[Enhancement] Upgrade isort in pre-commit hook (#1217)

* update isort

* update setuptools

* fix

* pre-commit run --all-files

.dev_scripts/gather_models.py

@@ -18,12 +18,13 @@ into it.
 import argparse
 import glob
 import json
-import mmcv
 import shutil
 import subprocess
-import torch
 from os import path as osp
 
+import mmcv
+import torch
+
 # build schedule look-up table to automatically find the final model
 SCHEDULES_LUT = {
     '_1x_': 12,

.pre-commit-config.yaml

@@ -3,12 +3,8 @@ repos:
     rev: 3.8.3
     hooks:
       - id: flake8
-  - repo: https://github.com/asottile/seed-isort-config
-    rev: v2.2.0
-    hooks:
-      - id: seed-isort-config
-  - repo: https://github.com/timothycrosley/isort
-    rev: 5.0.2
+  - repo: https://github.com/PyCQA/isort
+    rev: 5.10.1
     hooks:
       - id: isort
   - repo: https://github.com/pre-commit/mirrors-yapf

configs/pgd/metafile.yml

@@ -27,7 +27,7 @@ Models:
         Metrics:
           mAP: 18.33
     Weights: https://download.openmmlab.com/mmdetection3d/v1.0.0_models/pgd/pgd_r101_caffe_fpn_gn-head_3x4_4x_kitti-mono3d/pgd_r101_caffe_fpn_gn-head_3x4_4x_kitti-mono3d_20211022_102608-8a97533b.pth
-    
+
   - Name: pgd_r101_caffe_fpn_gn-head_2x16_1x_nus-mono3d
     In Collection: PGD
     Config: configs/pgd/pgd_r101_caffe_fpn_gn-head_2x16_1x_nus-mono3d.py

data/s3dis/collect_indoor3d_data.py

 import argparse
+from os import path as osp
+
 import mmcv
 from indoor3d_util import export
-from os import path as osp
 
 parser = argparse.ArgumentParser()
 parser.add_argument(

data/s3dis/indoor3d_util.py

 import glob
-import numpy as np
 from os import path as osp
 
+import numpy as np
+
 # -----------------------------------------------------------------------------
 # CONSTANTS
 # -----------------------------------------------------------------------------

data/scannet/batch_load_scannet_data.py

@@ -11,11 +11,12 @@ Usage example: python ./batch_load_scannet_data.py
 """
 import argparse
 import datetime
-import numpy as np
 import os
-from load_scannet_data import export
 from os import path as osp
 
+import numpy as np
+from load_scannet_data import export
+
 DONOTCARE_CLASS_IDS = np.array([])
 OBJ_CLASS_IDS = np.array(
     [3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 14, 16, 24, 28, 33, 34, 36, 39])

data/scannet/extract_posed_images.py

 # Modified from https://github.com/ScanNet/ScanNet/blob/master/SensReader/python/SensorData.py # noqa
-import imageio
-import mmcv
-import numpy as np
 import os
 import struct
 import zlib
 from argparse import ArgumentParser
 from functools import partial
 
+import imageio
+import mmcv
+import numpy as np
+
 COMPRESSION_TYPE_COLOR = {-1: 'unknown', 0: 'raw', 1: 'png', 2: 'jpeg'}
 
 COMPRESSION_TYPE_DEPTH = {

data/scannet/load_scannet_data.py

@@ -9,8 +9,9 @@ instance segmentations."""
 import argparse
 import inspect
 import json
-import numpy as np
 import os
+
+import numpy as np
 import scannet_utils
 
 currentdir = os.path.dirname(

data/scannet/scannet_utils.py

@@ -8,8 +8,9 @@
 """
 
 import csv
-import numpy as np
 import os
+
+import numpy as np
 from plyfile import PlyData
 
 

docs/en/conf.py

@@ -11,9 +11,10 @@
 # documentation root, use os.path.abspath to make it absolute, like shown here.
 #
 import os
-import pytorch_sphinx_theme
 import subprocess
 import sys
+
+import pytorch_sphinx_theme
 from m2r import MdInclude
 from recommonmark.transform import AutoStructify
 from sphinx.builders.html import StandaloneHTMLBuilder

docs/en/stat.py

 #!/usr/bin/env python
 import functools as func
 import glob
-import numpy as np
 import re
 from os import path as osp
 
+import numpy as np
+
 url_prefix = 'https://github.com/open-mmlab/mmdetection3d/blob/master/'
 
 files = sorted(glob.glob('../configs/*/README.md'))

docs/zh_cn/conf.py

@@ -11,9 +11,10 @@
 # documentation root, use os.path.abspath to make it absolute, like shown here.
 #
 import os
-import pytorch_sphinx_theme
 import subprocess
 import sys
+
+import pytorch_sphinx_theme
 from m2r import MdInclude
 from recommonmark.transform import AutoStructify
 from sphinx.builders.html import StandaloneHTMLBuilder

docs/zh_cn/stat.py

 #!/usr/bin/env python
 import functools as func
 import glob
-import numpy as np
 import re
 from os import path as osp
 
+import numpy as np
+
 url_prefix = 'https://github.com/open-mmlab/mmdetection3d/blob/master/'
 
 files = sorted(glob.glob('../configs/*/README.md'))

mmdet3d/apis/inference.py

 # Copyright (c) OpenMMLab. All rights reserved.
+import re
+from copy import deepcopy
+from os import path as osp
+
 import mmcv
 import numpy as np
-import re
 import torch
-from copy import deepcopy
 from mmcv.parallel import collate, scatter
 from mmcv.runner import load_checkpoint
-from os import path as osp
 
 from mmdet3d.core import (Box3DMode, CameraInstance3DBoxes, Coord3DMode,
                           DepthInstance3DBoxes, LiDARInstance3DBoxes,

mmdet3d/apis/test.py

 # Copyright (c) OpenMMLab. All rights reserved.
+from os import path as osp
+
 import mmcv
 import torch
 from mmcv.image import tensor2imgs
-from os import path as osp
 
 from mmdet3d.models import (Base3DDetector, Base3DSegmentor,
                             SingleStageMono3DDetector)

mmdet3d/core/bbox/structures/base_box3d.py

 # Copyright (c) OpenMMLab. All rights reserved.
-import numpy as np
-import torch
 import warnings
 from abc import abstractmethod
 
+import numpy as np
+import torch
+
 from mmdet3d.ops import points_in_boxes_all, points_in_boxes_part
 from mmdet3d.ops.iou3d import iou3d_cuda
 from .utils import limit_period, xywhr2xyxyr

mmdet3d/core/bbox/structures/box_3d_mode.py

 # Copyright (c) OpenMMLab. All rights reserved.
+from enum import IntEnum, unique
+
 import numpy as np
 import torch
-from enum import IntEnum, unique
 
 from .base_box3d import BaseInstance3DBoxes
 from .cam_box3d import CameraInstance3DBoxes

mmdet3d/core/bbox/structures/coord_3d_mode.py

 # Copyright (c) OpenMMLab. All rights reserved.
+from enum import IntEnum, unique
+
 import numpy as np
 import torch
-from enum import IntEnum, unique
 
 from ...points import BasePoints, CameraPoints, DepthPoints, LiDARPoints
 from .base_box3d import BaseInstance3DBoxes

mmdet3d/core/bbox/structures/utils.py

 # Copyright (c) OpenMMLab. All rights reserved.
+from logging import warning
+
 import numpy as np
 import torch
-from logging import warning
 
 from mmdet3d.core.utils import array_converter
 

mmdet3d/core/evaluation/kitti_utils/eval.py

 # Copyright (c) OpenMMLab. All rights reserved.
 import gc
 import io as sysio
+
 import numba
 import numpy as np