DENOISER 2 VS NEAT VIDEO ZIP
DENOISER 2 VS NEAT VIDEO HOW TO
Here are instructions on how to obtain this library and have waifu2x-caffe use it: Depending on the type of GPU used, images can be converted faster (exponentially faster in my experience)ĭue to licensing issues, waifu2x-caffe does not include this library by default.Compared to using your cpu or gpu (via CUDA) to upscale images, cuDNN offers the following advantages: This is a high-speed machine learning library that can only be used with NVIDIA GPUs. I highly recommend the NVIDIA CUDA Deep Neural Network (cuDNN) library when using waifu2x-caffe. Nodejs (Optional, only needed if you want to build from source).Windows executable of the waifu2x tool, waifu2x-caffe.Add the path to the ffmpeg executable into your PATH environment.
Visit this link to see my compiled list of screenshot comparisons. This is a very process intensive task, so expect to take quite a while (and enough disk space). Package the upscaled frames back into a new video, while copying over any audio, subtitle, and attachement streams (if applicable) from the source video.Many threads of this is run in parallel to split the work. Use waifu2x to upscale the frame to a higher resolution.Extract every frame in the source video.You can also grab the latest release here. This project is in github! You can find the page here. It's built to be flexible in terms of what options you pass into either the video encoder (ffmpeg) or the upscaler (waifu2x). It is based off of an existing python project using the same core principles to perform the video upscale, but with additional functionality to provide less verbouse output and hopefully more meaningful output. This tool upscales smaller resolution videoes to a higher resolution based on the Waifu2x art upscaler algorithm.