def get_empty_anchor_filter_2d(anchors, voxel_grid_2d, density_threshold=1):
""" Returns a filter for empty anchors from the given 2D anchor list
Args:
anchors: list of 3d anchors in the format
N x [x, y, z, dim_x, dim_y, dim_z]
voxel_grid_2d: a VoxelGrid object containing a 2D voxel grid of
point cloud used to filter the anchors
density_threshold: minimum number of points in voxel to keep the anchor
Returns:
anchor filter: N Boolean mask
"""
format_checker.check_anchor_format(anchors)
# Remove y dimensions from anchors to project into BEV
anchors_2d = anchors[:, [0, 2, 3, 5]]
# Get Integral image of the voxel, add 1 since filled = 0, empty is -1
leaf_layout = voxel_grid_2d.leaf_layout_2d + 1
leaf_layout = np.squeeze(leaf_layout)
integral_image = IntegralImage2D(leaf_layout)
# Make anchor container
anchor_container = np.zeros([len(anchors_2d), 4]).astype(np.uint32)
num_anchors = len(anchors_2d)
# Set up objects containing corners of anchors
top_left_up = np.zeros([num_anchors, 2]).astype(np.float32)
bot_right_down = np.zeros([num_anchors, 2]).astype(np.float32)
# Calculate minimum corner
top_left_up[:, 0] = anchors_2d[:, 0] - (anchors_2d[:, 2] / 2.)
top_left_up[:, 1] = anchors_2d[:, 1] - (anchors_2d[:, 3] / 2.)
# Calculate maximum corner
bot_right_down[:, 0] = anchors_2d[:, 0] + (anchors_2d[:, 2] / 2.)
bot_right_down[:, 1] = anchors_2d[:, 1] + (anchors_2d[:, 3] / 2.)
# map_to_index() expects N x 2 points
anchor_container[:, :2] = voxel_grid_2d.map_to_index(
top_left_up)
anchor_container[:, 2:] = voxel_grid_2d.map_to_index(
bot_right_down)
# Transpose to pass into query()
anchor_container = anchor_container.T
# Get point density score for each anchor
point_density_score = integral_image.query(anchor_container)
# Create the filter
anchor_filter = point_density_score >= density_threshold
return anchor_filter
def test_integral_image_2d(self):
# Generate integral image
integral_image = IntegralImage2D(self.test_image)
boxes = np.array([[0, 0, 1, 1],
[0, 0, 2, 2],
[0, 0, 3, 3]]).T.astype(np.uint32)
occupancy_count = integral_image.query(boxes)
# First box case = should be 1*1*1 = 1
self.assertTrue(occupancy_count[0] == 1)
# Second box case = should be 2*2*2 = 8
self.assertTrue(occupancy_count[1] == 4)
# Third box case = should be 3*3*3 = 27
self.assertTrue(occupancy_count[2] == 9)
boxes = np.array([[1, 1, 2, 2],
[1, 1, 3, 3]]).T.astype(np.uint32)
occupancy_count = integral_image.query(boxes)
# First box case = should be 1*1 = 1
self.assertTrue(occupancy_count[0] == 1)
# Second box case = should be 2*2 = 4
self.assertTrue(occupancy_count[1] == 4)
boxes = np.array([[0, 0, 3, 1]]).T.astype(np.uint32)
occupancy_count = integral_image.query(boxes)
# Flat Surface case = should be 1*3 = 3
self.assertTrue(occupancy_count[0] == 3)
# Test outside the boundary
boxes = np.array([[0, 0, 2312, 162]]).T.astype(np.uint32)
occupancy_count = integral_image.query(boxes)
self.assertTrue(occupancy_count[0] == 9)