def calculate_2d_bbox(row, view_matrix, proj_matrix, width, height):
pos = np.array(row['pos'])
rot = np.array(row['rot'])
model_sizes = np.array(row['model_sizes'])
points_3dbbox = get_model_3dbbox(model_sizes)
# calculating model_coords_to_ndc, so we have both anc and viewed points
point_homo = np.array([
points_3dbbox[:, 0], points_3dbbox[:, 1], points_3dbbox[:, 2],
np.ones_like(points_3dbbox[:, 0])
])
model_matrix = construct_model_matrix(pos, rot)
point_homo = model_matrix @ point_homo
viewed = view_matrix @ point_homo
projected = proj_matrix @ viewed
projected /= projected[3, :]
bbox_3d = projected.T[:, 0:3]
bbox_2d_points = bbox_3d[:, 0:2]
is_3d_bbox_partially_outside = (bbox_2d_points <
-1).any() or (bbox_2d_points > 1).any()
bbox_2d_points = bbox_2d_points[((bbox_2d_points <= 1) &
(bbox_2d_points >= -1)).all(axis=1)]
if is_3d_bbox_partially_outside:
bbox_2d = model_coords_to_pixel(pos, rot, points_3dbbox, view_matrix,
proj_matrix, width, height).T
# now we need to compute intersections between end of image and points
# now we build 12 lines for 3d bounding box
lines = list()
lines.append([bbox_2d[0, :], bbox_2d[1, :]])
lines.append([bbox_2d[1, :], bbox_2d[3, :]])
lines.append([bbox_2d[3, :], bbox_2d[2, :]])
lines.append([bbox_2d[2, :], bbox_2d[0, :]])
lines.append([bbox_2d[4, :], bbox_2d[5, :]])
lines.append([bbox_2d[5, :], bbox_2d[7, :]])
lines.append([bbox_2d[7, :], bbox_2d[6, :]])
lines.append([bbox_2d[6, :], bbox_2d[4, :]])
lines.append([bbox_2d[4, :], bbox_2d[0, :]])
lines.append([bbox_2d[5, :], bbox_2d[1, :]])
lines.append([bbox_2d[6, :], bbox_2d[2, :]])
lines.append([bbox_2d[7, :], bbox_2d[3, :]])
borders = list()
borders.append([[0, 0], [0, height]])
borders.append([[0, height], [width, height]])
borders.append([[0, 0], [width, 0]])
borders.append([[width, 0], [width, height]])
for line in lines:
for border in borders:
if are_intersecting(line, border):
l1 = Line(Point(line[0][0], line[0][1]),
Point(line[1][0], line[1][1]))
l2 = Line(Point(border[0][0], border[0][1]),
Point(border[1][0], border[1][1]))
x, y = np.array(next(iter(l1.intersect(l2))),
dtype=np.float32)
ndc_y, ndc_x = pixel_to_ndc((y, x), (height, width))
bbox_2d_points = np.vstack((bbox_2d_points, [ndc_x,
ndc_y]))
bbox_2d = np.array([
[bbox_2d_points[:, 0].max(), -bbox_2d_points[:, 1].min()],
[bbox_2d_points[:, 0].min(), -bbox_2d_points[:, 1].max()],
])
# rescale from [-1, 1] to [0, 1]
bbox_2d = (bbox_2d / 2) + 0.5
return bbox_2d.tolist()
