/cain-ncnn-vulkan

CAIN, Channel Attention Is All You Need for Video Frame Interpolation implemented with ncnn library

Primary LanguageCMIT LicenseMIT

CAIN ncnn Vulkan

CI download

ncnn implementation of CAIN, Channel Attention Is All You Need for Video Frame Interpolation.

cain-ncnn-vulkan uses ncnn project as the universal neural network inference framework.

Download

Download Windows/Linux/MacOS Executable for Intel/AMD/Nvidia GPU

https://github.com/nihui/cain-ncnn-vulkan/releases

This package includes all the binaries and models required. It is portable, so no CUDA or PyTorch runtime environment is needed :)

About CAIN

CAIN (Channel Attention Is All You Need for Video Frame Interpolation) (AAAI 2020)

https://github.com/myungsub/CAIN

Myungsub Choi, Heewon Kim, Bohyung Han, Ning Xu, Kyoung Mu Lee

2nd place in [AIM 2019 ICCV Workshop] - Video Temporal Super-Resolution Challenge

Project | Paper-AAAI (Download the paper [here] in case the AAAI link is broken) | Poster

Usages

Input two frame images, output one interpolated frame image.

Example Command

./cain-ncnn-vulkan -0 0.jpg -1 1.jpg -o 01.jpg
./cain-ncnn-vulkan -i input_frames/ -o output_frames/

Video Interpolation with FFmpeg

mkdir input_frames
mkdir output_frames

# find the source fps and format with ffprobe, for example 24fps, AAC
ffprobe input.mp4

# extract audio
ffmpeg -i input.mp4 -vn -acodec copy audio.m4a

# decode all frames
ffmpeg -i input.mp4 input_frames/frame_%06d.png

# interpolate 2x frame count
./cain-ncnn-vulkan -i input_frames -o output_frames

# encode interpolated frames in 48fps with audio
ffmpeg -framerate 48 -i output_frames/%06d.png -i audio.m4a -c:a copy -crf 20 -c:v libx264 -pix_fmt yuv420p output.mp4

Full Usages

Usage: cain-ncnn-vulkan -0 infile -1 infile1 -o outfile [options]...
       cain-ncnn-vulkan -i indir -o outdir [options]...

  -h                   show this help
  -v                   verbose output
  -0 input0-path       input image0 path (jpg/png/webp)
  -1 input1-path       input image1 path (jpg/png/webp)
  -i input-path        input image directory (jpg/png/webp)
  -o output-path       output image path (jpg/png/webp) or directory
  -m model-path        cain model path (default=cain)
  -g gpu-id            gpu device to use (default=auto) can be 0,1,2 for multi-gpu
  -j load:proc:save    thread count for load/proc/save (default=1:2:2) can be 1:2,2,2:2 for multi-gpu
  -f pattern-format    output image filename pattern format (%08d.jpg/png/webp, default=ext/%08d.png)
  • input0-path, input1-path and output-path accept file path
  • input-path and output-path accept file directory
  • load:proc:save = thread count for the three stages (image decoding + cain interpolation + image encoding), using larger values may increase GPU usage and consume more GPU memory. You can tune this configuration with "4:4:4" for many small-size images, and "2:2:2" for large-size images. The default setting usually works fine for most situations. If you find that your GPU is hungry, try increasing thread count to achieve faster processing.
  • pattern-format = the filename pattern and format of the image to be output, png is better supported, however webp generally yields smaller file sizes, both are losslessly encoded

If you encounter a crash or error, try upgrading your GPU driver:

Build from Source

  1. Download and setup the Vulkan SDK from https://vulkan.lunarg.com/
  • For Linux distributions, you can either get the essential build requirements from package manager
dnf install vulkan-headers vulkan-loader-devel
apt-get install libvulkan-dev
pacman -S vulkan-headers vulkan-icd-loader
  1. Clone this project with all submodules
git clone https://github.com/nihui/cain-ncnn-vulkan.git
cd cain-ncnn-vulkan
git submodule update --init --recursive
  1. Build with CMake
  • You can pass -DUSE_STATIC_MOLTENVK=ON option to avoid linking the vulkan loader library on MacOS
mkdir build
cd build
cmake ../src
cmake --build . -j 4

TODO

  • test-time sptial augmentation aka TTA-s
  • test-time temporal augmentation aka TTA-t

Sample Images

Original Image

origin0 origin1

Interpolate with cain

cain-ncnn-vulkan.exe -0 0.png -1 1.png -o out.png

cain

Original CAIN Project

Other Open-Source Code Used