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Extract TVL1 optical flows in python (multi-process && multi-server)

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Py-denseflow

This is a python port of denseflow, which extract the videos' frames and optical flow images with TVL1 algorithm as default.


Requirements:

  • numpy
  • cv2
  • PIL.Image
  • multiprocess
  • scikit-video (optional)
  • scipy

Installation

Install the requirements:

pip install -r requirements.txt


Usage

The denseflow.py contains two modes including 'run' and 'debug'.

here 'debug' is built for debugging the video paths and video-read methods. (IPython.embed suggested)

Just simply run the following code:

python denseflow.py --new_dir=denseflow_py --num_workers=1 --step=1 --bound=20 --mode=debug

While in 'run' mode, here we provide multi-process as well as multi-server with manually s_/e_ IDs setting.

for example: server 0 need to process 3000 videos with 4 processes parallelly working:

python denseflow.py --new_dir=denseflow_py --num_workers=4 --step=1 --bound=20 --mode=run --s_=0 --e_=3000

Just feel free to let me know if any bugs exist.

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Extract TVL1 optical flows in python (multi-process && multi-server)

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