waifu2x ncnn Vulkan

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ncnn implementation of waifu2x converter. Runs fast on Intel / AMD / NVIDIA / Apple-Silicon with Vulkan API.

waifu2x-ncnn-vulkan uses ncnn project as the universal neural network inference framework.

Download

Download Windows/Linux/macOS Executable for Intel/AMD/NVIDIA/Apple-Silicon GPU

https://github.com/nihui/waifu2x-ncnn-vulkan/releases

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

Usages

Example Command

waifu2x-ncnn-vulkan.exe -i input.jpg -o output.png -n 2 -s 2

Full Usages

Usage: waifu2x-ncnn-vulkan -i infile -o outfile [options]...

  -h                   show this help
  -v                   verbose output
  -i input-path        input image path (jpg/png/webp) or directory
  -o output-path       output image path (jpg/png/webp) or directory
  -n noise-level       denoise level (-1/0/1/2/3, default=0)
  -s scale             upscale ratio (1/2/4/8/16/32, default=2)
  -t tile-size         tile size (>=32/0=auto, default=0) can be 0,0,0 for multi-gpu
  -m model-path        waifu2x model path (default=models-cunet)
  -g gpu-id            gpu device to use (-1=cpu, 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
  -x                   enable tta mode
  -f format            output image format (jpg/png/webp, default=ext/png)

input-path and output-path accept either file path or directory path
noise-level = noise level, large value means strong denoise effect, -1 = no effect
scale = scale level, 1 = no scaling, 2 = upscale 2x
tile-size = tile size, use smaller value to reduce GPU memory usage, default selects automatically
load:proc:save = thread count for the three stages (image decoding + waifu2x upscaling + 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.
format = the 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:

Intel: https://downloadcenter.intel.com/product/80939/Graphics-Drivers
AMD: https://www.amd.com/en/support
NVIDIA: https://www.nvidia.com/Download/index.aspx

Build from Source

(macOS only) Download and setup the Vulkan SDK from https://vulkan.lunarg.com/
Clone this project with all submodules

git clone https://github.com/nihui/waifu2x-ncnn-vulkan.git
cd waifu2x-ncnn-vulkan
git submodule update --init --recursive

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

Speed Comparison with waifu2x-caffe-cui

Environment

Windows 10 1809
AMD R7-1700
NVIDIA GTX-1070
NVIDIA driver 419.67
CUDA 10.1.105
cuDNN 10.1

Measure-Command { waifu2x-ncnn-vulkan.exe -i input.png -o output.png -n 2 -s 2 -t [block size] -m [model dir] }

Measure-Command { waifu2x-caffe-cui.exe -t 0 --gpu 0 -b 1 -c [block size] -p cudnn --model_dir [model dir] -s 2 -n 2 -m noise_scale -i input.png -o output.png }

cunet

||Image Size|Target Size|Block Size|Total Time(s)|GPU Memory(MB)|
|---|---|---|---|---|---|
|waifu2x-ncnn-vulkan|200x200|400x400|400/200/100|0.86/0.86/0.82|638/638/197|
|waifu2x-caffe-cui|200x200|400x400|400/200/100|2.54/2.39/2.36|3017/936/843|
|waifu2x-ncnn-vulkan|400x400|800x800|400/200/100|1.17/1.04/1.02|2430/638/197|
|waifu2x-caffe-cui|400x400|800x800|400/200/100|2.91/2.43/2.7|3202/1389/1178|
|waifu2x-ncnn-vulkan|1000x1000|2000x2000|400/200/100|2.35/2.26/2.46|2430/638/197|
|waifu2x-caffe-cui|1000x1000|2000x2000|400/200/100|4.04/3.79/4.35|3258/1582/1175|
|waifu2x-ncnn-vulkan|2000x2000|4000x4000|400/200/100|6.46/6.59/7.49|2430/686/213|
|waifu2x-caffe-cui|2000x2000|4000x4000|400/200/100|7.01/7.54/10.11|3258/1499/1200|
|waifu2x-ncnn-vulkan|4000x4000|8000x8000|400/200/100|22.78/23.78/27.61|2448/654/213|
|waifu2x-caffe-cui|4000x4000|8000x8000|400/200/100|18.45/21.85/31.82|3325/1652/1236|

upconv_7_anime_style_art_rgb

||Image Size|Target Size|Block Size|Total Time(s)|GPU Memory(MB)|
|---|---|---|---|---|---|
|waifu2x-ncnn-vulkan|200x200|400x400|400/200/100|0.74/0.75/0.72|482/482/142|
|waifu2x-caffe-cui|200x200|400x400|400/200/100|2.04/1.99/1.99|995/546/459|
|waifu2x-ncnn-vulkan|400x400|800x800|400/200/100|0.95/0.83/0.81|1762/482/142|
|waifu2x-caffe-cui|400x400|800x800|400/200/100|2.08/2.12/2.11|995/546/459|
|waifu2x-ncnn-vulkan|1000x1000|2000x2000|400/200/100|1.52/1.41/1.44|1778/482/142|
|waifu2x-caffe-cui|1000x1000|2000x2000|400/200/100|2.72/2.60/2.68|1015/570/459|
|waifu2x-ncnn-vulkan|2000x2000|4000x4000|400/200/100|3.45/3.42/3.63|1778/482/142|
|waifu2x-caffe-cui|2000x2000|4000x4000|400/200/100|3.90/4.01/4.35|1015/521/462|
|waifu2x-ncnn-vulkan|4000x4000|8000x8000|400/200/100|11.16/11.29/12.07|1796/498/158|
|waifu2x-caffe-cui|4000x4000|8000x8000|400/200/100|9.24/9.81/11.16|995/546/436|

Sample Images

Original Image

Upscale 2x with ImageMagick

convert origin.jpg -resize 200% output.png

Upscale 2x with ImageMagick Lanczo4 Filter

convert origin.jpg -filter Lanczos -resize 200% output.png

Upscale 2x with waifu2x noise=2 scale=2

waifu2x-ncnn-vulkan.exe -i origin.jpg -o output.png -n 2 -s 2

Original waifu2x Project

https://github.com/nagadomi/waifu2x
https://github.com/lltcggie/waifu2x-caffe

Other Open-Source Code Used

https://github.com/Tencent/ncnn for fast neural network inference on ALL PLATFORMS
https://github.com/webmproject/libwebp for encoding and decoding Webp images on ALL PLATFORMS
https://github.com/libjpeg-turbo/libjpeg-turbo for encoding and decoding JPEG images on ALL PLATFORMS
https://github.com/pnggroup/libpng for encoding and decoding PNG images on ALL PLATFORMS
https://github.com/zlib-ng/zlib-ng for encoding and decoding PNG images on ALL PLATFORMS
https://github.com/tronkko/dirent for listing files in directory on Windows

README