refactor directory

mmdet3d/evaluation/functional/kitti_utils/__init__.py

+# Copyright (c) OpenMMLab. All rights reserved.
+from .eval import do_eval, eval_class, kitti_eval, kitti_eval_coco_style
+
+__all__ = ['kitti_eval', 'kitti_eval_coco_style', 'do_eval', 'eval_class']

mmdet3d/core/evaluation/waymo_utils/__init__.py → mmdet3d/evaluation/functional/waymo_utils/__init__.py

 # Copyright (c) OpenMMLab. All rights reserved.
+
 from .prediction_kitti_to_waymo import KITTI2Waymo
 
 __all__ = ['KITTI2Waymo']

mmdet3d/metrics/indoor_metric.py → mmdet3d/evaluation/metrics/indoor_metric.py

@@ -6,9 +6,10 @@ import numpy as np
 from mmengine.evaluator import BaseMetric
 from mmengine.logging import MMLogger
 
-from mmdet3d.core import get_box_type, indoor_eval
+from mmdet3d.evaluation import indoor_eval
 from mmdet3d.registry import METRICS
-from mmdet.core import eval_map
+from mmdet3d.structures import get_box_type
+from mmdet.evaluation import eval_map
 
 
 @METRICS.register_module()

mmdet3d/metrics/instance_seg_metric.py → mmdet3d/evaluation/metrics/instance_seg_metric.py

@@ -4,7 +4,7 @@ from typing import Dict, Optional, Sequence
 from mmengine.evaluator import BaseMetric
 from mmengine.logging import MMLogger
 
-from mmdet3d.core import instance_seg_eval
+from mmdet3d.evaluation import instance_seg_eval
 from mmdet3d.registry import METRICS
 
 

mmdet3d/metrics/kitti_metric.py → mmdet3d/evaluation/metrics/kitti_metric.py

@@ -10,10 +10,10 @@ from mmcv.utils import print_log
 from mmengine.evaluator import BaseMetric
 from mmengine.logging import MMLogger
 
-from mmdet3d.core.bbox import (Box3DMode, CameraInstance3DBoxes,
-                               LiDARInstance3DBoxes, points_cam2img)
-from mmdet3d.core.evaluation import kitti_eval
+from mmdet3d.evaluation import kitti_eval
 from mmdet3d.registry import METRICS
+from mmdet3d.structures import (Box3DMode, CameraInstance3DBoxes,
+                                LiDARInstance3DBoxes, points_cam2img)
 
 
 @METRICS.register_module()

mmdet3d/metrics/lyft_metric.py → mmdet3d/evaluation/metrics/lyft_metric.py

@@ -14,7 +14,7 @@ from mmengine.evaluator import BaseMetric
 from mmengine.logging import MMLogger
 from pyquaternion import Quaternion
 
-from mmdet3d.core.evaluation.lyft_eval import lyft_eval
+from mmdet3d.evaluation import lyft_eval
 from mmdet3d.registry import METRICS
 
 
@@ -354,7 +354,7 @@ def output_to_lyft_box(detection: dict) -> List[LyftBox]:
     Returns:
         list[:obj:`LyftBox`]: List of standard LyftBoxes.
     """
-    bbox3d = detection['bboxes_3d']
+    bbox3d = detection['bbox_3d']
     scores = detection['scores_3d'].numpy()
     labels = detection['labels_3d'].numpy()
 

mmdet3d/metrics/nuscenes_metric.py → mmdet3d/evaluation/metrics/nuscenes_metric.py

@@ -14,9 +14,10 @@ from nuscenes.eval.detection.config import config_factory
 from nuscenes.eval.detection.data_classes import DetectionConfig
 from nuscenes.utils.data_classes import Box as NuScenesBox
 
-from mmdet3d.core import bbox3d2result, box3d_multiclass_nms, xywhr2xyxyr
-from mmdet3d.core.bbox import CameraInstance3DBoxes, LiDARInstance3DBoxes
+from mmdet3d.models.layers import box3d_multiclass_nms
 from mmdet3d.registry import METRICS
+from mmdet3d.structures import (CameraInstance3DBoxes, LiDARInstance3DBoxes,
+                                bbox3d2result, xywhr2xyxyr)
 
 
 @METRICS.register_module()
@@ -294,7 +295,7 @@ class NuScenesMetric(BaseMetric):
                 print(f'\nFormating bboxes of {name}')
                 results_ = [out[name] for out in results]
                 tmp_file_ = osp.join(jsonfile_prefix, name)
-                box_type_3d = type(results_[0]['bboxes_3d'])
+                box_type_3d = type(results_[0]['bbox_3d'])
                 if box_type_3d == LiDARInstance3DBoxes:
                     result_dict[name] = self._format_lidar_bbox(
                         results_, sample_id_list, classes, tmp_file_)
@@ -505,14 +506,14 @@ def output_to_nusc_box(detection: dict) -> List[NuScenesBox]:
     Args:
         detection (dict): Detection results.
 
-            - bboxes_3d (:obj:`BaseInstance3DBoxes`): Detection bbox.
+            - bbox_3d (:obj:`BaseInstance3DBoxes`): Detection bbox.
             - scores_3d (torch.Tensor): Detection scores.
             - labels_3d (torch.Tensor): Predicted box labels.
 
     Returns:
         list[:obj:`NuScenesBox`]: List of standard NuScenesBoxes.
     """
-    bbox3d = detection['bboxes_3d']
+    bbox3d = detection['bbox_3d']
     scores = detection['scores_3d'].numpy()
     labels = detection['labels_3d'].numpy()
     attrs = None

mmdet3d/metrics/seg_metric.py → mmdet3d/evaluation/metrics/seg_metric.py

@@ -4,7 +4,7 @@ from typing import Dict, Optional, Sequence
 from mmengine.evaluator import BaseMetric
 from mmengine.logging import MMLogger
 
-from mmdet3d.core import seg_eval
+from mmdet3d.evaluation import seg_eval
 from mmdet3d.registry import METRICS
 
 

mmdet3d/models/__init__.py

 # Copyright (c) OpenMMLab. All rights reserved.
+from mmdet3d.models.layers.fusion_layers import *  # noqa: F401,F403
 from .backbones import *  # noqa: F401,F403
 from .builder import (BACKBONES, DETECTORS, FUSION_LAYERS, HEADS, LOSSES,
                       MIDDLE_ENCODERS, NECKS, ROI_EXTRACTORS, SEGMENTORS,
@@ -11,13 +12,14 @@ from .data_preprocessors import *  # noqa: F401,F403
 from .decode_heads import *  # noqa: F401,F403
 from .dense_heads import *  # noqa: F401,F403
 from .detectors import *  # noqa: F401,F403
-from .fusion_layers import *  # noqa: F401,F403
+from .layers import *  # noqa: F401,F403
 from .losses import *  # noqa: F401,F403
 from .middle_encoders import *  # noqa: F401,F403
-from .model_utils import *  # noqa: F401,F403
 from .necks import *  # noqa: F401,F403
 from .roi_heads import *  # noqa: F401,F403
 from .segmentors import *  # noqa: F401,F403
+from .test_time_augs import *  # noqa: F401,F403
+from .utils import *  # noqa: F401,F403
 from .voxel_encoders import *  # noqa: F401,F403
 
 __all__ = [