[Enhance] Refactor the import of `mmdet` (#1947)

* fix config

* refactor import of `mmdet`

* fix lint

* fix lint

mmdet3d/structures/ops/iou3d_calculator.py

 # Copyright (c) OpenMMLab. All rights reserved.
 import torch
+from mmdet.structures.bbox import bbox_overlaps
 
 from mmdet3d.registry import TASK_UTILS
 from mmdet3d.structures.bbox_3d import get_box_type
-from mmdet.structures.bbox import bbox_overlaps
 
 
 @TASK_UTILS.register_module()

mmdet3d/utils/collect_env.py

 # Copyright (c) OpenMMLab. All rights reserved.
+import mmdet
 from mmengine.utils import get_git_hash
 from mmengine.utils.dl_utils import collect_env as collect_base_env
 
-import mmdet
 import mmdet3d
 
 

mmdet3d/utils/typing.py

@@ -2,11 +2,11 @@
 """Collecting some commonly used type hint in MMDetection3D."""
 from typing import List, Optional, Union
 
+from mmdet.models.task_modules.samplers import SamplingResult
 from mmengine.config import ConfigDict
 from mmengine.structures import InstanceData
 
 from mmdet3d.structures.det3d_data_sample import Det3DDataSample
-from mmdet.models.task_modules.samplers import SamplingResult
 
 # Type hint of config data
 ConfigType = Union[ConfigDict, dict]

mmdet3d/visualization/local_visualizer.py

@@ -8,6 +8,7 @@ import numpy as np
 from matplotlib.collections import PatchCollection
 from matplotlib.patches import PathPatch
 from matplotlib.path import Path
+from mmdet.visualization import DetLocalVisualizer
 from mmengine.dist import master_only
 from mmengine.structures import InstanceData
 from mmengine.visualization.utils import check_type, tensor2ndarray
@@ -19,7 +20,6 @@ from mmdet3d.structures import (BaseInstance3DBoxes, CameraInstance3DBoxes,
                                 Det3DDataSample, LiDARInstance3DBoxes,
                                 PointData, points_cam2img)
 from mmdet3d.structures.bbox_3d.box_3d_mode import Box3DMode
-from mmdet.visualization import DetLocalVisualizer
 from .vis_utils import (proj_camera_bbox3d_to_img, proj_depth_bbox3d_to_img,
                         proj_lidar_bbox3d_to_img, to_depth_mode)
 
@@ -708,9 +708,9 @@ class Det3DLocalVisualizer(DetLocalVisualizer):
                 and masks. Defaults to 0.3.
             step (int): Global step value to record. Defaults to 0.
         """
-        classes = self.dataset_meta.get('classes', None)
-        # For object detection datasets, no palette is saved
-        palette = self.dataset_meta.get('palette', None)
+        classes = self.dataset_meta.get('CLASSES', None)
+        # For object detection datasets, no PALETTE is saved
+        palette = self.dataset_meta.get('PALETTE', None)
         ignore_index = self.dataset_meta.get('ignore_index', None)
 
         gt_data_3d = None

setup.cfg

@@ -7,8 +7,8 @@ SPLIT_BEFORE_EXPRESSION_AFTER_OPENING_PAREN = true
 line_length = 79
 multi_line_output = 0
 extra_standard_library = setuptools
-known_first_party = mmdet,mmseg,mmdet3d
-known_third_party = cv2,imageio,indoor3d_util,load_scannet_data,lyft_dataset_sdk,m2r,matplotlib,mmcv,nuimages,numba,numpy,nuscenes,pandas,plyfile,pycocotools,pyquaternion,pytest,pytorch_sphinx_theme,recommonmark,requests,scannet_utils,scipy,seaborn,shapely,skimage,sphinx,tensorflow,terminaltables,torch,trimesh,ts,waymo_open_dataset
+known_first_party = mmdet3d
+known_third_party = cv2,imageio,indoor3d_util,load_scannet_data,lyft_dataset_sdk,m2r,matplotlib,mmcv,mmdet,mmengine,nuimages,numba,numpy,nuscenes,pandas,plyfile,pycocotools,pyquaternion,pytest,pytorch_sphinx_theme,recommonmark,requests,scannet_utils,scipy,seaborn,shapely,skimage,sphinx,tensorflow,terminaltables,torch,trimesh,ts,waymo_open_dataset
 no_lines_before = STDLIB,LOCALFOLDER
 default_section = THIRDPARTY
 

tools/dataset_converters/create_gt_database.py

@@ -6,13 +6,13 @@ import mmcv
 import mmengine
 import numpy as np
 from mmcv.ops import roi_align
+from mmdet.evaluation import bbox_overlaps
 from mmengine import track_iter_progress
 from pycocotools import mask as maskUtils
 from pycocotools.coco import COCO
 
 from mmdet3d.datasets import build_dataset
 from mmdet3d.structures.ops import box_np_ops as box_np_ops
-from mmdet.evaluation import bbox_overlaps
 
 
 def _poly2mask(mask_ann, img_h, img_w):