MaskFlownet-Pytorch

Unofficial PyTorch implementation of MaskFlownet (https://github.com/microsoft/MaskFlownet).

Tested with:

• PyTorch 1.5.0
• CUDA 10.1

Install

The correlation package must be installed first:

cd model/correlation_package
python setup.py install

Inference

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

Differences with the original implementation

The results are slightly different from the original implementation:

Examples

KITTI Original implementation:

KITTI This implementation:

Sintel Original implementation:

Sintel This implementation:

FlyingChairs Original implementation:

FlyingChairs This implementation:

Notes

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.

Acknowledgment

Original MXNet implementation: here

correlation_package was taken from flownet2