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Python bindings to optical flow algorithms.

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Python Optical Flow

This package provides python bindings to CUDA accelerated optical flow methods.

Methods

Brox Optical Flow

Taken from OpenCV 3.X 1. OpenCV must be installed on the machine.

To do: Write function to locate OpenCV on the machine without the use of pkg-config.

@inproceedings{brox2004high,
  title={High accuracy optical flow estimation based on a theory for warping},
  author={Brox, Thomas and Bruhn, Andr{\'e}s and Papenberg, Nils and Weickert, Joachim},
  booktitle={European conference on computer vision},
  pages={25--36},
  year={2004},
  organization={Springer}
}

Fast Edge-Preserving PatchMatch for Large Displacement Optical Flow

@inproceedings{bao2014cvpreppm,
  title={Fast Edge-Preserving PatchMatch for Large Displacement Optical Flow},
  author={Bao, Linchao and Yang, Qingxiong and Jin, Hailin},
  booktitle={IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2014},
  pages={3534-3541},
  organization={IEEE}
}

Install

git clone https://github.com/linchaobao/EPPM ~/EPPM
ln -s ~/EPPM .
python2 setup.py build_ext -i
python2 demo.py

1: https://docs.opencv.org/3.4.1/d7/d18/classcv_1_1cuda_1_1BroxOpticalFlow.html

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Python bindings to optical flow algorithms.

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