Python object_detection.utils.shape_utils.pad_or_clip_tensor() Examples

The following are 30 code examples of object_detection.utils.shape_utils.pad_or_clip_tensor(). 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.shape_utils , or try the search function .
Example #1
Source File: shape_utils_test.py    From MBMD with MIT License 6 votes vote down vote up 
def test_pad_or_clip_tensor_using_integer_input(self):
    t1 = tf.constant([1], dtype=tf.int32)
    tt1 = shape_utils.pad_or_clip_tensor(t1, 2)
    t2 = tf.constant([[0.1, 0.2]], dtype=tf.float32)
    tt2 = shape_utils.pad_or_clip_tensor(t2, 2)

    t3 = tf.constant([1, 2, 3], dtype=tf.int32)
    tt3 = shape_utils.clip_tensor(t3, 2)
    t4 = tf.constant([[0.1, 0.2], [0.2, 0.4], [0.5, 0.8]], dtype=tf.float32)
    tt4 = shape_utils.clip_tensor(t4, 2)

    self.assertEqual(2, tt1.get_shape()[0])
    self.assertEqual(2, tt2.get_shape()[0])
    self.assertEqual(2, tt3.get_shape()[0])
    self.assertEqual(2, tt4.get_shape()[0])

    with self.test_session() as sess:
      tt1_result, tt2_result, tt3_result, tt4_result = sess.run(
          [tt1, tt2, tt3, tt4])
      self.assertAllEqual([1, 0], tt1_result)
      self.assertAllClose([[0.1, 0.2], [0, 0]], tt2_result)
      self.assertAllEqual([1, 2], tt3_result)
      self.assertAllClose([[0.1, 0.2], [0.2, 0.4]], tt4_result)
Example #2
Source File: shape_utils_test.py    From open-solution-googleai-object-detection with MIT License 6 votes vote down vote up 
def test_pad_or_clip_tensor_using_tensor_input(self):
    t1 = tf.constant([1], dtype=tf.int32)
    tt1 = shape_utils.pad_or_clip_tensor(t1, tf.constant(2))
    t2 = tf.constant([[0.1, 0.2]], dtype=tf.float32)
    tt2 = shape_utils.pad_or_clip_tensor(t2, tf.constant(2))

    t3 = tf.constant([1, 2, 3], dtype=tf.int32)
    tt3 = shape_utils.clip_tensor(t3, tf.constant(2))
    t4 = tf.constant([[0.1, 0.2], [0.2, 0.4], [0.5, 0.8]], dtype=tf.float32)
    tt4 = shape_utils.clip_tensor(t4, tf.constant(2))

    with self.test_session() as sess:
      tt1_result, tt2_result, tt3_result, tt4_result = sess.run(
          [tt1, tt2, tt3, tt4])
      self.assertAllEqual([1, 0], tt1_result)
      self.assertAllClose([[0.1, 0.2], [0, 0]], tt2_result)
      self.assertAllEqual([1, 2], tt3_result)
      self.assertAllClose([[0.1, 0.2], [0.2, 0.4]], tt4_result)
Example #3
Source File: shape_utils_test.py    From AniSeg with Apache License 2.0 6 votes vote down vote up 
def test_pad_or_clip_tensor_using_tensor_input(self):
    t1 = tf.constant([1], dtype=tf.int32)
    tt1 = shape_utils.pad_or_clip_tensor(t1, tf.constant(2))
    t2 = tf.constant([[0.1, 0.2]], dtype=tf.float32)
    tt2 = shape_utils.pad_or_clip_tensor(t2, tf.constant(2))

    t3 = tf.constant([1, 2, 3], dtype=tf.int32)
    tt3 = shape_utils.clip_tensor(t3, tf.constant(2))
    t4 = tf.constant([[0.1, 0.2], [0.2, 0.4], [0.5, 0.8]], dtype=tf.float32)
    tt4 = shape_utils.clip_tensor(t4, tf.constant(2))

    with self.test_session() as sess:
      tt1_result, tt2_result, tt3_result, tt4_result = sess.run(
          [tt1, tt2, tt3, tt4])
      self.assertAllEqual([1, 0], tt1_result)
      self.assertAllClose([[0.1, 0.2], [0, 0]], tt2_result)
      self.assertAllEqual([1, 2], tt3_result)
      self.assertAllClose([[0.1, 0.2], [0.2, 0.4]], tt4_result)
Example #4
Source File: shape_utils_test.py    From g-tensorflow-models with Apache License 2.0 6 votes vote down vote up 
def test_pad_or_clip_tensor_using_integer_input(self):
    t1 = tf.constant([1], dtype=tf.int32)
    tt1 = shape_utils.pad_or_clip_tensor(t1, 2)
    t2 = tf.constant([[0.1, 0.2]], dtype=tf.float32)
    tt2 = shape_utils.pad_or_clip_tensor(t2, 2)

    t3 = tf.constant([1, 2, 3], dtype=tf.int32)
    tt3 = shape_utils.clip_tensor(t3, 2)
    t4 = tf.constant([[0.1, 0.2], [0.2, 0.4], [0.5, 0.8]], dtype=tf.float32)
    tt4 = shape_utils.clip_tensor(t4, 2)

    self.assertEqual(2, tt1.get_shape()[0])
    self.assertEqual(2, tt2.get_shape()[0])
    self.assertEqual(2, tt3.get_shape()[0])
    self.assertEqual(2, tt4.get_shape()[0])

    with self.test_session() as sess:
      tt1_result, tt2_result, tt3_result, tt4_result = sess.run(
          [tt1, tt2, tt3, tt4])
      self.assertAllEqual([1, 0], tt1_result)
      self.assertAllClose([[0.1, 0.2], [0, 0]], tt2_result)
      self.assertAllEqual([1, 2], tt3_result)
      self.assertAllClose([[0.1, 0.2], [0.2, 0.4]], tt4_result)
Example #5
Source File: shape_utils_test.py    From g-tensorflow-models with Apache License 2.0 6 votes vote down vote up 
def test_pad_or_clip_tensor_using_tensor_input(self):
    t1 = tf.constant([1], dtype=tf.int32)
    tt1 = shape_utils.pad_or_clip_tensor(t1, tf.constant(2))
    t2 = tf.constant([[0.1, 0.2]], dtype=tf.float32)
    tt2 = shape_utils.pad_or_clip_tensor(t2, tf.constant(2))

    t3 = tf.constant([1, 2, 3], dtype=tf.int32)
    tt3 = shape_utils.clip_tensor(t3, tf.constant(2))
    t4 = tf.constant([[0.1, 0.2], [0.2, 0.4], [0.5, 0.8]], dtype=tf.float32)
    tt4 = shape_utils.clip_tensor(t4, tf.constant(2))

    with self.test_session() as sess:
      tt1_result, tt2_result, tt3_result, tt4_result = sess.run(
          [tt1, tt2, tt3, tt4])
      self.assertAllEqual([1, 0], tt1_result)
      self.assertAllClose([[0.1, 0.2], [0, 0]], tt2_result)
      self.assertAllEqual([1, 2], tt3_result)
      self.assertAllClose([[0.1, 0.2], [0.2, 0.4]], tt4_result)
Example #6
Source File: box_list_ops.py    From Accident-Detection-on-Indian-Roads with GNU Affero General Public License v3.0 6 votes vote down vote up 
def pad_or_clip_box_list(boxlist, num_boxes, scope=None):
  """Pads or clips all fields of a BoxList.

  Args:
    boxlist: A BoxList with arbitrary of number of boxes.
    num_boxes: First num_boxes in boxlist are kept.
      The fields are zero-padded if num_boxes is bigger than the
      actual number of boxes.
    scope: name scope.

  Returns:
    BoxList with all fields padded or clipped.
  """
  with tf.name_scope(scope, 'PadOrClipBoxList'):
    subboxlist = box_list.BoxList(shape_utils.pad_or_clip_tensor(
        boxlist.get(), num_boxes))
    for field in boxlist.get_extra_fields():
      subfield = shape_utils.pad_or_clip_tensor(
          boxlist.get_field(field), num_boxes)
      subboxlist.add_field(field, subfield)
    return subboxlist
Example #7
Source File: box_list_ops.py    From MAX-Object-Detector with Apache License 2.0 6 votes vote down vote up 
def pad_or_clip_box_list(boxlist, num_boxes, scope=None):
  """Pads or clips all fields of a BoxList.

  Args:
    boxlist: A BoxList with arbitrary of number of boxes.
    num_boxes: First num_boxes in boxlist are kept.
      The fields are zero-padded if num_boxes is bigger than the
      actual number of boxes.
    scope: name scope.

  Returns:
    BoxList with all fields padded or clipped.
  """
  with tf.name_scope(scope, 'PadOrClipBoxList'):
    subboxlist = box_list.BoxList(shape_utils.pad_or_clip_tensor(
        boxlist.get(), num_boxes))
    for field in boxlist.get_extra_fields():
      subfield = shape_utils.pad_or_clip_tensor(
          boxlist.get_field(field), num_boxes)
      subboxlist.add_field(field, subfield)
    return subboxlist
Example #8
Source File: shape_utils_test.py    From MAX-Object-Detector with Apache License 2.0 6 votes vote down vote up 
def test_pad_or_clip_tensor_using_tensor_input(self):
    t1 = tf.constant([1], dtype=tf.int32)
    tt1 = shape_utils.pad_or_clip_tensor(t1, tf.constant(2))
    t2 = tf.constant([[0.1, 0.2]], dtype=tf.float32)
    tt2 = shape_utils.pad_or_clip_tensor(t2, tf.constant(2))

    t3 = tf.constant([1, 2, 3], dtype=tf.int32)
    tt3 = shape_utils.clip_tensor(t3, tf.constant(2))
    t4 = tf.constant([[0.1, 0.2], [0.2, 0.4], [0.5, 0.8]], dtype=tf.float32)
    tt4 = shape_utils.clip_tensor(t4, tf.constant(2))

    with self.test_session() as sess:
      tt1_result, tt2_result, tt3_result, tt4_result = sess.run(
          [tt1, tt2, tt3, tt4])
      self.assertAllEqual([1, 0], tt1_result)
      self.assertAllClose([[0.1, 0.2], [0, 0]], tt2_result)
      self.assertAllEqual([1, 2], tt3_result)
      self.assertAllClose([[0.1, 0.2], [0.2, 0.4]], tt4_result)
Example #9
Source File: shape_utils_test.py    From MAX-Object-Detector with Apache License 2.0 6 votes vote down vote up 
def test_pad_or_clip_tensor_using_integer_input(self):
    t1 = tf.constant([1], dtype=tf.int32)
    tt1 = shape_utils.pad_or_clip_tensor(t1, 2)
    t2 = tf.constant([[0.1, 0.2]], dtype=tf.float32)
    tt2 = shape_utils.pad_or_clip_tensor(t2, 2)

    t3 = tf.constant([1, 2, 3], dtype=tf.int32)
    tt3 = shape_utils.clip_tensor(t3, 2)
    t4 = tf.constant([[0.1, 0.2], [0.2, 0.4], [0.5, 0.8]], dtype=tf.float32)
    tt4 = shape_utils.clip_tensor(t4, 2)

    self.assertEqual(2, tt1.get_shape()[0])
    self.assertEqual(2, tt2.get_shape()[0])
    self.assertEqual(2, tt3.get_shape()[0])
    self.assertEqual(2, tt4.get_shape()[0])

    with self.test_session() as sess:
      tt1_result, tt2_result, tt3_result, tt4_result = sess.run(
          [tt1, tt2, tt3, tt4])
      self.assertAllEqual([1, 0], tt1_result)
      self.assertAllClose([[0.1, 0.2], [0, 0]], tt2_result)
      self.assertAllEqual([1, 2], tt3_result)
      self.assertAllClose([[0.1, 0.2], [0.2, 0.4]], tt4_result)
Example #10
Source File: box_list_ops.py    From AniSeg with Apache License 2.0 6 votes vote down vote up 
def pad_or_clip_box_list(boxlist, num_boxes, scope=None):
  """Pads or clips all fields of a BoxList.

  Args:
    boxlist: A BoxList with arbitrary of number of boxes.
    num_boxes: First num_boxes in boxlist are kept.
      The fields are zero-padded if num_boxes is bigger than the
      actual number of boxes.
    scope: name scope.

  Returns:
    BoxList with all fields padded or clipped.
  """
  with tf.name_scope(scope, 'PadOrClipBoxList'):
    subboxlist = box_list.BoxList(shape_utils.pad_or_clip_tensor(
        boxlist.get(), num_boxes))
    for field in boxlist.get_extra_fields():
      subfield = shape_utils.pad_or_clip_tensor(
          boxlist.get_field(field), num_boxes)
      subboxlist.add_field(field, subfield)
    return subboxlist
Example #11
Source File: shape_utils_test.py    From open-solution-googleai-object-detection with MIT License 6 votes vote down vote up 
def test_pad_or_clip_tensor_using_integer_input(self):
    t1 = tf.constant([1], dtype=tf.int32)
    tt1 = shape_utils.pad_or_clip_tensor(t1, 2)
    t2 = tf.constant([[0.1, 0.2]], dtype=tf.float32)
    tt2 = shape_utils.pad_or_clip_tensor(t2, 2)

    t3 = tf.constant([1, 2, 3], dtype=tf.int32)
    tt3 = shape_utils.clip_tensor(t3, 2)
    t4 = tf.constant([[0.1, 0.2], [0.2, 0.4], [0.5, 0.8]], dtype=tf.float32)
    tt4 = shape_utils.clip_tensor(t4, 2)

    self.assertEqual(2, tt1.get_shape()[0])
    self.assertEqual(2, tt2.get_shape()[0])
    self.assertEqual(2, tt3.get_shape()[0])
    self.assertEqual(2, tt4.get_shape()[0])

    with self.test_session() as sess:
      tt1_result, tt2_result, tt3_result, tt4_result = sess.run(
          [tt1, tt2, tt3, tt4])
      self.assertAllEqual([1, 0], tt1_result)
      self.assertAllClose([[0.1, 0.2], [0, 0]], tt2_result)
      self.assertAllEqual([1, 2], tt3_result)
      self.assertAllClose([[0.1, 0.2], [0.2, 0.4]], tt4_result)
Example #12
Source File: shape_utils_test.py    From Elphas with Apache License 2.0 6 votes vote down vote up 
def test_pad_or_clip_tensor_using_tensor_input(self):
    t1 = tf.constant([1], dtype=tf.int32)
    tt1 = shape_utils.pad_or_clip_tensor(t1, tf.constant(2))
    t2 = tf.constant([[0.1, 0.2]], dtype=tf.float32)
    tt2 = shape_utils.pad_or_clip_tensor(t2, tf.constant(2))

    t3 = tf.constant([1, 2, 3], dtype=tf.int32)
    tt3 = shape_utils.clip_tensor(t3, tf.constant(2))
    t4 = tf.constant([[0.1, 0.2], [0.2, 0.4], [0.5, 0.8]], dtype=tf.float32)
    tt4 = shape_utils.clip_tensor(t4, tf.constant(2))

    with self.test_session() as sess:
      tt1_result, tt2_result, tt3_result, tt4_result = sess.run(
          [tt1, tt2, tt3, tt4])
      self.assertAllEqual([1, 0], tt1_result)
      self.assertAllClose([[0.1, 0.2], [0, 0]], tt2_result)
      self.assertAllEqual([1, 2], tt3_result)
      self.assertAllClose([[0.1, 0.2], [0.2, 0.4]], tt4_result)
Example #13
Source File: shape_utils_test.py    From Elphas with Apache License 2.0 6 votes vote down vote up 
def test_pad_or_clip_tensor_using_integer_input(self):
    t1 = tf.constant([1], dtype=tf.int32)
    tt1 = shape_utils.pad_or_clip_tensor(t1, 2)
    t2 = tf.constant([[0.1, 0.2]], dtype=tf.float32)
    tt2 = shape_utils.pad_or_clip_tensor(t2, 2)

    t3 = tf.constant([1, 2, 3], dtype=tf.int32)
    tt3 = shape_utils.clip_tensor(t3, 2)
    t4 = tf.constant([[0.1, 0.2], [0.2, 0.4], [0.5, 0.8]], dtype=tf.float32)
    tt4 = shape_utils.clip_tensor(t4, 2)

    self.assertEqual(2, tt1.get_shape()[0])
    self.assertEqual(2, tt2.get_shape()[0])
    self.assertEqual(2, tt3.get_shape()[0])
    self.assertEqual(2, tt4.get_shape()[0])

    with self.test_session() as sess:
      tt1_result, tt2_result, tt3_result, tt4_result = sess.run(
          [tt1, tt2, tt3, tt4])
      self.assertAllEqual([1, 0], tt1_result)
      self.assertAllClose([[0.1, 0.2], [0, 0]], tt2_result)
      self.assertAllEqual([1, 2], tt3_result)
      self.assertAllClose([[0.1, 0.2], [0.2, 0.4]], tt4_result)
Example #14
Source File: box_list_ops.py    From MBMD with MIT License 6 votes vote down vote up 
def pad_or_clip_box_list(boxlist, num_boxes, scope=None):
  """Pads or clips all fields of a BoxList.

  Args:
    boxlist: A BoxList with arbitrary of number of boxes.
    num_boxes: First num_boxes in boxlist are kept.
      The fields are zero-padded if num_boxes is bigger than the
      actual number of boxes.
    scope: name scope.

  Returns:
    BoxList with all fields padded or clipped.
  """
  with tf.name_scope(scope, 'PadOrClipBoxList'):
    subboxlist = box_list.BoxList(shape_utils.pad_or_clip_tensor(
        boxlist.get(), num_boxes))
    for field in boxlist.get_extra_fields():
      subfield = shape_utils.pad_or_clip_tensor(
          boxlist.get_field(field), num_boxes)
      subboxlist.add_field(field, subfield)
    return subboxlist
Example #15
Source File: shape_utils_test.py    From MBMD with MIT License 6 votes vote down vote up 
def test_pad_or_clip_tensor_using_tensor_input(self):
    t1 = tf.constant([1], dtype=tf.int32)
    tt1 = shape_utils.pad_or_clip_tensor(t1, tf.constant(2))
    t2 = tf.constant([[0.1, 0.2]], dtype=tf.float32)
    tt2 = shape_utils.pad_or_clip_tensor(t2, tf.constant(2))

    t3 = tf.constant([1, 2, 3], dtype=tf.int32)
    tt3 = shape_utils.clip_tensor(t3, tf.constant(2))
    t4 = tf.constant([[0.1, 0.2], [0.2, 0.4], [0.5, 0.8]], dtype=tf.float32)
    tt4 = shape_utils.clip_tensor(t4, tf.constant(2))

    with self.test_session() as sess:
      tt1_result, tt2_result, tt3_result, tt4_result = sess.run(
          [tt1, tt2, tt3, tt4])
      self.assertAllEqual([1, 0], tt1_result)
      self.assertAllClose([[0.1, 0.2], [0, 0]], tt2_result)
      self.assertAllEqual([1, 2], tt3_result)
      self.assertAllClose([[0.1, 0.2], [0.2, 0.4]], tt4_result)
Example #16
Source File: box_list_ops.py    From Elphas with Apache License 2.0 6 votes vote down vote up 
def pad_or_clip_box_list(boxlist, num_boxes, scope=None):
  """Pads or clips all fields of a BoxList.

  Args:
    boxlist: A BoxList with arbitrary of number of boxes.
    num_boxes: First num_boxes in boxlist are kept.
      The fields are zero-padded if num_boxes is bigger than the
      actual number of boxes.
    scope: name scope.

  Returns:
    BoxList with all fields padded or clipped.
  """
  with tf.name_scope(scope, 'PadOrClipBoxList'):
    subboxlist = box_list.BoxList(shape_utils.pad_or_clip_tensor(
        boxlist.get(), num_boxes))
    for field in boxlist.get_extra_fields():
      subfield = shape_utils.pad_or_clip_tensor(
          boxlist.get_field(field), num_boxes)
      subboxlist.add_field(field, subfield)
    return subboxlist
Example #17
Source File: box_list_ops.py    From object_detection_kitti with Apache License 2.0 6 votes vote down vote up 
def pad_or_clip_box_list(boxlist, num_boxes, scope=None):
  """Pads or clips all fields of a BoxList.

  Args:
    boxlist: A BoxList with arbitrary of number of boxes.
    num_boxes: First num_boxes in boxlist are kept.
      The fields are zero-padded if num_boxes is bigger than the
      actual number of boxes.
    scope: name scope.

  Returns:
    BoxList with all fields padded or clipped.
  """
  with tf.name_scope(scope, 'PadOrClipBoxList'):
    subboxlist = box_list.BoxList(shape_utils.pad_or_clip_tensor(
        boxlist.get(), num_boxes))
    for field in boxlist.get_extra_fields():
      subfield = shape_utils.pad_or_clip_tensor(
          boxlist.get_field(field), num_boxes)
      subboxlist.add_field(field, subfield)
    return subboxlist
Example #18
Source File: shape_utils_test.py    From object_detection_kitti with Apache License 2.0 6 votes vote down vote up 
def test_pad_or_clip_tensor_using_tensor_input(self):
    t1 = tf.constant([1], dtype=tf.int32)
    tt1 = shape_utils.pad_or_clip_tensor(t1, tf.constant(2))
    t2 = tf.constant([[0.1, 0.2]], dtype=tf.float32)
    tt2 = shape_utils.pad_or_clip_tensor(t2, tf.constant(2))

    t3 = tf.constant([1, 2, 3], dtype=tf.int32)
    tt3 = shape_utils.clip_tensor(t3, tf.constant(2))
    t4 = tf.constant([[0.1, 0.2], [0.2, 0.4], [0.5, 0.8]], dtype=tf.float32)
    tt4 = shape_utils.clip_tensor(t4, tf.constant(2))

    with self.test_session() as sess:
      tt1_result, tt2_result, tt3_result, tt4_result = sess.run(
          [tt1, tt2, tt3, tt4])
      self.assertAllEqual([1, 0], tt1_result)
      self.assertAllClose([[0.1, 0.2], [0, 0]], tt2_result)
      self.assertAllEqual([1, 2], tt3_result)
      self.assertAllClose([[0.1, 0.2], [0.2, 0.4]], tt4_result)
Example #19
Source File: shape_utils_test.py    From object_detection_kitti with Apache License 2.0 6 votes vote down vote up 
def test_pad_or_clip_tensor_using_integer_input(self):
    t1 = tf.constant([1], dtype=tf.int32)
    tt1 = shape_utils.pad_or_clip_tensor(t1, 2)
    t2 = tf.constant([[0.1, 0.2]], dtype=tf.float32)
    tt2 = shape_utils.pad_or_clip_tensor(t2, 2)

    t3 = tf.constant([1, 2, 3], dtype=tf.int32)
    tt3 = shape_utils.clip_tensor(t3, 2)
    t4 = tf.constant([[0.1, 0.2], [0.2, 0.4], [0.5, 0.8]], dtype=tf.float32)
    tt4 = shape_utils.clip_tensor(t4, 2)

    self.assertEqual(2, tt1.get_shape()[0])
    self.assertEqual(2, tt2.get_shape()[0])
    self.assertEqual(2, tt3.get_shape()[0])
    self.assertEqual(2, tt4.get_shape()[0])

    with self.test_session() as sess:
      tt1_result, tt2_result, tt3_result, tt4_result = sess.run(
          [tt1, tt2, tt3, tt4])
      self.assertAllEqual([1, 0], tt1_result)
      self.assertAllClose([[0.1, 0.2], [0, 0]], tt2_result)
      self.assertAllEqual([1, 2], tt3_result)
      self.assertAllClose([[0.1, 0.2], [0.2, 0.4]], tt4_result)
Example #20
Source File: shape_utils_test.py    From Live-feed-object-device-identification-using-Tensorflow-and-OpenCV with Apache License 2.0 6 votes vote down vote up 
def test_pad_or_clip_tensor_using_tensor_input(self):
    t1 = tf.constant([1], dtype=tf.int32)
    tt1 = shape_utils.pad_or_clip_tensor(t1, tf.constant(2))
    t2 = tf.constant([[0.1, 0.2]], dtype=tf.float32)
    tt2 = shape_utils.pad_or_clip_tensor(t2, tf.constant(2))

    t3 = tf.constant([1, 2, 3], dtype=tf.int32)
    tt3 = shape_utils.clip_tensor(t3, tf.constant(2))
    t4 = tf.constant([[0.1, 0.2], [0.2, 0.4], [0.5, 0.8]], dtype=tf.float32)
    tt4 = shape_utils.clip_tensor(t4, tf.constant(2))

    with self.test_session() as sess:
      tt1_result, tt2_result, tt3_result, tt4_result = sess.run(
          [tt1, tt2, tt3, tt4])
      self.assertAllEqual([1, 0], tt1_result)
      self.assertAllClose([[0.1, 0.2], [0, 0]], tt2_result)
      self.assertAllEqual([1, 2], tt3_result)
      self.assertAllClose([[0.1, 0.2], [0.2, 0.4]], tt4_result)
Example #21
Source File: shape_utils_test.py    From Live-feed-object-device-identification-using-Tensorflow-and-OpenCV with Apache License 2.0 6 votes vote down vote up 
def test_pad_or_clip_tensor_using_integer_input(self):
    t1 = tf.constant([1], dtype=tf.int32)
    tt1 = shape_utils.pad_or_clip_tensor(t1, 2)
    t2 = tf.constant([[0.1, 0.2]], dtype=tf.float32)
    tt2 = shape_utils.pad_or_clip_tensor(t2, 2)

    t3 = tf.constant([1, 2, 3], dtype=tf.int32)
    tt3 = shape_utils.clip_tensor(t3, 2)
    t4 = tf.constant([[0.1, 0.2], [0.2, 0.4], [0.5, 0.8]], dtype=tf.float32)
    tt4 = shape_utils.clip_tensor(t4, 2)

    self.assertEqual(2, tt1.get_shape()[0])
    self.assertEqual(2, tt2.get_shape()[0])
    self.assertEqual(2, tt3.get_shape()[0])
    self.assertEqual(2, tt4.get_shape()[0])

    with self.test_session() as sess:
      tt1_result, tt2_result, tt3_result, tt4_result = sess.run(
          [tt1, tt2, tt3, tt4])
      self.assertAllEqual([1, 0], tt1_result)
      self.assertAllClose([[0.1, 0.2], [0, 0]], tt2_result)
      self.assertAllEqual([1, 2], tt3_result)
      self.assertAllClose([[0.1, 0.2], [0.2, 0.4]], tt4_result)
Example #22
Source File: box_list_ops.py    From hands-detection with MIT License 6 votes vote down vote up 
def pad_or_clip_box_list(boxlist, num_boxes, scope=None):
  """Pads or clips all fields of a BoxList.

  Args:
    boxlist: A BoxList with arbitrary of number of boxes.
    num_boxes: First num_boxes in boxlist are kept.
      The fields are zero-padded if num_boxes is bigger than the
      actual number of boxes.
    scope: name scope.

  Returns:
    BoxList with all fields padded or clipped.
  """
  with tf.name_scope(scope, 'PadOrClipBoxList'):
    subboxlist = box_list.BoxList(shape_utils.pad_or_clip_tensor(
        boxlist.get(), num_boxes))
    for field in boxlist.get_extra_fields():
      subfield = shape_utils.pad_or_clip_tensor(
          boxlist.get_field(field), num_boxes)
      subboxlist.add_field(field, subfield)
    return subboxlist
Example #23
Source File: shape_utils_test.py    From hands-detection with MIT License 6 votes vote down vote up 
def test_pad_or_clip_tensor_using_tensor_input(self):
    t1 = tf.constant([1], dtype=tf.int32)
    tt1 = shape_utils.pad_or_clip_tensor(t1, tf.constant(2))
    t2 = tf.constant([[0.1, 0.2]], dtype=tf.float32)
    tt2 = shape_utils.pad_or_clip_tensor(t2, tf.constant(2))

    t3 = tf.constant([1, 2, 3], dtype=tf.int32)
    tt3 = shape_utils.clip_tensor(t3, tf.constant(2))
    t4 = tf.constant([[0.1, 0.2], [0.2, 0.4], [0.5, 0.8]], dtype=tf.float32)
    tt4 = shape_utils.clip_tensor(t4, tf.constant(2))

    with self.test_session() as sess:
      tt1_result, tt2_result, tt3_result, tt4_result = sess.run(
          [tt1, tt2, tt3, tt4])
      self.assertAllEqual([1, 0], tt1_result)
      self.assertAllClose([[0.1, 0.2], [0, 0]], tt2_result)
      self.assertAllEqual([1, 2], tt3_result)
      self.assertAllClose([[0.1, 0.2], [0.2, 0.4]], tt4_result)
Example #24
Source File: shape_utils_test.py    From hands-detection with MIT License 6 votes vote down vote up 
def test_pad_or_clip_tensor_using_integer_input(self):
    t1 = tf.constant([1], dtype=tf.int32)
    tt1 = shape_utils.pad_or_clip_tensor(t1, 2)
    t2 = tf.constant([[0.1, 0.2]], dtype=tf.float32)
    tt2 = shape_utils.pad_or_clip_tensor(t2, 2)

    t3 = tf.constant([1, 2, 3], dtype=tf.int32)
    tt3 = shape_utils.clip_tensor(t3, 2)
    t4 = tf.constant([[0.1, 0.2], [0.2, 0.4], [0.5, 0.8]], dtype=tf.float32)
    tt4 = shape_utils.clip_tensor(t4, 2)

    self.assertEqual(2, tt1.get_shape()[0])
    self.assertEqual(2, tt2.get_shape()[0])
    self.assertEqual(2, tt3.get_shape()[0])
    self.assertEqual(2, tt4.get_shape()[0])

    with self.test_session() as sess:
      tt1_result, tt2_result, tt3_result, tt4_result = sess.run(
          [tt1, tt2, tt3, tt4])
      self.assertAllEqual([1, 0], tt1_result)
      self.assertAllClose([[0.1, 0.2], [0, 0]], tt2_result)
      self.assertAllEqual([1, 2], tt3_result)
      self.assertAllClose([[0.1, 0.2], [0.2, 0.4]], tt4_result)
Example #25
Source File: box_list_ops.py    From moveo_ros with MIT License 6 votes vote down vote up 
def pad_or_clip_box_list(boxlist, num_boxes, scope=None):
  """Pads or clips all fields of a BoxList.

  Args:
    boxlist: A BoxList with arbitrary of number of boxes.
    num_boxes: First num_boxes in boxlist are kept.
      The fields are zero-padded if num_boxes is bigger than the
      actual number of boxes.
    scope: name scope.

  Returns:
    BoxList with all fields padded or clipped.
  """
  with tf.name_scope(scope, 'PadOrClipBoxList'):
    subboxlist = box_list.BoxList(shape_utils.pad_or_clip_tensor(
        boxlist.get(), num_boxes))
    for field in boxlist.get_extra_fields():
      subfield = shape_utils.pad_or_clip_tensor(
          boxlist.get_field(field), num_boxes)
      subboxlist.add_field(field, subfield)
    return subboxlist
Example #26
Source File: shape_utils_test.py    From moveo_ros with MIT License 6 votes vote down vote up 
def test_pad_or_clip_tensor_using_tensor_input(self):
    t1 = tf.constant([1], dtype=tf.int32)
    tt1 = shape_utils.pad_or_clip_tensor(t1, tf.constant(2))
    t2 = tf.constant([[0.1, 0.2]], dtype=tf.float32)
    tt2 = shape_utils.pad_or_clip_tensor(t2, tf.constant(2))

    t3 = tf.constant([1, 2, 3], dtype=tf.int32)
    tt3 = shape_utils.clip_tensor(t3, tf.constant(2))
    t4 = tf.constant([[0.1, 0.2], [0.2, 0.4], [0.5, 0.8]], dtype=tf.float32)
    tt4 = shape_utils.clip_tensor(t4, tf.constant(2))

    with self.test_session() as sess:
      tt1_result, tt2_result, tt3_result, tt4_result = sess.run(
          [tt1, tt2, tt3, tt4])
      self.assertAllEqual([1, 0], tt1_result)
      self.assertAllClose([[0.1, 0.2], [0, 0]], tt2_result)
      self.assertAllEqual([1, 2], tt3_result)
      self.assertAllClose([[0.1, 0.2], [0.2, 0.4]], tt4_result)
Example #27
Source File: shape_utils_test.py    From moveo_ros with MIT License 6 votes vote down vote up 
def test_pad_or_clip_tensor_using_integer_input(self):
    t1 = tf.constant([1], dtype=tf.int32)
    tt1 = shape_utils.pad_or_clip_tensor(t1, 2)
    t2 = tf.constant([[0.1, 0.2]], dtype=tf.float32)
    tt2 = shape_utils.pad_or_clip_tensor(t2, 2)

    t3 = tf.constant([1, 2, 3], dtype=tf.int32)
    tt3 = shape_utils.clip_tensor(t3, 2)
    t4 = tf.constant([[0.1, 0.2], [0.2, 0.4], [0.5, 0.8]], dtype=tf.float32)
    tt4 = shape_utils.clip_tensor(t4, 2)

    self.assertEqual(2, tt1.get_shape()[0])
    self.assertEqual(2, tt2.get_shape()[0])
    self.assertEqual(2, tt3.get_shape()[0])
    self.assertEqual(2, tt4.get_shape()[0])

    with self.test_session() as sess:
      tt1_result, tt2_result, tt3_result, tt4_result = sess.run(
          [tt1, tt2, tt3, tt4])
      self.assertAllEqual([1, 0], tt1_result)
      self.assertAllClose([[0.1, 0.2], [0, 0]], tt2_result)
      self.assertAllEqual([1, 2], tt3_result)
      self.assertAllClose([[0.1, 0.2], [0.2, 0.4]], tt4_result)
Example #28
Source File: box_list_ops.py    From BMW-TensorFlow-Training-GUI with Apache License 2.0 6 votes vote down vote up 
def pad_or_clip_box_list(boxlist, num_boxes, scope=None):
  """Pads or clips all fields of a BoxList.

  Args:
    boxlist: A BoxList with arbitrary of number of boxes.
    num_boxes: First num_boxes in boxlist are kept.
      The fields are zero-padded if num_boxes is bigger than the
      actual number of boxes.
    scope: name scope.

  Returns:
    BoxList with all fields padded or clipped.
  """
  with tf.name_scope(scope, 'PadOrClipBoxList'):
    subboxlist = box_list.BoxList(shape_utils.pad_or_clip_tensor(
        boxlist.get(), num_boxes))
    for field in boxlist.get_extra_fields():
      subfield = shape_utils.pad_or_clip_tensor(
          boxlist.get_field(field), num_boxes)
      subboxlist.add_field(field, subfield)
    return subboxlist
Example #29
Source File: shape_utils_test.py    From BMW-TensorFlow-Training-GUI with Apache License 2.0 6 votes vote down vote up 
def test_pad_or_clip_tensor_using_tensor_input(self):
    t1 = tf.constant([1], dtype=tf.int32)
    tt1 = shape_utils.pad_or_clip_tensor(t1, tf.constant(2))
    t2 = tf.constant([[0.1, 0.2]], dtype=tf.float32)
    tt2 = shape_utils.pad_or_clip_tensor(t2, tf.constant(2))

    t3 = tf.constant([1, 2, 3], dtype=tf.int32)
    tt3 = shape_utils.clip_tensor(t3, tf.constant(2))
    t4 = tf.constant([[0.1, 0.2], [0.2, 0.4], [0.5, 0.8]], dtype=tf.float32)
    tt4 = shape_utils.clip_tensor(t4, tf.constant(2))

    with self.test_session() as sess:
      tt1_result, tt2_result, tt3_result, tt4_result = sess.run(
          [tt1, tt2, tt3, tt4])
      self.assertAllEqual([1, 0], tt1_result)
      self.assertAllClose([[0.1, 0.2], [0, 0]], tt2_result)
      self.assertAllEqual([1, 2], tt3_result)
      self.assertAllClose([[0.1, 0.2], [0.2, 0.4]], tt4_result)
Example #30
Source File: shape_utils_test.py    From BMW-TensorFlow-Training-GUI with Apache License 2.0 6 votes vote down vote up 
def test_pad_or_clip_tensor_using_integer_input(self):
    t1 = tf.constant([1], dtype=tf.int32)
    tt1 = shape_utils.pad_or_clip_tensor(t1, 2)
    t2 = tf.constant([[0.1, 0.2]], dtype=tf.float32)
    tt2 = shape_utils.pad_or_clip_tensor(t2, 2)

    t3 = tf.constant([1, 2, 3], dtype=tf.int32)
    tt3 = shape_utils.clip_tensor(t3, 2)
    t4 = tf.constant([[0.1, 0.2], [0.2, 0.4], [0.5, 0.8]], dtype=tf.float32)
    tt4 = shape_utils.clip_tensor(t4, 2)

    self.assertEqual(2, tt1.get_shape()[0])
    self.assertEqual(2, tt2.get_shape()[0])
    self.assertEqual(2, tt3.get_shape()[0])
    self.assertEqual(2, tt4.get_shape()[0])

    with self.test_session() as sess:
      tt1_result, tt2_result, tt3_result, tt4_result = sess.run(
          [tt1, tt2, tt3, tt4])
      self.assertAllEqual([1, 0], tt1_result)
      self.assertAllClose([[0.1, 0.2], [0, 0]], tt2_result)
      self.assertAllEqual([1, 2], tt3_result)
      self.assertAllClose([[0.1, 0.2], [0.2, 0.4]], tt4_result)