Unofficial PyTorch implementation of MaskFlownet (https://github.com/microsoft/MaskFlownet).
Tested with:
- PyTorch 1.5.0
- CUDA 10.1
The correlation package must be installed first:
cd model/correlation_package
python setup.py install
Right now, I implemented the inference script for KITTI 2012/2015, MPI Sintel and FlyingChairs.
python predict.py CONFIG -c CHECKPOINT --dataset_cfg DATASET -f ROOT_FOLDER [-b BATCH_SIZE]
For example:
python predict.py MaskFlownet.yaml -c 5adNov03-0005_1000000.pth --dataset_cfg sintel.yaml -f ./SINTEL -b 4
python predict.py MaskFlownet.yaml -c 8caNov12-1532_300000.pth --dataset_cfg kitti.yaml -f ./KITTI -b 4
python predict.py MaskFlownet_S.yaml -c 771Sep25-0735_500000.pth --dataset_cfg chairs.yaml -f ./FLYINGCHAIRS -b 4
python predict.py MaskFlownet_S.yaml -c dbbSep30-1206_1000000.pth --dataset_cfg sintel.yaml -f ./SINTEL -b 4
The results are slightly different from the original implementation:
Checkpoint | Network | Implementation | KITTI2012 | KITTI2015 | Sintel Clean | Sintel Final | FlyingChairs |
---|---|---|---|---|---|---|---|
771Sep25 | MaskFlownet_S | Original AEPE: |
4.12 |
11.52 |
3.38 |
4.71 |
1.84 |
dbbSep30 | MaskFlownet_S | Original AEPE: |
1.27 |
1.92 |
2.76 |
3.29 |
2.36 |
5adNov03 | MaskFlownet | Original AEPE: |
1.16 |
1.66 |
2.58 |
3.14 |
2.23 |
8caNov12 | MaskFlownet | Original AEPE: |
0.82 |
1.38 |
4.34 |
5.27 |
4.01 |
KITTI Original implementation:
KITTI This implementation:
Sintel Original implementation:
Sintel This implementation:
FlyingChairs Original implementation:
FlyingChairs This implementation:
If you use my implementation for training, it might happen that you encounter this error:
CUDA error: an illegal memory access was encountered
This is due to a bug in the torchvision implementation of deformable convolutions. (still present in version 0.7.0)
To solve it, you need to use the nightly version of torchvision.
Original MXNet implementation: here
correlation_package was taken from flownet2