Merge branch 'dev' of github.com:open-mmlab/mmrotate into hrsc

� Conflicts:
�	mmrotate/datasets/dota.py

.github/workflows/build.yml

@@ -198,7 +198,7 @@ jobs:
       - name: Build and install
         run: pip install -e .
       - name: Run unittests
-        run: coverage run --branch --source mmrotate -m pytest tests -sv
+        run: coverage run --branch --source mmrotate -m pytest tests
       - name: Generate coverage report
         run: |
           coverage xml

README.md

@@ -145,21 +145,21 @@ This project is released under the [Apache 2.0 license](LICENSE).
 ## Projects in OpenMMLab
 
 * [MMCV](https://github.com/open-mmlab/mmcv): OpenMMLab foundational library for computer vision.
-* [MIM](https://github.com/open-mmlab/mim): MIM Installs OpenMMLab Packages.
+* [MIM](https://github.com/open-mmlab/mim): MIM installs OpenMMLab packages.
 * [MMClassification](https://github.com/open-mmlab/mmclassification): OpenMMLab image classification toolbox and benchmark.
 * [MMDetection](https://github.com/open-mmlab/mmdetection): OpenMMLab detection toolbox and benchmark.
-* [MMDetection3D](https://github.com/open-mmlab/mmdetection3d): OpenMMLab next-generation platform for general 3D object detection.
+* [MMDetection3D](https://github.com/open-mmlab/mmdetection3d): OpenMMLab's next-generation platform for general 3D object detection.
+* [MMRotate](https://github.com/open-mmlab/mmrotate): OpenMMLab rotated object detection toolbox and benchmark.
 * [MMSegmentation](https://github.com/open-mmlab/mmsegmentation): OpenMMLab semantic segmentation toolbox and benchmark.
-* [MMAction2](https://github.com/open-mmlab/mmaction2): OpenMMLab next-generation action understanding toolbox and benchmark.
-* [MMTracking](https://github.com/open-mmlab/mmtracking): OpenMMLab video perception toolbox and benchmark.
+* [MMOCR](https://github.com/open-mmlab/mmocr): OpenMMLab text detection, recognition, and understanding toolbox.
 * [MMPose](https://github.com/open-mmlab/mmpose): OpenMMLab pose estimation toolbox and benchmark.
-* [MMEditing](https://github.com/open-mmlab/mmediting): OpenMMLab image and video editing toolbox.
-* [MMOCR](https://github.com/open-mmlab/mmocr): A comprehensive toolbox for text detection, recognition and understanding.
-* [MMGeneration](https://github.com/open-mmlab/mmgeneration): OpenMMLab next-generation toolbox for generative models.
-* [MMFlow](https://github.com/open-mmlab/mmflow): OpenMMLab optical flow toolbox and benchmark.
-* [MMFewShot](https://github.com/open-mmlab/mmfewshot): OpenMMLab fewshot learning toolbox and benchmark.
 * [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.
+* [MMFewShot](https://github.com/open-mmlab/mmfewshot): OpenMMLab fewshot learning toolbox and benchmark.
+* [MMAction2](https://github.com/open-mmlab/mmaction2): OpenMMLab's next-generation action understanding toolbox and benchmark.
+* [MMTracking](https://github.com/open-mmlab/mmtracking): OpenMMLab video perception toolbox and benchmark.
+* [MMFlow](https://github.com/open-mmlab/mmflow): OpenMMLab optical flow toolbox and benchmark.
+* [MMEditing](https://github.com/open-mmlab/mmediting): OpenMMLab image and video editing toolbox.
+* [MMGeneration](https://github.com/open-mmlab/mmgeneration): OpenMMLab image and video generative models toolbox.
 * [MMDeploy](https://github.com/open-mmlab/mmdeploy): OpenMMLab model deployment framework.
-* [MMRotate](https://github.com/open-mmlab/mmrotate): OpenMMLab rotated object detection toolbox and benchmark.

README_zh-CN.md

@@ -141,23 +141,23 @@ MMRotate 是一款由不同学校和公司共同贡献的开源项目。我们
 
 * [MMCV](https://github.com/open-mmlab/mmcv): OpenMMLab 计算机视觉基础库
 * [MIM](https://github.com/open-mmlab/mim): MIM 是 OpenMMlab 项目、算法、模型的统一入口
-* [MMClassification](https://github.com/open-mmlab/mmclassification): OpenMMLab 图像分类工具箱与测试基准
-* [MMDetection](https://github.com/open-mmlab/mmdetection): OpenMMLab 检测工具箱与测试基准
-* [MMDetection3D](https://github.com/open-mmlab/mmdetection3d): OpenMMLab 新一代通用3D目标检测平台
-* [MMSegmentation](https://github.com/open-mmlab/mmsegmentation): OpenMMLab 语义分割工具箱与测试基准
-* [MMAction2](https://github.com/open-mmlab/mmaction2): OpenMMLab 新一代视频理解工具箱与测试基准
-* [MMTracking](https://github.com/open-mmlab/mmtracking): OpenMMLab 一体化视频目标感知平台
-* [MMPose](https://github.com/open-mmlab/mmpose): OpenMMLab 姿态估计工具箱与测试基准
-* [MMEditing](https://github.com/open-mmlab/mmediting): OpenMMLab 图像视频编辑工具箱
+* [MMClassification](https://github.com/open-mmlab/mmclassification): OpenMMLab 图像分类工具箱
+* [MMDetection](https://github.com/open-mmlab/mmdetection): OpenMMLab 目标检测工具箱
+* [MMDetection3D](https://github.com/open-mmlab/mmdetection3d): OpenMMLab 新一代通用 3D 目标检测平台
+* [MMRotate](https://github.com/open-mmlab/mmrotate): OpenMMLab 旋转框检测工具箱与测试基准
+* [MMSegmentation](https://github.com/open-mmlab/mmsegmentation): OpenMMLab 语义分割工具箱
 * [MMOCR](https://github.com/open-mmlab/mmocr): OpenMMLab 全流程文字检测识别理解工具包
-* [MMGeneration](https://github.com/open-mmlab/mmgeneration): OpenMMLab 新一代生成模型工具箱
-* [MMFlow](https://github.com/open-mmlab/mmflow): OpenMMLab 光流估计工具箱与测试基准
-* [MMFewShot](https://github.com/open-mmlab/mmfewshot): OpenMMLab 少样本学习工具箱与测试基准
+* [MMPose](https://github.com/open-mmlab/mmpose): OpenMMLab 姿态估计工具箱
 * [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
+* [MMFewShot](https://github.com/open-mmlab/mmfewshot): OpenMMLab 少样本学习工具箱与测试基准
+* [MMAction2](https://github.com/open-mmlab/mmaction2): OpenMMLab 新一代视频理解工具箱
+* [MMTracking](https://github.com/open-mmlab/mmtracking): OpenMMLab 一体化视频目标感知平台
+* [MMFlow](https://github.com/open-mmlab/mmflow): OpenMMLab 光流估计工具箱与测试基准
+* [MMEditing](https://github.com/open-mmlab/mmediting): OpenMMLab 图像视频编辑工具箱
+* [MMGeneration](https://github.com/open-mmlab/mmgeneration): OpenMMLab 图片视频生成模型工具箱
 * [MMDeploy](https://github.com/open-mmlab/mmdeploy): OpenMMLab 模型部署框架
-* [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
 

mmrotate/models/roi_heads/roi_extractors/rotate_single_level_roi_extractor.py

@@ -98,19 +98,21 @@ def forward(self, feats, rois, roi_scale_factor=None):
         Returns:
             torch.Tensor: Scaled RoI features.
         """
-        out_size = self.roi_layers[0].out_size
+        if isinstance(self.roi_layers[0], ops.RiRoIAlignRotated):
+            out_size = nn.modules.utils._pair(self.roi_layers[0].out_size)
+        else:
+            out_size = self.roi_layers[0].output_size
         num_levels = len(feats)
-        expand_dims = (-1, self.out_channels * out_size * out_size)
+        expand_dims = (-1, self.out_channels * out_size[0] * out_size[1])
         if torch.onnx.is_in_onnx_export():
             # Work around to export mask-rcnn to onnx
             roi_feats = rois[:, :1].clone().detach()
             roi_feats = roi_feats.expand(*expand_dims)
-            roi_feats = roi_feats.reshape(-1, self.out_channels, out_size,
-                                          out_size)
+            roi_feats = roi_feats.reshape(-1, self.out_channels, *out_size)
             roi_feats = roi_feats * 0
         else:
             roi_feats = feats[0].new_zeros(
-                rois.size(0), self.out_channels, out_size, out_size)
+                rois.size(0), self.out_channels, *out_size)
         # TODO: remove this when parrots supports
         if torch.__version__ == 'parrots':
             roi_feats.requires_grad = True