论文标题
mmrotate：使用pytorch的旋转对象检测基准测试
MMRotate: A Rotated Object Detection Benchmark using PyTorch
论文作者
论文摘要
我们提出了一个名为mmrotate的开源工具箱，该工具箱提供了基于深度学习的流行旋转对象检测算法的训练，推断和评估的连贯算法框架。 Mmrotate实现了18种最先进的算法，并支持三种最常用的角度定义方法。为了促进与旋转对象检测有关的问题的未来研究和工业应用，我们还提供了大量训练有素的模型和详细的基准测试，以深入了解旋转对象检测的性能。 mmrotate将于https://github.com/open-mmlab/mmrotate公开发布。
We present an open-source toolbox, named MMRotate, which provides a coherent algorithm framework of training, inferring, and evaluation for the popular rotated object detection algorithm based on deep learning. MMRotate implements 18 state-of-the-art algorithms and supports the three most frequently used angle definition methods. To facilitate future research and industrial applications of rotated object detection-related problems, we also provide a large number of trained models and detailed benchmarks to give insights into the performance of rotated object detection. MMRotate is publicly released at https://github.com/open-mmlab/mmrotate.
