def setUpClass(cls):
cls.fake_kitti_dir = tests.test_path() + "/datasets/Kitti/object"
cls.dataset = generate_fake_dataset()
# create generic ground plane (normal vector is straight up)
cls.ground_plane = np.array([0., -1., 0., 0.])
cls.clusters = np.array([[1., 1., 1.], [2., 1., 1.]])
cls.anchor_generator = grid_anchor_3d_generator.GridAnchor3dGenerator()
def setUpClass(cls):
# Initialize the Kitti dataset
test_dir = tests.test_path()
# Get the unittest-kitti dataset
dataset_builder = DatasetBuilder()
cls.dataset = dataset_builder.build_kitti_dataset(
dataset_builder.KITTI_UNITTEST)
cls.log_dir = test_dir + '/logs'
cls.bev_vgg_cls = vgg.BevVggClassification()
def test_project_to_image_space_tensors(self):
anchors = np.asarray([[0, 0, 3, 2, 0, 6], [3, 0, 3, 2, 0, 2]],
dtype=np.float64)
img_idx = int('000217')
img_shape = [375, 1242]
dataset_config = DatasetBuilder.copy_config(
DatasetBuilder.KITTI_UNITTEST)
dataset_config.data_split = 'train'
dataset_config.dataset_dir = tests.test_path() + \
"/datasets/Kitti/object"
dataset = DatasetBuilder().build_kitti_dataset(dataset_config)
stereo_calib_p2 = calib_utils.read_calibration(dataset.calib_dir,
img_idx).p2
# Project the 3D points in numpy space
img_corners, img_corners_norm = anchor_projector.project_to_image_space(
anchors, stereo_calib_p2, img_shape)
# convert the required params to tensors
tf_stereo_calib_p2 = tf.convert_to_tensor(stereo_calib_p2,
dtype=tf.float32)
tf_anchors = tf.convert_to_tensor(anchors, dtype=tf.float32)
tf_img_shape = tf.convert_to_tensor(img_shape, dtype=tf.float32)
# Project the 3D points in tensor space
img_corners_tensor, img_corners_norm_tensor = \
anchor_projector.tf_project_to_image_space(tf_anchors,
tf_stereo_calib_p2,
tf_img_shape)
sess = tf.Session()
with sess.as_default():
img_corners_out = img_corners_tensor.eval()
img_corners_norm_out = img_corners_norm_tensor.eval()
np.testing.assert_allclose(img_corners,
img_corners_out,
atol=1e-04,
err_msg='Incorrect corner projection')
np.testing.assert_allclose(
img_corners_norm,
img_corners_norm_out,
atol=1e-04,
err_msg='Incorrect normalized corner projection')
def setUpClass(cls):
cls.fake_kitti_dir = tests.test_path() + "/datasets/Kitti/object"
def setUpClass(cls):
cls.fake_kitti_dir = tests.test_path() + "/datasets/Kitti/object"
cls.dataset = DatasetBuilder.build_kitti_dataset(
DatasetBuilder.KITTI_UNITTEST)