https://github.com/willprice/flowty

The swiss army knife for extracting optical flow
https://github.com/willprice/flowty

brox cuda cython dense-inverse-search dis docker farneback lucas-kanade nvidia-docker opencv optic-flow optical-flow pyramidal tv-l1 tvl1 variational-refinement

Last synced: about 1 year ago
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The swiss army knife for extracting optical flow

• Host: GitHub
• URL: https://github.com/willprice/flowty
• Owner: willprice
• Created: 2019-04-15T22:13:43.000Z (about 7 years ago)
• Default Branch: master
• Last Pushed: 2020-05-13T08:46:28.000Z (about 6 years ago)
• Last Synced: 2025-04-10T23:43:49.685Z (about 1 year ago)
• Topics: brox, cuda, cython, dense-inverse-search, dis, docker, farneback, lucas-kanade, nvidia-docker, opencv, optic-flow, optical-flow, pyramidal, tv-l1, tvl1, variational-refinement
• Language: Python
• Homepage: https://flowty.rtfd.org
• Size: 19.5 MB
• Stars: 16
• Watchers: 7
• Forks: 1
• Open Issues: 16
• Metadata Files:
  • Readme: README.md
  • Changelog: CHANGELOG.md

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README

          
# Flowty

[![Build status](https://img.shields.io/circleci/project/github/willprice/flowty/master.svg)](https://circleci.com/gh/willprice/flowty)

[![Dockerhub](https://img.shields.io/badge/docker-flowty-informational.svg)](https://hub.docker.com/r/willprice/flowty)

[![Docker image size](https://images.microbadger.com/badges/image/willprice/flowty.svg)](https://microbadger.com/images/willprice/flowty)

[![Read the Docs](https://img.shields.io/readthedocs/flowty.svg)](https://flowty.rtfd.org)

## WARNING

Currently Flowty is built atop of OpenCV 4 which has a serious performance regression in (at least) TVL1 optical flow which makes it inpractical to use. I suggest using my other optical flow tool [furnari-flow](https://github.com/dl-container-registry/furnari-flow) until this has been resolved. I have a [benchmark repository](https://github.com/willprice/opencv-tvl1-performance-regression-demo) demoing this issue and have filed a [bug report](https://github.com/opencv/opencv_contrib/issues/2459). Until that is resolved I suggest you try out multiple tools and pick which ever you find most performant.

Flowty is the swiss army knife of computing optical flow. Flowty is...

- Performant—leveraging CUDA accelerated optical flow implementations.

- Easy to use—packaged in docker so you don't have to compile OpenCV and 

  Flowty yourself.

## Usage

Visit https://flowty.rtfd.org to learn more about how to obtain and use flowty.

In a nutshell:

```sh

$ ls /path/to/media

video.mp4

$ docker run --rm --runtime=nvidia willprice/flowty

[Flowty help description]

  

$ docker run -it --rm \

  --runtime=nvidia \

  --mount type=bind,source=/path/to/media,target=/data \

  willprice/flowty tvl1 /data/video.mp4 /data/flow/{axis}/{index:05d}.jpg --cuda

```