bilibili/ailab
None observed · 2026-08-28
Health v2 · maintenance only
23/100
- Activity 0
- Release rhythm 8
- Longevity 100
Flags: no_license
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 1944
- days_rel: n/a
- days_push: 1127
- n_releases_24m: 0
Adoption not part of the score
5881 stars · 554 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded
Bilibili's AI lab repository, best known for Real-CUGAN, a deep learning model for anime image super-resolution (upscaling). It provides pretrained models and tools to enhance low-resolution anime images and video frames.
Use cases
- upscale anime images without losing detail
- enhance low-resolution anime screenshots
- super-resolution for anime video frames
- denoise and restore old anime footage
- run anime upscaling models locally with python
When to choose
- you need high-quality anime-specific image upscaling
- you want pretrained super-resolution models tuned for anime art styles
- you are processing anime video frames in a python pipeline
When to avoid
- you need upscaling for photorealistic images rather than anime
- you need a maintained project with active releases and a clear license
- you want a GUI-based one-click upscaler
Facets
library · maturity maintenance
machine-learning image-processing deep-learning image-processing machine-learning python cross-platform super-resolution anime-upscaling real-cugan computer-vision anime gpu
1 source
- readme: https://github.com/bilibili/ailab · fetched 2026-08-28 · 45fe6ddca3b5
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| bilibili/ailab | main | 23 |
For agents
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem