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PWC-Net_tf

PWC-Network with TensorFlow estimated flow

input image0, estimated flow at each 5 scale, ground truth flow, input image1

Acknowledgments

Working confirmed. I hope this helps you.
Adding PWCDCNet: advanced model! I'm going to make the trained parameters avaliable ASAP! :)
Unofficial implementation of CVPR2018 paper: Deqing Sun et al. "PWC-Net: CNNs for Optical Flow Using Pyramid, Warping, and Cost Volume". arXiv

Usage

<!-- - `model_3000epoch/model_3007.ckpt` is fully trained by [SintelClean](http://files.is.tue.mpg.de/sintel/MPI-Sintel-complete.zip) dataset. -->

Training (the case SintelClean)

# Training from scratch
python train.py --dataset SintelClean --dataset_dir /path/to/MPI-Sintel-complete 
# Start with learned checkpoint
python train.py --dataset SintelClean --dataset_dir /path/to/MPI-Sintel-complete --resume /path/to/model.ckpt

After running above script, utilize GPU-id is asked, (-1:CPU). You can use other learning configs (like --n_epoch or --batch_size) see all arguments in train.py, regards.

Testing (inferring optical flow) by paired images

python test.py --input_images /path/to/image_0 /path/to/image_1 --resume /path/to/model.ckpt
# for multiple images (using wild-card for 001.png, 002.png, 003.png, ...)
python test_continuous.py -i /path/to/images* -r /path/to/model.ckpt