FlowItOut

Generate Optical Flow from trending Optical Flow Algorithms

Usage

1. Clone and Update Submodules(RAFT)

git clone https://github.com/Justin62628/FlowItOut
cd FlowItOut
git submodule update --init --recursive

2. Install Dependencies by pip

pip install -r requirements.txt

2.1 Install PyTorch with CUDA, we are currently using CUDA 11.3

pip install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cu113

2.2 Put ffmpeg and ffprobe in your System Environment Parameters

For Windows users, put ffmpeg.exe and ffprobe.exe in the same folder for greatest convenience. 3. Download models from other places, put them in models

mkdir models

For RAFT, download raft.pkl at Google Drive 4. Prepare a video for test and Run

mkdir test
python flow_it_out.py -i test/test.mp4

Typical Commands to use GMF:

python ./flow_it_out.py -i test/test.mp4 -s 960x540 --gmflow --model models/flownet.pkl

4.1 Please DO Remember to read notes by python flow_it_out.py --help

usage: #### FlowItOut by Jeanna #### [-h] -i INPUT [-s RESIZE] [--model MODEL]
                                     [--raft | --gmflow | --others] [--small] 
                                     [--mixed_precision] [--alternate_corr]   

To generate flow by different trending algorithms

optional arguments:
  -h, --help            show this help message and exit

Basic Settings:
  -i INPUT, --input INPUT
                        Path of input video
  -s RESIZE, --resize RESIZE
                        Resized Resolution for flow, leave '0' for no-resize
  --model MODEL         restore checkpoint
  --raft
  --gmflow
  --others

RAFT Settings:
  Set the following parameters for RAFT

  --small               use small model
  --mixed_precision     use mixed precision
  --alternate_corr      use efficent correlation implementation, if
                        alternate_corr is not compiled, do not use