So with my setup, I'm sure that I have more than enough to meet the recommended specs to run this program, but. Mac Operating SystemCatalina 10.15 and higherĭedicated GPU from 2015 onward Video RAM2GB I have also tried just simply upscaling to 4K, aswell as simply upscaling using de-interlace to HD 1920x 1080ģ.2 GHz 6-Core Intel Core i7 (which is AVX2 instruction set extension)Ĭhipset Model: AMD Radeon RX 5700 XT eGpu I have tried a range of models and filters in Topaz and am trying to output to Prores 422HQ. The settings for Topaz are set to using the eGpu for processing and the file paths set to an empty 1TB ex SSD. <=1440p needs 6-8 GB of RAM, 4K wants at least 10 GB.Hi there everyone, I hope that you're well and not going around in circles and pulling your hair out like I have been doing for the past week!Īfter a great amount of watching and reading 'VERSUS' info on the whole gammut of AI video upscalers, I decided upon using Topaz AI and I can see that it makes an incredible amount of difference to my old footage in the preview, but when I try to export anything, I either get out of memory messages or more frequently now, it crashes and shuts down my whole system. Most likely you don't have enough RAM on the video cards. TensorRT: optimization pass gives an error.Check with double-clicking the "Vapoursynth Filter", if everything is OK then the properties window must open. TensorRT: it still doesn't work even with Vapoursynth filter! Ensure you modified the environment variables, restart MPC-HC.RIFE profile won't select by default: ensure you switched video filter to Vapoursynth Filter!.Ensure you switched video filter to Vapoursynth Filter! DirectShow player (MPC-HC, etc) using Avisynth Filter: needs Avisynth 3.7.2 very slow initialization (10+ secs), be patient! TensorRT is not supported.Īfter playback started, switch to the RIFE video profile if needed - it can be in the Other profiles sub-menu depending on profile conditions currently set.Īdvanced usage with profile conditions: for example, you may want to use RIFE for 1 doesn't work for Apple M1.DirectShow player (MPC-HC, etc) using Vapoursynth Filter: needs environment variables to be set: SVP menu -> Utilities -> Set environment variables for Vapoursynth.If everything is fine you'll see a new RIFE AI engine video profile.Īlternatively if you own a high-end video card you may try it in a real-time playback.usr/local/bin/brew install vulkan-loader molten-vk opt/homebrew/bin/brew install vulkan-loader molten-vk Everything is already installed EXCEPT Vulkan loader in Homebrew:.Don't close it! Wait! Installation - macOS Note: when it runs the optimization pass, it's OK for the command-line window to stay for 4-5 or even 8 mins. run MPC-HC, View -> Options -> External filters, uncheck "Avisynth Filter", add "Vapoursynth Filter", check it and set to "Prefer".SVP menu -> Utilities -> Set environment variables for Vapoursynth -> Continue.Only for Vapoursynth, so you have to switch to Vapoursynth Filter in MPC-HC (or any other DirectShow video player) first: To give it a try install an additional package called "TensorRT" via SVP menu -> Utilities -> Additional programs and features, then choose the TensorRT engine in the RIFE video profile. It can be up to 100% faster than ncnn/Vulkan implementation, but there're a few cons, for example a very long optimization passes. TensorRT is a neural network engine heavily optimized for NVidia GPUs. You'll notice a new video profile called RIFE AI engine added.programs and features, called RIFE AI interpolation engine, restart SVP Install an additional package via SVP menu -> Utilities -> Add.Required GPU for a real-time playback (estimated, also works on AMD and Apple Mx): very demanding (comparing to SVP's interpolation method), real-time playback requires a decent video card. ![]() ![]() very high quality of the intermediate frames.Avisynth filter based on RIFE/ncnn/Vulkan.Vapoursynth filter based on RIFE/ncnn/Vulkan.SVP can use RIFE engine in both transcoding and real-time playback modes. ![]() RIFE is a Real-time Intermediate Flow Estimation algorithm based on a neural network named IFNet, that can directly estimate the intermediate flows from images.
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