- 4 NVIDIA Tesla V100 GPUs
- Intel(R) Xeon(R) CPU E5-2640 v4 @ 2.40GHz
- Python 3.6 / 3.7
- PyTorch 1.1.0
- CUDA 10.0.176
- CUDNN 7.4.1
- All baselines were trained using 4 GPU with a batch size of 8 (2 images per GPU).
- We adopt the same training schedules as Detectron. 1x indicates 12 epochs and 2x indicates 24 epochs, which corresponds to slightly less iterations than Detectron and the difference can be ignored.
- We report the inference time as the overall time including data loading, network forwarding and post processing in chips with size of 1024.
More benchmark results based on the code are on the way.
- Baseline results on DOTA (R-FPN-50, without data augmentation)
