Extracting dense flow field given a video.
- support multiple optical flow algorithms, including Nvidia hardware optical flow
- support single video (or a frame folder) / a list of videos (or a list of frame folders) as input
- support multiple output types (image, hdf5)
- faster, 40% faster (by parallelize IO & computation)
- record the progress when extract a list of videos, and resume by simply running the same command again (idempotent)
git clone https://github.com/open-mmlab/denseflow.git
cd denseflow && mkdir build && cd build
cmake -DCMAKE_INSTALL_PREFIX=$HOME/app -DUSE_HDF5=no -DUSE_NVFLOW=no ..
make -j
make install
If you have trouble setting up building environments, scripts in INSTALL might be helpful.
denseflow test.avi -b=20 -a=tvl1 -s=1 -v
test.avi
: input video-b=20
bound set to 20-a=tvl1
algorithm is tvl1-s=1
step is 1, ie flow of adjacent frames-v
: verbose
denseflow videolist.txt -b=20 -a=tvl1 -s=1 -v
videolist.txt
: a list of video paths-b=20
bound set to 20-a=tvl1
algorithm is tvl1-s=1
step is 1, ie flow of adjacent frames-v
: verbose
denseflow videolist.txt -b=20 -a=tvl1 -s=1 -cf -v
videolist.txt
: a list of video paths-b=20
bound set to 20-a=tvl1
algorithm is tvl1-s=1
step is 1, ie flow of adjacent frames-cf
this switch means that parent folder of the video is a class name-v
: verbose
denseflow test -b=20 -a=tvl1 -s=1 -if -v
test
: folder of the frame images-b=20
bound set to 20-a=tvl1
algorithm is tvl1-s=1
step is 1, ie flow of adjacent frames-if
indicates that inputs are frames-v
: verbose
denseflow test.avi -s=0 -v
test.avi
: input video-s=0
step 0 is reserved for extracting frames-v
: verbose
denseflow videolist.txt -s=0 -v
videolist.txt
: a list of video paths-s=1
step is 1, ie flow of adjacent frames-s=0
step 0 is reserved for extracting frames-v
: verbose
$ denseflow -h
GPU optical flow extraction.
Usage: denseflow [params] input
-a, --algorithm (value:tvl1)
optical flow algorithm (nv/tvl1/farn/brox)
-b, --bound (value:32)
maximum of optical flow
--cf, --classFolder
outputDir/class/video/flow.jpg
-f, --force
regardless of the marked .done file
-h, --help (value:true)
print help message
--if, --inputFrames
inputs are frames
--newHeight, --nh (value:0)
new height
--newShort, --ns (value:0)
short side length
--newWidth, --nw (value:0)
new width
-o, --outputDir (value:.)
root dir of output
-s, --step (value:0)
right - left (0 for img, non-0 for flow)
--saveType, --st (value:jpg)
save format type (png/h5/jpg)
-v, --verbose
verbose
input
filename of video or folder of frames or a list.txt of those
If you use this tool in your research, please cite this project.
@misc{denseflow,
author = {Wang, Shiguang* and Li, Zhizhong* and Zhao, Yue and Xiong, Yuanjun and Wang, Limin and Lin, Dahua},
title = {{denseflow}},
howpublished = {\url{https://github.com/open-mmlab/denseflow}},
year = {2020}
}
Rewritten based on yuanjun's fork of dense_flow.