k4yt3x/video2x
A machine learning-based video super resolution and frame interpolation framework. Est. Hack the Valley II, 2018.
Build with Backblaze B2
SDKs, agent skills, IDE extensions, and reference pipelines from Backblaze Labs. All open source.
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Where it stands
Rank, growth pace and release cadence relative to everything GStars tracks.
Ranks #315 of 3,103 repositories GStars tracks this week (top 10%).
No releases in the last 90 days; the most recent was 637 days ago, with 24 contributors on GitHub.
Gained 70% more stars in the last 90 days than in the 90 days before.
Use Cases & Benefits
- Provides a machine learning-based framework for video super resolution and frame interpolation using C++.
- Delivers faster, more efficient, and higher quality video upscaling with cross-platform support and Vulkan acceleration.
- Use for enhancing low-resolution anime videos to 4K quality with Anime4K and Real-ESRGAN models.
- Use for creating smooth slow-motion videos by interpolating frames with RIFE neural network models.
- Use for integrating video upscaling and interpolation into cross-platform desktop applications with a user-friendly GUI.
Should you depend on it?
License terms, project hygiene and risks, from GitHub metadata and GStars' snapshots.
License
AGPL 3.0
Network copyleft: like the GPL, and also triggered by offering the software over a network.
Community files
- README: present
- Contributing guide: present
- Code of conduct: present
Watch-outs
- AGPL-style copyleft also applies when the software is offered over a network.
- No commits in the last six months (last push Mar 2026).
General guidance from repository metadata, not legal advice. How we score
From the README
Your system must meet the minimum hardware requirements below to run Video2X.
Video2X packages are available for the Linux distros listed below. A universal AppImage is also available for other distros. If you'd like to build it from source code, refer to the PKGBUILD file for a general overview of the required dependencies and commands.
Daily snapshots
Stars gained per day, and how forks and open issues moved, from GStars' daily snapshots
Forks
2.0K+173
Open issues
139+17
Compared with peers in Machine Learning
Fastest-growing repositories GStars tracks in this cohort for the week of Oct 18, by 7-day star growth
| Repository | Stars | +7d | Health | Last release |
|---|---|---|---|---|
| Comfy-Org/ComfyUI | 142.4K | +4.5K | 60 | 4 days ago |
| vllm-project/vllm | 95.3K | +1.4K | 75 | 5 days ago |
| pytorch/pytorch | 105.0K | +215 | 64 | 23 days ago |
| netdata/netdata | 81.1K | +0 | 75 | 12 days ago |
| k4yt3x/video2x | 22.4K | +0 | 75 | 637 days ago |
| kserve/kserve | 6.1K | +0 | 75 | 25 days ago |
| Category median | 95.3K | +215 | 75 | — |
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