def test_find_lane_bases_hollow_lane():
a = BinaryImage(
np.array([[0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0], [1, 0, 1, 0, 1, 0, 1],
[1, 0, 1, 0, 1, 0, 1], [1, 0, 1, 0, 1, 0, 1]]))
(left_lane_base, right_lane_base) = a.lane_bases(midpoint_x=3)
assert left_lane_base == 1
assert right_lane_base == 5
def test_find_lane_bases_multiple_candidates():
a = BinaryImage(
np.array([[0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 0, 0, 1, 1],
[1, 1, 1, 0, 1, 1, 1], [1, 1, 1, 0, 1, 1, 1]]))
(left_lane_base, right_lane_base) = a.lane_bases(midpoint_x=3)
assert left_lane_base == 1
assert right_lane_base == 5
def test_xy_positions_in_window():
a = BinaryImage(
np.array([[0, 0, 0, 0, 0, 1, 0], [0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0], [1, 1, 0, 0, 0, 0, 0],
[1, 0, 0, 0, 0, 1, 0], [0, 0, 0, 0, 1, 0, 0]]))
window = Window(a, 5, (6, 3), 1)
(x, y) = window.nonzero_xy
assert np.array_equal(x, [5, 4])
assert np.array_equal(y, [4, 5])
def test_find_y_positions():
a = BinaryImage(np.zeros((90, 2), np.int8))
expected_y_positions = np.array([(90, 80), (80, 70), (70, 60), (60, 50),
(50, 40), (40, 30), (30, 20), (20, 10),
(10, 0)])
assert np.array_equal(a.window_y_positions(), expected_y_positions)
def test_combine_images_with_and():
a = BinaryImage(np.array([[1, 0], [1, 0]]))
b = BinaryImage(np.array([[1, 1], [0, 0]]))
assert (a & b) == BinaryImage(np.array([[1, 0], [0, 0]]))
def test_create_from_image_within_threshold():
image = np.array([[20, 10], [5, 25]])
a = BinaryImage.in_threshold(image, 8, 21)
assert a == BinaryImage(np.array([[1, 1], [0, 0]]))