoints_ = sess.run([output, expected_keypoints])
      self.assertAllClose(output_, expected_keypoints_)
Example #16
Source File: keypoint_ops_test.py    From moveo_ros with MIT License 6 votes vote down vote up 
def test_clip_to_window(self):
    keypoints = tf.constant([
        [[0.25, 0.5], [0.75, 0.75]],
        [[0.5, 0.0], [1.0, 1.0]]
    ])
    window = tf.constant([0.25, 0.25, 0.75, 0.75])

    expected_keypoints = tf.constant([
        [[0.25, 0.5], [0.75, 0.75]],
        [[0.5, 0.25], [0.75, 0.75]]
    ])
    output = keypoint_ops.clip_to_window(keypoints, window)

    with self.test_session() as sess:
      output_, expected_keypoints_ = sess.run([output, expected_keypoints])
      self.assertAllClose(output_, expected_keypoints_)
Example #17
Source File: keypoint_ops_test.py    From BMW-TensorFlow-Training-GUI with Apache License 2.0 6 votes vote down vote up 
def test_clip_to_window(self):
    keypoints = tf.constant([
        [[0.25, 0.5], [0.75, 0.75]],
        [[0.5, 0.0], [1.0, 1.0]]
    ])
    window = tf.constant([0.25, 0.25, 0.75, 0.75])

    expected_keypoints = tf.constant([
        [[0.25, 0.5], [0.75, 0.75]],
        [[0.5, 0.25], [0.75, 0.75]]
    ])
    output = keypoint_ops.clip_to_window(keypoints, window)

    with self.test_session() as sess:
      output_, expected_keypoints_ = sess.run([output, expected_keypoints])
      self.assertAllClose(output_, expected_keypoints_)
Example #18
Source File: keypoint_ops_test.py    From ros_tensorflow with Apache License 2.0 6 votes vote down vote up 
def test_clip_to_window(self):
    keypoints = tf.constant([
        [[0.25, 0.5], [0.75, 0.75]],
        [[0.5, 0.0], [1.0, 1.0]]
    ])
    window = tf.constant([0.25, 0.25, 0.75, 0.75])

    expected_keypoints = tf.constant([
        [[0.25, 0.5], [0.75, 0.75]],
        [[0.5, 0.25], [0.75, 0.75]]
    ])
    output = keypoint_ops.clip_to_window(keypoints, window)

    with self.test_session() as sess:
      output_, expected_keypoints_ = sess.run([output, expected_keypoints])
      self.assertAllClose(output_, expected_keypoints_)
Example #19
Source File: keypoint_ops_test.py    From Gun-Detector with Apache License 2.0 6 votes vote down vote up 
def test_clip_to_window(self):
    keypoints = tf.constant([
        [[0.25, 0.5], [0.75, 0.75]],
        [[0.5, 0.0], [1.0, 1.0]]
    ])
    window = tf.constant([0.25, 0.25, 0.75, 0.75])

    expected_keypoints = tf.constant([
        [[0.25, 0.5], [0.75, 0.75]],
        [[0.5, 0.25], [0.75, 0.75]]
    ])
    output = keypoint_ops.clip_to_window(keypoints, window)

    with self.test_session() as sess:
      output_, expected_keypoints_ = sess.run([output, expected_keypoints])
      self.assertAllClose(output_, expected_keypoints_)
Example #20
Source File: keypoint_ops_test.py    From tensorflow with BSD 2-Clause "Simplified" License 6 votes vote down vote up 
def test_clip_to_window(self):
    keypoints = tf.constant([
        [[0.25, 0.5], [0.75, 0.75]],
        [[0.5, 0.0], [1.0, 1.0]]
    ])
    window = tf.constant([0.25, 0.25, 0.75, 0.75])

    expected_keypoints = tf.constant([
        [[0.25, 0.5], [0.75, 0.75]],
        [[0.5, 0.25], [0.75, 0.75]]
    ])
    output = keypoint_ops.clip_to_window(keypoints, window)

    with self.test_session() as sess:
      output_, expected_keypoints_ = sess.run([output, expected_keypoints])
      self.assertAllClose(output_, expected_keypoints_)
Example #21
Source File: keypoint_ops_test.py    From Hands-On-Machine-Learning-with-OpenCV-4 with MIT License 6 votes vote down vote up 
def test_clip_to_window(self):
    keypoints = tf.constant([
        [[0.25, 0.5], [0.75, 0.75]],
        [[0.5, 0.0], [1.0, 1.0]]
    ])
    window = tf.constant([0.25, 0.25, 0.75, 0.75])

    expected_keypoints = tf.constant([
        [[0.25, 0.5], [0.75, 0.75]],
        [[0.5, 0.25], [0.75, 0.75]]
    ])
    output = keypoint_ops.clip_to_window(keypoints, window)

    with self.test_session() as sess:
      output_, expected_keypoints_ = sess.run([output, expected_keypoints])
      self.assertAllClose(output_, expected_keypoints_)
Example #22
Source File: keypoint_ops_test.py    From Traffic-Rule-Violation-Detection-System with MIT License 6 votes vote down vote up 
def test_clip_to_window(self):
    keypoints = tf.constant([
        [[0.25, 0.5], [0.75, 0.75]],
        [[0.5, 0.0], [1.0, 1.0]]
    ])
    window = tf.constant([0.25, 0.25, 0.75, 0.75])

    expected_keypoints = tf.constant([
        [[0.25, 0.5], [0.75, 0.75]],
        [[0.5, 0.25], [0.75, 0.75]]
    ])
    output = keypoint_ops.clip_to_window(keypoints, window)

    with self.test_session() as sess:
      output_, expected_keypoints_ = sess.run([output, expected_keypoints])
      self.assertAllClose(output_, expected_keypoints_)
Example #23
Source File: keypoint_ops_test.py    From yolo_v2 with Apache License 2.0 6 votes vote down vote up 
def test_clip_to_window(self):
    keypoints = tf.constant([
        [[0.25, 0.5], [0.75, 0.75]],
        [[0.5, 0.0], [1.0, 1.0]]
    ])
    window = tf.constant([0.25, 0.25, 0.75, 0.75])

    expected_keypoints = tf.constant([
        [[0.25, 0.5], [0.75, 0.75]],
        [[0.5, 0.25], [0.75, 0.75]]
    ])
    output = keypoint_ops.clip_to_window(keypoints, window)

    with self.test_session() as sess:
      output_, expected_keypoints_ = sess.run([output, expected_keypoints])
      self.assertAllClose(output_, expected_keypoints_)
Example #24
Source File: keypoint_ops_test.py    From HereIsWally with MIT License 6 votes vote down vote up 
def test_clip_to_window(self):
    keypoints = tf.constant([
        [[0.25, 0.5], [0.75, 0.75]],
        [[0.5, 0.0], [1.0, 1.0]]
    ])
    window = tf.constant([0.25, 0.25, 0.75, 0.75])

    expected_keypoints = tf.constant([
        [[0.25, 0.5], [0.75, 0.75]],
        [[0.5, 0.25], [0.75, 0.75]]
    ])
    output = keypoint_ops.clip_to_window(keypoints, window)

    with self.test_session() as sess:
      output_, expected_keypoints_ = sess.run([output, expected_keypoints])
      self.assertAllClose(output_, expected_keypoints_)
Example #25
Source File: keypoint_ops_test.py    From garbage-object-detection-tensorflow with MIT License 6 votes vote down vote up 
def test_clip_to_window(self):
    keypoints = tf.constant([
        [[0.25, 0.5], [0.75, 0.75]],
        [[0.5, 0.0], [1.0, 1.0]]
    ])
    window = tf.constant([0.25, 0.25, 0.75, 0.75])

    expected_keypoints = tf.constant([
        [[0.25, 0.5], [0.75, 0.75]],
        [[0.5, 0.25], [0.75, 0.75]]
    ])
    output = keypoint_ops.clip_to_window(keypoints, window)

    with self.test_session() as sess:
      output_, expected_keypoints_ = sess.run([output, expected_keypoints])
      self.assertAllClose(output_, expected_keypoints_)
Example #26
Source File: keypoint_ops_test.py    From Person-Detection-and-Tracking with MIT License 6 votes vote down vote up 
def test_clip_to_window(self):
    keypoints = tf.constant([
        [[0.25, 0.5], [0.75, 0.75]],
        [[0.5, 0.0], [1.0, 1.0]]
    ])
    window = tf.constant([0.25, 0.25, 0.75, 0.75])

    expected_keypoints = tf.constant([
        [[0.25, 0.5], [0.75, 0.75]],
        [[0.5, 0.25], [0.75, 0.75]]
    ])
    output = keypoint_ops.clip_to_window(keypoints, window)

    with self.test_session() as sess:
      output_, expected_keypoints_ = sess.run([output, expected_keypoints])
      self.assertAllClose(output_, expected_keypoints_)
Example #27
Source File: keypoint_ops_test.py    From ros_people_object_detection_tensorflow with Apache License 2.0 6 votes vote down vote up 
def test_clip_to_window(self):
    keypoints = tf.constant([
        [[0.25, 0.5], [0.75, 0.75]],
        [[0.5, 0.0], [1.0, 1.0]]
    ])
    window = tf.constant([0.25, 0.25, 0.75, 0.75])

    expected_keypoints = tf.constant([
        [[0.25, 0.5], [0.75, 0.75]],
        [[0.5, 0.25], [0.75, 0.75]]
    ])
    output = keypoint_ops.clip_to_window(keypoints, window)

    with self.test_session() as sess:
      output_, expected_keypoints_ = sess.run([output, expected_keypoints])
      self.assertAllClose(output_, expected_keypoints_)
Example #28
Source File: keypoint_ops_test.py    From vehicle_counting_tensorflow with MIT License 6 votes vote down vote up 
def test_clip_to_window(self):
    keypoints = tf.constant([
        [[0.25, 0.5], [0.75, 0.75]],
        [[0.5, 0.0], [1.0, 1.0]]
    ])
    window = tf.constant([0.25, 0.25, 0.75, 0.75])

    expected_keypoints = tf.constant([
        [[0.25, 0.5], [0.75, 0.75]],
        [[0.5, 0.25], [0.75, 0.75]]
    ])
    output = keypoint_ops.clip_to_window(keypoints, window)

    with self.test_session() as sess:
      output_, expected_keypoints_ = sess.run([output, expected_keypoints])
      self.assertAllClose(output_, expected_keypoints_)
Example #29
Source File: keypoint_ops_test.py    From object_detector_app with MIT License 6 votes vote down vote up 
def test_clip_to_window(self):
    keypoints = tf.constant([
        [[0.25, 0.5], [0.75, 0.75]],
        [[0.5, 0.0], [1.0, 1.0]]
    ])
    window = tf.constant([0.25, 0.25, 0.75, 0.75])

    expected_keypoints = tf.constant([
        [[0.25, 0.5], [0.75, 0.75]],
        [[0.5, 0.25], [0.75, 0.75]]
    ])
    output = keypoint_ops.clip_to_window(keypoints, window)

    with self.test_session() as sess:
      output_, expected_keypoints_ = sess.run([output, expected_keypoints])
      self.assertAllClose(output_, expected_keypoints_)
Example #30
Source File: center_net_meta_arch.py    From models with Apache License 2.0 5 votes vote down vote up 
def convert_strided_predictions_to_normalized_boxes(boxes, stride,
                                                    true_image_shapes):
  """Converts predictions in the output space to normalized boxes.

  Boxes falling outside the valid image boundary are clipped to be on the
  boundary.

  Args:
    boxes: A tensor of shape [batch_size, num_boxes, 4] holding the raw
     coordinates of boxes in the model's output space.
    stride: The stride in the output space.
    true_image_shapes: A tensor of shape [batch_size, 3] representing the true
      shape of the input not considering padding.

  Returns:
    boxes: A tensor of shape [batch_size, num_boxes, 4] representing the
      coordinates of the normalized boxes.
  """

  def _normalize_boxlist(args):

    boxes, height, width = args
    boxes = box_list_ops.scale(boxes, stride, stride)
    boxes = box_list_ops.to_normalized_coordinates(boxes, height, width)
    boxes = box_list_ops.clip_to_window(boxes, [0., 0., 1., 1.],
                                        filter_nonoverlapping=False)
    return boxes

  box_lists = [box_list.BoxList(boxes) for boxes in tf.unstack(boxes, axis=0)]
  true_heights, true_widths, _ = tf.unstack(true_image_shapes, axis=1)

  true_heights_list = tf.unstack(true_heights, axis=0)
  true_widths_list = tf.unstack(true_widths, axis=0)

  box_lists = list(map(_normalize_boxlist,
                       zip(box_lists, true_heights_list, true_widths_list)))
  boxes = tf.stack([box_list_instance.get() for
                    box_list_instance in box_lists], axis=0)

  return boxes