|
|
|
import numpy as np |
|
from mmcv.transforms.base import BaseTransform |
|
from mmengine.registry import TRANSFORMS |
|
from mmengine.structures import InstanceData |
|
|
|
from mmdet3d.datasets import LyftDataset |
|
from mmdet3d.structures import Det3DDataSample, LiDARInstance3DBoxes |
|
|
|
|
|
def _generate_nus_dataset_config(): |
|
data_root = 'tests/data/lyft' |
|
ann_file = 'lyft_infos.pkl' |
|
classes = [ |
|
'car', 'truck', 'bus', 'emergency_vehicle', 'other_vehicle', |
|
'motorcycle', 'bicycle', 'pedestrian', 'animal' |
|
] |
|
if 'Identity' not in TRANSFORMS: |
|
|
|
@TRANSFORMS.register_module() |
|
class Identity(BaseTransform): |
|
|
|
def transform(self, info): |
|
packed_input = dict(data_samples=Det3DDataSample()) |
|
if 'ann_info' in info: |
|
packed_input[ |
|
'data_samples'].gt_instances_3d = InstanceData() |
|
packed_input[ |
|
'data_samples'].gt_instances_3d.labels_3d = info[ |
|
'ann_info']['gt_labels_3d'] |
|
return packed_input |
|
|
|
pipeline = [ |
|
dict(type='Identity'), |
|
] |
|
modality = dict(use_lidar=True, use_camera=False) |
|
data_prefix = dict(pts='lidar', img='', sweeps='sweeps/LIDAR_TOP') |
|
return data_root, ann_file, classes, data_prefix, pipeline, modality |
|
|
|
|
|
def test_getitem(): |
|
np.random.seed(0) |
|
data_root, ann_file, classes, data_prefix, pipeline, modality = \ |
|
_generate_nus_dataset_config() |
|
|
|
lyft_dataset = LyftDataset( |
|
data_root, |
|
ann_file, |
|
data_prefix=data_prefix, |
|
pipeline=pipeline, |
|
metainfo=dict(classes=classes), |
|
modality=modality) |
|
|
|
lyft_dataset.prepare_data(0) |
|
input_dict = lyft_dataset.get_data_info(0) |
|
|
|
assert data_prefix['pts'] in input_dict['lidar_points']['lidar_path'] |
|
assert data_root in input_dict['lidar_points']['lidar_path'] |
|
|
|
ann_info = lyft_dataset.parse_ann_info(input_dict) |
|
|
|
|
|
assert 'gt_labels_3d' in ann_info |
|
assert ann_info['gt_labels_3d'].dtype == np.int64 |
|
assert len(ann_info['gt_labels_3d']) == 3 |
|
|
|
assert 'gt_bboxes_3d' in ann_info |
|
assert isinstance(ann_info['gt_bboxes_3d'], LiDARInstance3DBoxes) |
|
|
|
assert len(lyft_dataset.metainfo['classes']) == 9 |
|
|
