Add CI for windows (#7228)

* [Fix] Fix wrong img name in onnx2tensorrt.py (#7157)

* [Docs] fix albumentations installed way (#7143)

* Add mmrotate (#7216)

* fix description for args in CSPDarknet (#7187)

* Update build.yml

* Update build.yml

* Update build.yml

* Update build.yml

* Update build.yml

* Update build.yml

* Update build.yml

* Update build.yml

* Update build.yml

* Update build.yml

* Update build.yml

* Update build.yml

* fix test_find_latest_checkpoint

* fix data_infos__default_db_directories

* fix test_custom_classes_override_default

* Update test_custom_dataset.py

* Update test_common.py

* Update assign_result.py

* use os.path.join

* fix bug

* Update test_common.py

* Update assign_result.py

* Update sampling_result.py

* os.path -> osp

* os.path -> osp

Co-authored-by: Jamie <jamiechoi1995@users.noreply.github.com>
Co-authored-by: BigDong <yudongwang@tju.edu.cn>
Co-authored-by: Hyeokjoon Kwon <dsazz801@gmail.com>

.github/workflows/build.yml

@@ -231,3 +231,50 @@ jobs:
           env_vars: OS,PYTHON
           name: codecov-umbrella
           fail_ci_if_error: false
+
+  build_windows:
+    runs-on: ${{ matrix.os }}
+    strategy:
+      matrix:
+        os: [windows-2022]
+        python: [3.8]
+        platform: [cpu, cu111]
+    steps:
+      - uses: actions/checkout@v2
+      - name: Set up Python ${{ matrix.python }}
+        uses: actions/setup-python@v2
+        with:
+          python-version: ${{ matrix.python }}
+      - name: Upgrade pip
+        run: pip install pip --upgrade --user
+      - name: Install PyTorch
+        # As a complement to Linux CI, we test on PyTorch LTS version
+        run: pip install torch==1.8.2+${{ matrix.platform }} torchvision==0.9.2+${{ matrix.platform }} -f https://download.pytorch.org/whl/lts/1.8/torch_lts.html
+      - name: Install MMCV
+        run: pip install mmcv-full -f https://download.openmmlab.com/mmcv/dist/cpu/torch1.8/index.html --only-binary mmcv-full
+      - name: Install unittest dependencies
+        run: |
+          python -V
+          python -m pip install pycocotools
+          python -m pip install -r requirements/tests.txt -r requirements/optional.txt
+          python -m pip install albumentations>=0.3.2 --no-binary imgaug,albumentations
+          python -m pip install git+https://github.com/cocodataset/panopticapi.git
+          python -c 'import mmcv; print(mmcv.__version__)'
+      - name: Show pip list
+        run: pip list
+      - name: Build and install
+        run: pip install -e .
+      - name: Run unittests
+        run: coverage run --branch --source mmdet -m pytest tests -sv
+      - name: Generate coverage report
+        run: |
+          coverage xml
+          coverage report -m
+      - name: Upload coverage to Codecov
+        uses: codecov/codecov-action@v2
+        with:
+          file: ./coverage.xml
+          flags: unittests
+          env_vars: OS,PYTHON
+          name: codecov-umbrella
+          fail_ci_if_error: false

README.md

@@ -321,3 +321,4 @@ If you use this toolbox or benchmark in your research, please cite this project.
 - [MMHuman3D](https://github.com/open-mmlab/mmhuman3d): OpenMMLab 3D human parametric model toolbox and benchmark.
 - [MMSelfSup](https://github.com/open-mmlab/mmselfsup): OpenMMLab self-supervised learning toolbox and benchmark.
 - [MMRazor](https://github.com/open-mmlab/mmrazor): OpenMMLab Model Compression Toolbox and Benchmark.
+- [MMRotate](https://github.com/open-mmlab/mmrotate): OpenMMLab rotated object detection toolbox and benchmark.

README_zh-CN.md

@@ -324,6 +324,7 @@ MMDetection 是一款由来自不同高校和企业的研发人员共同参与
 - [MMHuman3D](https://github.com/open-mmlab/mmhuman3d): OpenMMLab 人体参数化模型工具箱与测试基准
 - [MMSelfSup](https://github.com/open-mmlab/mmselfsup): OpenMMLab 自监督学习工具箱与测试基准
 - [MMRazor](https://github.com/open-mmlab/mmrazor): OpenMMLab 模型压缩工具箱与测试基准
+- [MMRotate](https://github.com/open-mmlab/mmrotate): OpenMMLab 旋转框检测工具箱与测试基准
 
 ## 欢迎加入 OpenMMLab 社区
 

mmdet/core/bbox/assigners/assign_result.py

@@ -165,7 +165,7 @@ def random(cls, **kwargs):
             true_idxs = np.arange(num_gts)
             rng.shuffle(true_idxs)
             true_idxs = torch.from_numpy(true_idxs)
-            gt_inds[is_assigned] = true_idxs[:n_assigned]
+            gt_inds[is_assigned] = true_idxs[:n_assigned].long()
 
             gt_inds = torch.from_numpy(
                 rng.randint(1, num_gts + 1, size=num_preds))

mmdet/core/bbox/samplers/sampling_result.py

@@ -42,7 +42,7 @@ def __init__(self, pos_inds, neg_inds, bboxes, gt_bboxes, assign_result,
             if len(gt_bboxes.shape) < 2:
                 gt_bboxes = gt_bboxes.view(-1, 4)
 
-            self.pos_gt_bboxes = gt_bboxes[self.pos_assigned_gt_inds, :]
+            self.pos_gt_bboxes = gt_bboxes[self.pos_assigned_gt_inds.long(), :]
 
         if assign_result.labels is not None:
             self.pos_gt_labels = assign_result.labels[pos_inds]

mmdet/models/backbones/csp_darknet.py

@@ -128,9 +128,9 @@ class CSPDarknet(BaseModule):
         arch (str): Architecture of CSP-Darknet, from {P5, P6}.
             Default: P5.
         deepen_factor (float): Depth multiplier, multiply number of
-            channels in each layer by this amount. Default: 1.0.
-        widen_factor (float): Width multiplier, multiply number of
             blocks in CSP layer by this amount. Default: 1.0.
+        widen_factor (float): Width multiplier, multiply number of
+            channels in each layer by this amount. Default: 1.0.
         out_indices (Sequence[int]): Output from which stages.
             Default: (2, 3, 4).
         frozen_stages (int): Stages to be frozen (stop grad and set eval

tests/test_data/test_datasets/test_common.py

@@ -3,6 +3,8 @@
 import logging
 import os
 import os.path as osp
+import platform
+import shutil
 import tempfile
 from unittest.mock import MagicMock, patch
 
@@ -107,8 +109,11 @@ def _create_dummy_results():
 def test_dataset_init(config_path):
     use_symlink = False
     if not os.path.exists('./data'):
-        os.symlink('./tests/data', './data')
-        use_symlink = True
+        if platform.system() != 'Windows':
+            os.symlink('./tests/data', './data')
+            use_symlink = True
+        else:
+            shutil.copytree('./tests/data', './data')
     data_config = mmcv.Config.fromfile(config_path)
     if 'data' not in data_config:
         return
@@ -119,6 +124,8 @@ def test_dataset_init(config_path):
         dataset[0]
     if use_symlink:
         os.unlink('./data')
+    else:
+        shutil.rmtree('./data')
 
 
 def test_dataset_evaluation():

tests/test_data/test_datasets/test_custom_dataset.py

@@ -1,5 +1,5 @@
 # Copyright (c) OpenMMLab. All rights reserved.
-import os
+import os.path as osp
 import unittest
 from unittest.mock import MagicMock, patch
 
@@ -75,16 +75,16 @@ def test_custom_classes_override_default(dataset):
 
     # Test sending file path
     import tempfile
-    tmp_file = tempfile.NamedTemporaryFile()
-    with open(tmp_file.name, 'w') as f:
-        f.write('bus\ncar\n')
+    with tempfile.TemporaryDirectory() as tmpdir:
+        path = tmpdir + 'classes.txt'
+        with open(path, 'w') as f:
+            f.write('bus\ncar\n')
     custom_dataset = dataset_class(
         ann_file=MagicMock(),
         pipeline=[],
-        classes=tmp_file.name,
+        classes=path,
         test_mode=True,
         img_prefix='VOC2007' if dataset == 'VOCDataset' else '')
-    tmp_file.close()
 
     assert custom_dataset.CLASSES != original_classes
     assert custom_dataset.CLASSES == ['bus', 'car']
@@ -95,35 +95,34 @@ class CustomDatasetTests(unittest.TestCase):
 
     def setUp(self):
         super().setUp()
-        self.data_dir = os.path.join(
-            os.path.dirname(os.path.dirname(os.path.dirname(__file__))),
-            'data')
+        self.data_dir = osp.join(
+            osp.dirname(osp.dirname(osp.dirname(__file__))), 'data')
         self.dataset_class = DATASETS.get('XMLDataset')
 
     def test_data_infos__default_db_directories(self):
         """Test correct data read having a Pacal-VOC directory structure."""
-        test_dataset_root = os.path.join(self.data_dir, 'VOCdevkit', 'VOC2007')
+        test_dataset_root = osp.join(self.data_dir, 'VOCdevkit', 'VOC2007')
         custom_ds = self.dataset_class(
             data_root=test_dataset_root,
-            ann_file=os.path.join(test_dataset_root, 'ImageSets', 'Main',
-                                  'trainval.txt'),
+            ann_file=osp.join(test_dataset_root, 'ImageSets', 'Main',
+                              'trainval.txt'),
             pipeline=[],
             classes=('person', 'dog'),
             test_mode=True)
 
         self.assertListEqual([{
             'id': '000001',
-            'filename': 'JPEGImages/000001.jpg',
+            'filename': osp.join('JPEGImages', '000001.jpg'),
             'width': 353,
             'height': 500
         }], custom_ds.data_infos)
 
     def test_data_infos__overridden_db_subdirectories(self):
         """Test correct data read having a customized directory structure."""
-        test_dataset_root = os.path.join(self.data_dir, 'custom_dataset')
+        test_dataset_root = osp.join(self.data_dir, 'custom_dataset')
         custom_ds = self.dataset_class(
             data_root=test_dataset_root,
-            ann_file=os.path.join(test_dataset_root, 'trainval.txt'),
+            ann_file=osp.join(test_dataset_root, 'trainval.txt'),
             pipeline=[],
             classes=('person', 'dog'),
             test_mode=True,
@@ -133,7 +132,7 @@ def test_data_infos__overridden_db_subdirectories(self):
 
         self.assertListEqual([{
             'id': '000001',
-            'filename': 'images/000001.jpg',
+            'filename': osp.join('images', '000001.jpg'),
             'width': 353,
             'height': 500
         }], custom_ds.data_infos)

tests/test_utils/test_misc.py

@@ -1,4 +1,5 @@
 # Copyright (c) OpenMMLab. All rights reserved.
+import os.path as osp
 import tempfile
 
 import numpy as np
@@ -172,32 +173,32 @@ def test_find_latest_checkpoint():
         # There are no checkpoints in the path.
         assert latest is None
 
-        path = tmpdir + '/none'
+        path = osp.join(tmpdir, 'none')
         latest = find_latest_checkpoint(path)
         # The path does not exist.
         assert latest is None
 
     with tempfile.TemporaryDirectory() as tmpdir:
-        with open(tmpdir + '/latest.pth', 'w') as f:
+        with open(osp.join(tmpdir, 'latest.pth'), 'w') as f:
             f.write('latest')
         path = tmpdir
         latest = find_latest_checkpoint(path)
-        assert latest == tmpdir + '/latest.pth'
+        assert latest == osp.join(tmpdir, 'latest.pth')
 
     with tempfile.TemporaryDirectory() as tmpdir:
-        with open(tmpdir + '/iter_4000.pth', 'w') as f:
+        with open(osp.join(tmpdir, 'iter_4000.pth'), 'w') as f:
             f.write('iter_4000')
-        with open(tmpdir + '/iter_8000.pth', 'w') as f:
+        with open(osp.join(tmpdir, 'iter_8000.pth'), 'w') as f:
             f.write('iter_8000')
         path = tmpdir
         latest = find_latest_checkpoint(path)
-        assert latest == tmpdir + '/iter_8000.pth'
+        assert latest == osp.join(tmpdir, 'iter_8000.pth')
 
     with tempfile.TemporaryDirectory() as tmpdir:
-        with open(tmpdir + '/epoch_1.pth', 'w') as f:
+        with open(osp.join(tmpdir, 'epoch_1.pth'), 'w') as f:
             f.write('epoch_1')
-        with open(tmpdir + '/epoch_2.pth', 'w') as f:
+        with open(osp.join(tmpdir, 'epoch_2.pth'), 'w') as f:
             f.write('epoch_2')
         path = tmpdir
         latest = find_latest_checkpoint(path)
-        assert latest == tmpdir + '/epoch_2.pth'
+        assert latest == osp.join(tmpdir, 'epoch_2.pth')