Python ops.meshgrid方法代码示例

# 需要导入模块: from object_detection.utils import ops [as 别名]
# 或者: from object_detection.utils.ops import meshgrid [as 别名]
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) 

# 需要导入模块: from object_detection.utils import ops [as 别名]
# 或者: from object_detection.utils.ops import meshgrid [as 别名]
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) 

# 需要导入模块: from object_detection.utils import ops [as 别名]
# 或者: from object_detection.utils.ops import meshgrid [as 别名]
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])