![]() ![]() Grab models for specific kinds of content here, or train your own:įor help, just post an issue, or ask in the Game Upscale or Animation Upscale Discords. Each guide contains detailed information about particular workflows you'll find useful. Also, keep in mind that Colab's CPU is very slow, and that sessions are limited to 12 hours, so use GPU accelerated filters wherever possible in scripts with heavy CPU filters, and write your processesed videos to Google Drive or Nextcloud. Learn our recommended workflows to improve the quality of your videos with Topaz Video AI. I highly recommend stabilizing ESRGAN output with a temporal filter, or using a dedicated video model from another repo. Ultra high precision of transition recognition, reaching 95+ accuracy in most videos without affecting smoothness. Process the whole video in a scratch cell.įor basics on VapourSynth and super resolution filters, see the wiki (and links to other guides) here:īrowse through VS plugins and scripts here, search for "vapoursynth" on github, or look through the "VapourSynthImports" folder and VapourSynth's imported plugins: More efficient, less memory used, and 20 times faster than DAIN.Generate the preview in the preview cell. JTime to read: 19 Minutes Download Video Enhance AI v2.3 Windows MacOS Release Notes Video Enhance AI v2.3 at a glance New Chronos AI model for frame rate conversion Easily adjust motion in your clips by slowing them down by up to 2000.Run the "Preview Options" cell to test the script.Run the cell with the example VapourSynth script, or load your own video and edit it.Run the "Check GPU" and "Run This at Startup" cells. ![]() ![]() Run ESRGAN or MXNet models, OpenCL and CUDA filters, and CPU filters on video frames simultaneously in VapourSynth scripts, or use VapourSynth filters to pre/post process videos for other ML Colab projects, and do it all in the cloud for free. A Google Colab notebook set up for both conventional and machine learning-based video processing. ![]()
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