def test_one_car(self):
cars_a, people_a, tensor = self.initialize()
expected = tensor.copy()
expected[1, 1, 1, 5] = 0.1
cars_a[0].append((1, 1, 1, 1, 1, 1))
out, cars_predicted, people_predicted, reconstruction_2D = frame_reconstruction(
tensor, cars_a, people_a)
np.testing.assert_array_equal(out, expected)
def test_one_person(self):
cars_a, people_a, tensor = self.initialize()
expected = tensor.copy()
expected[1, 1, 1, 4] = 0.1
people_a[0].append(np.ones((3, 2), dtype=np.int))
out, cars_predicted, people_predicted, reconstruction_2D = frame_reconstruction(
tensor, cars_a, people_a)
np.testing.assert_array_equal(out, expected)
def test_many_cars(self):
cars_a, people_a, tensor = self.initialize()
expected = tensor.copy()
indx = 0
for x in range(0, 3):
for y in range(0, 3):
cars_a[indx].append((0, 0, x, x, y, y))
indx += 1
expected[0, :, :, 5] = 0.1 * np.ones(expected.shape[1:3])
out, cars_predicted, people_predicted, reconstruction_2D = frame_reconstruction(
tensor, cars_a, people_a)
np.testing.assert_array_equal(out, expected)
def test_two_cars(self):
cars_a, people_a, tensor = self.initialize()
expected = tensor.copy()
cars_a[0].append((0, 0, 0, 0, 0, 0))
cars_a[0].append((0, 0, 0, 0, 2, 2))
cars_a[2].append((0, 0, 0, 0, 0, 1))
expected[0, 0, 0, 5] = 0.2
expected[0, 0, 1, 5] = 0.1
expected[0, 0, 2, 5] = 0.1
out, cars_predicted, people_predicted, reconstruction_2D = frame_reconstruction(
tensor, cars_a, people_a)
np.testing.assert_array_equal(out, expected)
def test_many_people(self):
cars_a, people_a, tensor = self.initialize()
expected = tensor.copy()
indx = 0
#vals=[[0,1],[0,2],[1,3],[2,3]]
for x in range(0, 3):
for y in range(0, 3):
people_a[indx].append(
np.array([[0, 0], [y, y], [x, x]], np.int32))
indx += 1
expected[0, :, :, 4] = 0.1 * np.ones(expected.shape[1:3])
out, cars_predicted, people_predicted, reconstruction_2D = frame_reconstruction(
tensor, cars_a, people_a)
np.testing.assert_array_equal(out, expected)
def test_empty(self):
cars_a, people_a, tensor = self.initialize()
out, cars_predicted, people_predicted, reconstruction_2D = frame_reconstruction(
tensor, cars_a, people_a)
np.testing.assert_array_equal(out, tensor)