def test_raises_error_when_seconds_negative(self):
mock_samples = [{'token': '1', 'timestamp': 0, 'anns': ['1', '1b']}]
nusc = MockNuScenes(self.mock_annotations, mock_samples)
helper = PredictHelper(nusc)
with self.assertRaises(ValueError):
helper.get_future_for_agent('1', '1', -1, False)
with self.assertRaises(ValueError):
helper.get_past_for_agent('1', '1', -1, False)
with self.assertRaises(ValueError):
helper.get_past_for_sample('1', -1, False)
with self.assertRaises(ValueError):
helper.get_future_for_sample('1', -1, False)
def test_get_past_for_sample(self):
mock_samples = [{
'token': '5',
'timestamp': 0,
'anns': ['5', '5b']
}, {
'token': '4',
'timestamp': -1e6
}, {
'token': '3',
'timestamp': -2e6
}, {
'token': '2',
'timestamp': -3e6
}, {
'token': '1',
'timestamp': -4e6
}]
nusc = MockNuScenes(self.multiagent_mock_annotations, mock_samples)
helper = PredictHelper(nusc)
past = helper.get_past_for_sample('5', 3, True)
answer = {
'1': np.array([[-1, -1], [-2, -2], [-3, -3]]),
'2': np.array([[-1, -1], [-2, -2], [-3, -3]])
}
for k in answer:
np.testing.assert_equal(answer[k], answer[k])
def test_get_no_data_when_seconds_0(self):
mock_samples = [{'token': '1', 'timestamp': 0, 'anns': ['1']}]
nusc = MockNuScenes(self.mock_annotations, mock_samples)
helper = PredictHelper(nusc)
np.testing.assert_equal(
helper.get_future_for_agent('1', '1', 0, False), np.array([]))
np.testing.assert_equal(helper.get_past_for_agent('1', '1', 0, False),
np.array([]))
np.testing.assert_equal(helper.get_future_for_sample('1', 0, False),
np.array([]))
np.testing.assert_equal(helper.get_past_for_sample('1', 0, False),
np.array([]))
cv2.fillPoly(target_rep, pts=[np.int0(box)], color=1)
rotation_mat = get_rotation_matrix(target_rep.shape,
yaw + np.pi / 2)
target_rep = cv2.warpAffine(
target_rep, rotation_mat,
(target_rep.shape[1], target_rep.shape[0]))
row_crop, col_crop = get_crops(offset, offset, offset, offset,
res, target_rep.shape[0])
target_rep = target_rep[row_crop, col_crop]
#only get location where car is at
target_rep[target_rep != 1] = 0
target_rep = cv2.GaussianBlur(target_rep[:, :, 0], (5, 5), 0)
#get other vehicle representation
history = helper.get_past_for_sample(token,
0,
in_agent_frame=False,
just_xy=False)
history = reverse_history(history)
present_time = helper.get_annotations_for_sample(token)
history = add_present_time_to_history(present_time, history)
vehicle_rep = np.zeros((256, 256))
draw_other_vehicle_boxes(needed_ego_pose, (128, 128),
history,
vehicle_rep,
resolution=res)
vehicle_rep = cv2.warpAffine(vehicle_rep, rotation_mat,
vehicle_rep.shape)
row_crop, col_crop = get_crops(offset, offset, offset, offset,
res, target_rep.shape[0])
vehicle_rep = vehicle_rep[row_crop, col_crop]
