- https://github.com/jwyang/faster-rcnn.pytorch/tree/pytorch-1.0
- https://github.com/ruotianluo/pytorch-faster-rcnn
- Python 2.7 or 3.6
- Pytorch 1.1 or higher
- CUDA 9.0 or higher
- tensorboardX
First of all, clone the code
git clone https://github.com/leowangzi/FasterRCNN.git
cd FasterRCNN
Then, create a folder:
mkdir data
or
ln -s [source_data] data
- Support pytorch-1.1 (master).
- Support torchvision-0.3 (master).
We benchmark our code thoroughly on pascal voc datasets, using resnet101 network architecture. Below are the results:
1). PASCAL VOC 2007 (Train/Test: 07trainval/07test, scale=600, ROI Align)
| model | #GPUs | batch size | lr | lr_decay | max_epoch | time/epoch | mem/GPU | mAP |
|---|---|---|---|---|---|---|---|---|
| [Res-101] | 1 | 1 | 1e-3 | 5 | 10 | 0.88 hr | 3200 MB | 75.06 |
2). PASCAL VOC 2007&2012 (Train/Test: 07+12trainval/07test, scale=600, ROI Align)
| model | #GPUs | batch size | lr | lr_decay | max_epoch | time/epoch | mem/GPU | mAP |
|---|---|---|---|---|---|---|---|---|
| [Res-101] | 1 | 1 | 1e-3 | 5 | 10 | 0.88 hr | 3200 MB | 79.80 |