Python object_detection.utils.ops.meshgrid() Examples

The following are 30 code examples of object_detection.utils.ops.meshgrid(). 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.ops , or try the search function .
Example #1
Source File: ops_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_meshgrid_numpy_comparison(self):
    """Tests meshgrid op with vectors, for which it should match numpy."""
    x = np.arange(4)
    y = np.arange(6)
    exp_xgrid, exp_ygrid = np.meshgrid(x, y)
    xgrid, ygrid = ops.meshgrid(x, y)
    with self.test_session() as sess:
      xgrid_output, ygrid_output = sess.run([xgrid, ygrid])
      self.assertAllEqual(xgrid_output, exp_xgrid)
      self.assertAllEqual(ygrid_output, exp_ygrid)
Example #2
Source File: ops_test.py    From hands-detection with MIT License 5 votes vote down vote up 
def test_meshgrid_multidimensional(self):
    np.random.seed(18)
    x = np.random.rand(4, 1, 2).astype(np.float32)
    y = np.random.rand(2, 3).astype(np.float32)

    xgrid, ygrid = ops.meshgrid(x, y)

    grid_shape = list(y.shape) + list(x.shape)
    self.assertEqual(xgrid.get_shape().as_list(), grid_shape)
    self.assertEqual(ygrid.get_shape().as_list(), grid_shape)
    with self.test_session() as sess:
      xgrid_output, ygrid_output = sess.run([xgrid, ygrid])

    # Check the shape of the output grids
    self.assertEqual(xgrid_output.shape, tuple(grid_shape))
    self.assertEqual(ygrid_output.shape, tuple(grid_shape))

    # Check a few elements
    test_elements = [((3, 0, 0), (1, 2)),
                     ((2, 0, 1), (0, 0)),
                     ((0, 0, 0), (1, 1))]
    for xind, yind in test_elements:
      # These are float equality tests, but the meshgrid op should not introduce
      # rounding.
      self.assertEqual(xgrid_output[yind + xind], x[xind])
      self.assertEqual(ygrid_output[yind + xind], y[yind])
Example #3
Source File: ops_test.py    From hands-detection with MIT License 5 votes vote down vote up 
def test_meshgrid_numpy_comparison(self):
    """Tests meshgrid op with vectors, for which it should match numpy."""
    x = np.arange(4)
    y = np.arange(6)
    exp_xgrid, exp_ygrid = np.meshgrid(x, y)
    xgrid, ygrid = ops.meshgrid(x, y)
    with self.test_session() as sess:
      xgrid_output, ygrid_output = sess.run([xgrid, ygrid])
      self.assertAllEqual(xgrid_output, exp_xgrid)
      self.assertAllEqual(ygrid_output, exp_ygrid)
Example #4
Source File: grid_anchor_generator.py    From tensorflow with BSD 2-Clause "Simplified" License 5 votes vote down vote up 
def _generate(self, feature_map_shape_list):
    """Generates a collection of bounding boxes to be used as anchors.

    Args:
      feature_map_shape_list: list of pairs of convnet layer resolutions in the
        format [(height_0, width_0)].  For example, setting
        feature_map_shape_list=[(8, 8)] asks for anchors that correspond
        to an 8x8 layer.  For this anchor generator, only lists of length 1 are
        allowed.

    Returns:
      boxes: a BoxList holding a collection of N anchor boxes
    Raises:
      ValueError: if feature_map_shape_list, box_specs_list do not have the same
        length.
      ValueError: if feature_map_shape_list does not consist of pairs of
        integers
    """
    if not (isinstance(feature_map_shape_list, list)
            and len(feature_map_shape_list) == 1):
      raise ValueError('feature_map_shape_list must be a list of length 1.')
    if not all([isinstance(list_item, tuple) and len(list_item) == 2
                for list_item in feature_map_shape_list]):
      raise ValueError('feature_map_shape_list must be a list of pairs.')
    grid_height, grid_width = feature_map_shape_list[0]
    scales_grid, aspect_ratios_grid = ops.meshgrid(self._scales,
                                                   self._aspect_ratios)
    scales_grid = tf.reshape(scales_grid, [-1])
    aspect_ratios_grid = tf.reshape(aspect_ratios_grid, [-1])
    return tile_anchors(grid_height,
                        grid_width,
                        scales_grid,
                        aspect_ratios_grid,
                        self._base_anchor_size,
                        self._anchor_stride,
                        self._anchor_offset)
Example #5
Source File: ops_test.py    From moveo_ros with MIT License 5 votes vote down vote up 
def test_meshgrid_multidimensional(self):
    np.random.seed(18)
    x = np.random.rand(4, 1, 2).astype(np.float32)
    y = np.random.rand(2, 3).astype(np.float32)

    xgrid, ygrid = ops.meshgrid(x, y)

    grid_shape = list(y.shape) + list(x.shape)
    self.assertEqual(xgrid.get_shape().as_list(), grid_shape)
    self.assertEqual(ygrid.get_shape().as_list(), grid_shape)
    with self.test_session() as sess:
      xgrid_output, ygrid_output = sess.run([xgrid, ygrid])

    # Check the shape of the output grids
    self.assertEqual(xgrid_output.shape, tuple(grid_shape))
    self.assertEqual(ygrid_output.shape, tuple(grid_shape))

    # Check a few elements
    test_elements = [((3, 0, 0), (1, 2)),
                     ((2, 0, 1), (0, 0)),
                     ((0, 0, 0), (1, 1))]
    for xind, yind in test_elements:
      # These are float equality tests, but the meshgrid op should not introduce
      # rounding.
      self.assertEqual(xgrid_output[yind + xind], x[xind])
      self.assertEqual(ygrid_output[yind + xind], y[yind])
Example #6
Source File: ops_test.py    From moveo_ros with MIT License 5 votes vote down vote up 
def test_meshgrid_numpy_comparison(self):
    """Tests meshgrid op with vectors, for which it should match numpy."""
    x = np.arange(4)
    y = np.arange(6)
    exp_xgrid, exp_ygrid = np.meshgrid(x, y)
    xgrid, ygrid = ops.meshgrid(x, y)
    with self.test_session() as sess:
      xgrid_output, ygrid_output = sess.run([xgrid, ygrid])
      self.assertAllEqual(xgrid_output, exp_xgrid)
      self.assertAllEqual(ygrid_output, exp_ygrid)
Example #7
Source File: grid_anchor_generator.py    From moveo_ros with MIT License 5 votes vote down vote up 
def _generate(self, feature_map_shape_list):
    """Generates a collection of bounding boxes to be used as anchors.

    Args:
      feature_map_shape_list: list of pairs of convnet layer resolutions in the
        format [(height_0, width_0)].  For example, setting
        feature_map_shape_list=[(8, 8)] asks for anchors that correspond
        to an 8x8 layer.  For this anchor generator, only lists of length 1 are
        allowed.

    Returns:
      boxes: a BoxList holding a collection of N anchor boxes
    Raises:
      ValueError: if feature_map_shape_list, box_specs_list do not have the same
        length.
      ValueError: if feature_map_shape_list does not consist of pairs of
        integers
    """
    if not (isinstance(feature_map_shape_list, list)
            and len(feature_map_shape_list) == 1):
      raise ValueError('feature_map_shape_list must be a list of length 1.')
    if not all([isinstance(list_item, tuple) and len(list_item) == 2
                for list_item in feature_map_shape_list]):
      raise ValueError('feature_map_shape_list must be a list of pairs.')
    grid_height, grid_width = feature_map_shape_list[0]
    scales_grid, aspect_ratios_grid = ops.meshgrid(self._scales,
                                                   self._aspect_ratios)
    scales_grid = tf.reshape(scales_grid, [-1])
    aspect_ratios_grid = tf.reshape(aspect_ratios_grid, [-1])
    return tile_anchors(grid_height,
                        grid_width,
                        scales_grid,
                        aspect_ratios_grid,
                        self._base_anchor_size,
                        self._anchor_stride,
                        self._anchor_offset)
Example #8
Source File: grid_anchor_generator.py    From hands-detection with MIT License 5 votes vote down vote up 
def _generate(self, feature_map_shape_list):
    """Generates a collection of bounding boxes to be used as anchors.

    Args:
      feature_map_shape_list: list of pairs of convnet layer resolutions in the
        format [(height_0, width_0)].  For example, setting
        feature_map_shape_list=[(8, 8)] asks for anchors that correspond
        to an 8x8 layer.  For this anchor generator, only lists of length 1 are
        allowed.

    Returns:
      boxes: a BoxList holding a collection of N anchor boxes
    Raises:
      ValueError: if feature_map_shape_list, box_specs_list do not have the same
        length.
      ValueError: if feature_map_shape_list does not consist of pairs of
        integers
    """
    if not (isinstance(feature_map_shape_list, list)
            and len(feature_map_shape_list) == 1):
      raise ValueError('feature_map_shape_list must be a list of length 1.')
    if not all([isinstance(list_item, tuple) and len(list_item) == 2
                for list_item in feature_map_shape_list]):
      raise ValueError('feature_map_shape_list must be a list of pairs.')
    grid_height, grid_width = feature_map_shape_list[0]
    scales_grid, aspect_ratios_grid = ops.meshgrid(self._scales,
                                                   self._aspect_ratios)
    scales_grid = tf.reshape(scales_grid, [-1])
    aspect_ratios_grid = tf.reshape(aspect_ratios_grid, [-1])
    return tile_anchors(grid_height,
                        grid_width,
                        scales_grid,
                        aspect_ratios_grid,
                        self._base_anchor_size,
                        self._anchor_stride,
                        self._anchor_offset)
Example #9
Source File: grid_anchor_generator.py    From object_detection_kitti with Apache License 2.0 5 votes vote down vote up 
def _generate(self, feature_map_shape_list):
    """Generates a collection of bounding boxes to be used as anchors.

    Args:
      feature_map_shape_list: list of pairs of convnet layer resolutions in the
        format [(height_0, width_0)].  For example, setting
        feature_map_shape_list=[(8, 8)] asks for anchors that correspond
        to an 8x8 layer.  For this anchor generator, only lists of length 1 are
        allowed.

    Returns:
      boxes: a BoxList holding a collection of N anchor boxes
    Raises:
      ValueError: if feature_map_shape_list, box_specs_list do not have the same
        length.
      ValueError: if feature_map_shape_list does not consist of pairs of
        integers
    """
    if not (isinstance(feature_map_shape_list, list)
            and len(feature_map_shape_list) == 1):
      raise ValueError('feature_map_shape_list must be a list of length 1.')
    if not all([isinstance(list_item, tuple) and len(list_item) == 2
                for list_item in feature_map_shape_list]):
      raise ValueError('feature_map_shape_list must be a list of pairs.')
    grid_height, grid_width = feature_map_shape_list[0]
    scales_grid, aspect_ratios_grid = ops.meshgrid(self._scales,
                                                   self._aspect_ratios)
    scales_grid = tf.reshape(scales_grid, [-1])
    aspect_ratios_grid = tf.reshape(aspect_ratios_grid, [-1])
    return tile_anchors(grid_height,
                        grid_width,
                        scales_grid,
                        aspect_ratios_grid,
                        self._base_anchor_size,
                        self._anchor_stride,
                        self._anchor_offset)
Example #10
Source File: ops_test.py    From object_detection_kitti with Apache License 2.0 5 votes vote down vote up 
def test_meshgrid_numpy_comparison(self):
    """Tests meshgrid op with vectors, for which it should match numpy."""
    x = np.arange(4)
    y = np.arange(6)
    exp_xgrid, exp_ygrid = np.meshgrid(x, y)
    xgrid, ygrid = ops.meshgrid(x, y)
    with self.test_session() as sess:
      xgrid_output, ygrid_output = sess.run([xgrid, ygrid])
      self.assertAllEqual(xgrid_output, exp_xgrid)
      self.assertAllEqual(ygrid_output, exp_ygrid)
Example #11
Source File: ops_test.py    From object_detection_kitti with Apache License 2.0 5 votes vote down vote up 
def test_meshgrid_multidimensional(self):
    np.random.seed(18)
    x = np.random.rand(4, 1, 2).astype(np.float32)
    y = np.random.rand(2, 3).astype(np.float32)

    xgrid, ygrid = ops.meshgrid(x, y)

    grid_shape = list(y.shape) + list(x.shape)
    self.assertEqual(xgrid.get_shape().as_list(), grid_shape)
    self.assertEqual(ygrid.get_shape().as_list(), grid_shape)
    with self.test_session() as sess:
      xgrid_output, ygrid_output = sess.run([xgrid, ygrid])

    # Check the shape of the output grids
    self.assertEqual(xgrid_output.shape, tuple(grid_shape))
    self.assertEqual(ygrid_output.shape, tuple(grid_shape))

    # Check a few elements
    test_elements = [((3, 0, 0), (1, 2)),
                     ((2, 0, 1), (0, 0)),
                     ((0, 0, 0), (1, 1))]
    for xind, yind in test_elements:
      # These are float equality tests, but the meshgrid op should not introduce
      # rounding.
      self.assertEqual(xgrid_output[yind + xind], x[xind])
      self.assertEqual(ygrid_output[yind + xind], y[yind])
Example #12
Source File: grid_anchor_generator.py    From MBMD with MIT License 5 votes vote down vote up 
def _generate(self, feature_map_shape_list):
    """Generates a collection of bounding boxes to be used as anchors.

    Args:
      feature_map_shape_list: list of pairs of convnet layer resolutions in the
        format [(height_0, width_0)].  For example, setting
        feature_map_shape_list=[(8, 8)] asks for anchors that correspond
        to an 8x8 layer.  For this anchor generator, only lists of length 1 are
        allowed.

    Returns:
      boxes: a BoxList holding a collection of N anchor boxes
    Raises:
      ValueError: if feature_map_shape_list, box_specs_list do not have the same
        length.
      ValueError: if feature_map_shape_list does not consist of pairs of
        integers
    """
    if not (isinstance(feature_map_shape_list, list)
            and len(feature_map_shape_list) == 1):
      raise ValueError('feature_map_shape_list must be a list of length 1.')
    if not all([isinstance(list_item, tuple) and len(list_item) == 2
                for list_item in feature_map_shape_list]):
      raise ValueError('feature_map_shape_list must be a list of pairs.')
    grid_height, grid_width = feature_map_shape_list[0]
    scales_grid, aspect_ratios_grid = ops.meshgrid(self._scales,
                                                   self._aspect_ratios)
    scales_grid = tf.reshape(scales_grid, [-1])
    aspect_ratios_grid = tf.reshape(aspect_ratios_grid, [-1])
    return tile_anchors(grid_height,
                        grid_width,
                        scales_grid,
                        aspect_ratios_grid,
                        self._base_anchor_size,
                        self._anchor_stride,
                        self._anchor_offset)
Example #13
Source File: ops_test.py    From MBMD with MIT License 5 votes vote down vote up 
def test_meshgrid_numpy_comparison(self):
    """Tests meshgrid op with vectors, for which it should match numpy."""
    x = np.arange(4)
    y = np.arange(6)
    exp_xgrid, exp_ygrid = np.meshgrid(x, y)
    xgrid, ygrid = ops.meshgrid(x, y)
    with self.test_session() as sess:
      xgrid_output, ygrid_output = sess.run([xgrid, ygrid])
      self.assertAllEqual(xgrid_output, exp_xgrid)
      self.assertAllEqual(ygrid_output, exp_ygrid)
Example #14
Source File: ops_test.py    From MBMD with MIT License 5 votes vote down vote up 
def test_meshgrid_multidimensional(self):
    np.random.seed(18)
    x = np.random.rand(4, 1, 2).astype(np.float32)
    y = np.random.rand(2, 3).astype(np.float32)

    xgrid, ygrid = ops.meshgrid(x, y)

    grid_shape = list(y.shape) + list(x.shape)
    self.assertEqual(xgrid.get_shape().as_list(), grid_shape)
    self.assertEqual(ygrid.get_shape().as_list(), grid_shape)
    with self.test_session() as sess:
      xgrid_output, ygrid_output = sess.run([xgrid, ygrid])

    # Check the shape of the output grids
    self.assertEqual(xgrid_output.shape, tuple(grid_shape))
    self.assertEqual(ygrid_output.shape, tuple(grid_shape))

    # Check a few elements
    test_elements = [((3, 0, 0), (1, 2)),
                     ((2, 0, 1), (0, 0)),
                     ((0, 0, 0), (1, 1))]
    for xind, yind in test_elements:
      # These are float equality tests, but the meshgrid op should not introduce
      # rounding.
      self.assertEqual(xgrid_output[yind + xind], x[xind])
      self.assertEqual(ygrid_output[yind + xind], y[yind])
Example #15
Source File: ops_test.py    From Elphas with Apache License 2.0 5 votes vote down vote up 
def test_meshgrid_numpy_comparison(self):
    """Tests meshgrid op with vectors, for which it should match numpy."""
    x = np.arange(4)
    y = np.arange(6)
    exp_xgrid, exp_ygrid = np.meshgrid(x, y)
    xgrid, ygrid = ops.meshgrid(x, y)
    with self.test_session() as sess:
      xgrid_output, ygrid_output = sess.run([xgrid, ygrid])
      self.assertAllEqual(xgrid_output, exp_xgrid)
      self.assertAllEqual(ygrid_output, exp_ygrid)
Example #16
Source File: ops_test.py    From BMW-TensorFlow-Training-GUI with Apache License 2.0 5 votes vote down vote up 
def test_meshgrid_multidimensional(self):
    np.random.seed(18)
    x = np.random.rand(4, 1, 2).astype(np.float32)
    y = np.random.rand(2, 3).astype(np.float32)

    xgrid, ygrid = ops.meshgrid(x, y)

    grid_shape = list(y.shape) + list(x.shape)
    self.assertEqual(xgrid.get_shape().as_list(), grid_shape)
    self.assertEqual(ygrid.get_shape().as_list(), grid_shape)
    with self.test_session() as sess:
      xgrid_output, ygrid_output = sess.run([xgrid, ygrid])

    # Check the shape of the output grids
    self.assertEqual(xgrid_output.shape, tuple(grid_shape))
    self.assertEqual(ygrid_output.shape, tuple(grid_shape))

    # Check a few elements
    test_elements = [((3, 0, 0), (1, 2)),
                     ((2, 0, 1), (0, 0)),
                     ((0, 0, 0), (1, 1))]
    for xind, yind in test_elements:
      # These are float equality tests, but the meshgrid op should not introduce
      # rounding.
      self.assertEqual(xgrid_output[yind + xind], x[xind])
      self.assertEqual(ygrid_output[yind + xind], y[yind])
Example #17
Source File: ops_test.py    From BMW-TensorFlow-Training-GUI with Apache License 2.0 5 votes vote down vote up 
def test_meshgrid_numpy_comparison(self):
    """Tests meshgrid op with vectors, for which it should match numpy."""
    x = np.arange(4)
    y = np.arange(6)
    exp_xgrid, exp_ygrid = np.meshgrid(x, y)
    xgrid, ygrid = ops.meshgrid(x, y)
    with self.test_session() as sess:
      xgrid_output, ygrid_output = sess.run([xgrid, ygrid])
      self.assertAllEqual(xgrid_output, exp_xgrid)
      self.assertAllEqual(ygrid_output, exp_ygrid)
Example #18
Source File: ops_test.py    From ros_tensorflow with Apache License 2.0 5 votes vote down vote up 
def test_meshgrid_multidimensional(self):
    np.random.seed(18)
    x = np.random.rand(4, 1, 2).astype(np.float32)
    y = np.random.rand(2, 3).astype(np.float32)

    xgrid, ygrid = ops.meshgrid(x, y)

    grid_shape = list(y.shape) + list(x.shape)
    self.assertEqual(xgrid.get_shape().as_list(), grid_shape)
    self.assertEqual(ygrid.get_shape().as_list(), grid_shape)
    with self.test_session() as sess:
      xgrid_output, ygrid_output = sess.run([xgrid, ygrid])

    # Check the shape of the output grids
    self.assertEqual(xgrid_output.shape, tuple(grid_shape))
    self.assertEqual(ygrid_output.shape, tuple(grid_shape))

    # Check a few elements
    test_elements = [((3, 0, 0), (1, 2)),
                     ((2, 0, 1), (0, 0)),
                     ((0, 0, 0), (1, 1))]
    for xind, yind in test_elements:
      # These are float equality tests, but the meshgrid op should not introduce
      # rounding.
      self.assertEqual(xgrid_output[yind + xind], x[xind])
      self.assertEqual(ygrid_output[yind + xind], y[yind])
Example #19
Source File: ops_test.py    From ros_tensorflow with Apache License 2.0 5 votes vote down vote up 
def test_meshgrid_numpy_comparison(self):
    """Tests meshgrid op with vectors, for which it should match numpy."""
    x = np.arange(4)
    y = np.arange(6)
    exp_xgrid, exp_ygrid = np.meshgrid(x, y)
    xgrid, ygrid = ops.meshgrid(x, y)
    with self.test_session() as sess:
      xgrid_output, ygrid_output = sess.run([xgrid, ygrid])
      self.assertAllEqual(xgrid_output, exp_xgrid)
      self.assertAllEqual(ygrid_output, exp_ygrid)
Example #20
Source File: ops_test.py    From Gun-Detector with Apache License 2.0 5 votes vote down vote up 
def test_meshgrid_multidimensional(self):
    np.random.seed(18)
    x = np.random.rand(4, 1, 2).astype(np.float32)
    y = np.random.rand(2, 3).astype(np.float32)

    xgrid, ygrid = ops.meshgrid(x, y)

    grid_shape = list(y.shape) + list(x.shape)
    self.assertEqual(xgrid.get_shape().as_list(), grid_shape)
    self.assertEqual(ygrid.get_shape().as_list(), grid_shape)
    with self.test_session() as sess:
      xgrid_output, ygrid_output = sess.run([xgrid, ygrid])

    # Check the shape of the output grids
    self.assertEqual(xgrid_output.shape, tuple(grid_shape))
    self.assertEqual(ygrid_output.shape, tuple(grid_shape))

    # Check a few elements
    test_elements = [((3, 0, 0), (1, 2)),
                     ((2, 0, 1), (0, 0)),
                     ((0, 0, 0), (1, 1))]
    for xind, yind in test_elements:
      # These are float equality tests, but the meshgrid op should not introduce
      # rounding.
      self.assertEqual(xgrid_output[yind + xind], x[xind])
      self.assertEqual(ygrid_output[yind + xind], y[yind])
Example #21
Source File: ops_test.py    From Gun-Detector with Apache License 2.0 5 votes vote down vote up 
def test_meshgrid_numpy_comparison(self):
    """Tests meshgrid op with vectors, for which it should match numpy."""
    x = np.arange(4)
    y = np.arange(6)
    exp_xgrid, exp_ygrid = np.meshgrid(x, y)
    xgrid, ygrid = ops.meshgrid(x, y)
    with self.test_session() as sess:
      xgrid_output, ygrid_output = sess.run([xgrid, ygrid])
      self.assertAllEqual(xgrid_output, exp_xgrid)
      self.assertAllEqual(ygrid_output, exp_ygrid)
Example #22
Source File: ops_test.py    From tensorflow with BSD 2-Clause "Simplified" License 5 votes vote down vote up 
def test_meshgrid_multidimensional(self):
    np.random.seed(18)
    x = np.random.rand(4, 1, 2).astype(np.float32)
    y = np.random.rand(2, 3).astype(np.float32)

    xgrid, ygrid = ops.meshgrid(x, y)

    grid_shape = list(y.shape) + list(x.shape)
    self.assertEqual(xgrid.get_shape().as_list(), grid_shape)
    self.assertEqual(ygrid.get_shape().as_list(), grid_shape)
    with self.test_session() as sess:
      xgrid_output, ygrid_output = sess.run([xgrid, ygrid])

    # Check the shape of the output grids
    self.assertEqual(xgrid_output.shape, tuple(grid_shape))
    self.assertEqual(ygrid_output.shape, tuple(grid_shape))

    # Check a few elements
    test_elements = [((3, 0, 0), (1, 2)),
                     ((2, 0, 1), (0, 0)),
                     ((0, 0, 0), (1, 1))]
    for xind, yind in test_elements:
      # These are float equality tests, but the meshgrid op should not introduce
      # rounding.
      self.assertEqual(xgrid_output[yind + xind], x[xind])
      self.assertEqual(ygrid_output[yind + xind], y[yind])
Example #23
Source File: ops_test.py    From tensorflow with BSD 2-Clause "Simplified" License 5 votes vote down vote up 
def test_meshgrid_numpy_comparison(self):
    """Tests meshgrid op with vectors, for which it should match numpy."""
    x = np.arange(4)
    y = np.arange(6)
    exp_xgrid, exp_ygrid = np.meshgrid(x, y)
    xgrid, ygrid = ops.meshgrid(x, y)
    with self.test_session() as sess:
      xgrid_output, ygrid_output = sess.run([xgrid, ygrid])
      self.assertAllEqual(xgrid_output, exp_xgrid)
      self.assertAllEqual(ygrid_output, exp_ygrid)
Example #24
Source File: grid_anchor_generator.py    From DOTA_models with Apache License 2.0 5 votes vote down vote up 
def _generate(self, feature_map_shape_list):
    """Generates a collection of bounding boxes to be used as anchors.

    Args:
      feature_map_shape_list: list of pairs of convnet layer resolutions in the
        format [(height_0, width_0)].  For example, setting
        feature_map_shape_list=[(8, 8)] asks for anchors that correspond
        to an 8x8 layer.  For this anchor generator, only lists of length 1 are
        allowed.

    Returns:
      boxes: a BoxList holding a collection of N anchor boxes
    Raises:
      ValueError: if feature_map_shape_list, box_specs_list do not have the same
        length.
      ValueError: if feature_map_shape_list does not consist of pairs of
        integers
    """
    if not (isinstance(feature_map_shape_list, list)
            and len(feature_map_shape_list) == 1):
      raise ValueError('feature_map_shape_list must be a list of length 1.')
    if not all([isinstance(list_item, tuple) and len(list_item) == 2
                for list_item in feature_map_shape_list]):
      raise ValueError('feature_map_shape_list must be a list of pairs.')
    grid_height, grid_width = feature_map_shape_list[0]
    scales_grid, aspect_ratios_grid = ops.meshgrid(self._scales,
                                                   self._aspect_ratios)
    scales_grid = tf.reshape(scales_grid, [-1])
    aspect_ratios_grid = tf.reshape(aspect_ratios_grid, [-1])
    return tile_anchors(grid_height,
                        grid_width,
                        scales_grid,
                        aspect_ratios_grid,
                        self._base_anchor_size,
                        self._anchor_stride,
                        self._anchor_offset)
Example #25
Source File: ops_test.py    From Hands-On-Machine-Learning-with-OpenCV-4 with MIT License 5 votes vote down vote up 
def test_meshgrid_multidimensional(self):
    np.random.seed(18)
    x = np.random.rand(4, 1, 2).astype(np.float32)
    y = np.random.rand(2, 3).astype(np.float32)

    xgrid, ygrid = ops.meshgrid(x, y)

    grid_shape = list(y.shape) + list(x.shape)
    self.assertEqual(xgrid.get_shape().as_list(), grid_shape)
    self.assertEqual(ygrid.get_shape().as_list(), grid_shape)
    with self.test_session() as sess:
      xgrid_output, ygrid_output = sess.run([xgrid, ygrid])

    # Check the shape of the output grids
    self.assertEqual(xgrid_output.shape, tuple(grid_shape))
    self.assertEqual(ygrid_output.shape, tuple(grid_shape))

    # Check a few elements
    test_elements = [((3, 0, 0), (1, 2)),
                     ((2, 0, 1), (0, 0)),
                     ((0, 0, 0), (1, 1))]
    for xind, yind in test_elements:
      # These are float equality tests, but the meshgrid op should not introduce
      # rounding.
      self.assertEqual(xgrid_output[yind + xind], x[xind])
      self.assertEqual(ygrid_output[yind + xind], y[yind])
Example #26
Source File: ops_test.py    From Hands-On-Machine-Learning-with-OpenCV-4 with MIT License 5 votes vote down vote up 
def test_meshgrid_numpy_comparison(self):
    """Tests meshgrid op with vectors, for which it should match numpy."""
    x = np.arange(4)
    y = np.arange(6)
    exp_xgrid, exp_ygrid = np.meshgrid(x, y)
    xgrid, ygrid = ops.meshgrid(x, y)
    with self.test_session() as sess:
      xgrid_output, ygrid_output = sess.run([xgrid, ygrid])
      self.assertAllEqual(xgrid_output, exp_xgrid)
      self.assertAllEqual(ygrid_output, exp_ygrid)
Example #27
Source File: grid_anchor_generator.py    From Hands-On-Machine-Learning-with-OpenCV-4 with MIT License 5 votes vote down vote up 
def _generate(self, feature_map_shape_list):
    """Generates a collection of bounding boxes to be used as anchors.

    Args:
      feature_map_shape_list: list of pairs of convnet layer resolutions in the
        format [(height_0, width_0)].  For example, setting
        feature_map_shape_list=[(8, 8)] asks for anchors that correspond
        to an 8x8 layer.  For this anchor generator, only lists of length 1 are
        allowed.

    Returns:
      boxes: a BoxList holding a collection of N anchor boxes
    Raises:
      ValueError: if feature_map_shape_list, box_specs_list do not have the same
        length.
      ValueError: if feature_map_shape_list does not consist of pairs of
        integers
    """
    if not (isinstance(feature_map_shape_list, list)
            and len(feature_map_shape_list) == 1):
      raise ValueError('feature_map_shape_list must be a list of length 1.')
    if not all([isinstance(list_item, tuple) and len(list_item) == 2
                for list_item in feature_map_shape_list]):
      raise ValueError('feature_map_shape_list must be a list of pairs.')
    grid_height, grid_width = feature_map_shape_list[0]
    scales_grid, aspect_ratios_grid = ops.meshgrid(self._scales,
                                                   self._aspect_ratios)
    scales_grid = tf.reshape(scales_grid, [-1])
    aspect_ratios_grid = tf.reshape(aspect_ratios_grid, [-1])
    return tile_anchors(grid_height,
                        grid_width,
                        scales_grid,
                        aspect_ratios_grid,
                        self._base_anchor_size,
                        self._anchor_stride,
                        self._anchor_offset)
Example #28
Source File: ops_test.py    From Traffic-Rule-Violation-Detection-System with MIT License 5 votes vote down vote up 
def test_meshgrid_multidimensional(self):
    np.random.seed(18)
    x = np.random.rand(4, 1, 2).astype(np.float32)
    y = np.random.rand(2, 3).astype(np.float32)

    xgrid, ygrid = ops.meshgrid(x, y)

    grid_shape = list(y.shape) + list(x.shape)
    self.assertEqual(xgrid.get_shape().as_list(), grid_shape)
    self.assertEqual(ygrid.get_shape().as_list(), grid_shape)
    with self.test_session() as sess:
      xgrid_output, ygrid_output = sess.run([xgrid, ygrid])

    # Check the shape of the output grids
    self.assertEqual(xgrid_output.shape, tuple(grid_shape))
    self.assertEqual(ygrid_output.shape, tuple(grid_shape))

    # Check a few elements
    test_elements = [((3, 0, 0), (1, 2)),
                     ((2, 0, 1), (0, 0)),
                     ((0, 0, 0), (1, 1))]
    for xind, yind in test_elements:
      # These are float equality tests, but the meshgrid op should not introduce
      # rounding.
      self.assertEqual(xgrid_output[yind + xind], x[xind])
      self.assertEqual(ygrid_output[yind + xind], y[yind])
Example #29
Source File: ops_test.py    From Traffic-Rule-Violation-Detection-System with MIT License 5 votes vote down vote up 
def test_meshgrid_numpy_comparison(self):
    """Tests meshgrid op with vectors, for which it should match numpy."""
    x = np.arange(4)
    y = np.arange(6)
    exp_xgrid, exp_ygrid = np.meshgrid(x, y)
    xgrid, ygrid = ops.meshgrid(x, y)
    with self.test_session() as sess:
      xgrid_output, ygrid_output = sess.run([xgrid, ygrid])
      self.assertAllEqual(xgrid_output, exp_xgrid)
      self.assertAllEqual(ygrid_output, exp_ygrid)
Example #30
Source File: ops_test.py    From yolo_v2 with Apache License 2.0 5 votes vote down vote up 
def test_meshgrid_multidimensional(self):
    np.random.seed(18)
    x = np.random.rand(4, 1, 2).astype(np.float32)
    y = np.random.rand(2, 3).astype(np.float32)

    xgrid, ygrid = ops.meshgrid(x, y)

    grid_shape = list(y.shape) + list(x.shape)
    self.assertEqual(xgrid.get_shape().as_list(), grid_shape)
    self.assertEqual(ygrid.get_shape().as_list(), grid_shape)
    with self.test_session() as sess:
      xgrid_output, ygrid_output = sess.run([xgrid, ygrid])

    # Check the shape of the output grids
    self.assertEqual(xgrid_output.shape, tuple(grid_shape))
    self.assertEqual(ygrid_output.shape, tuple(grid_shape))

    # Check a few elements
    test_elements = [((3, 0, 0), (1, 2)),
                     ((2, 0, 1), (0, 0)),
                     ((0, 0, 0), (1, 1))]
    for xind, yind in test_elements:
      # These are float equality tests, but the meshgrid op should not introduce
      # rounding.
      self.assertEqual(xgrid_output[yind + xind], x[xind])
      self.assertEqual(ygrid_output[yind + xind], y[yind])