Stars and mentions
Last 30 days, Oct 4 – Nov 2
Package downloads
Top repositories
xinntao’s repositories ranked by pull request authors, as on trending.
Contributes to
Repositories outside xinntao’s account where xinntao opened or reviewed pull requests in the past 365 days.
Who noticed xinntao
Everyone who starred or forked xinntao’s repositories since the archive began in 2011.
Notable accounts
Ordered by the stars their own repositories have received.
Biggest fans
Accounts that starred the most of these repositories.
Breakout weeks
Each repository’s best week of new stars, with the release published around it.
- Gold
- 01st place finishes
- Silver
- 12nd place finishes
- Bronze
- 03rd place finishes
- Awarded repositories
- 1Owned by xinntao now
Repositories
Ordered by gold, then silver, then bronze.
- Real-ESRGANBest: 2nd by stars, 191 stars010
Every award
Top-three finishes of these repositories in completed trending days and weeks, newest first.
A repository earns an award for finishing first, second or third in a completed trending day or week, ranked by new stars, new forks or pull request authors. Awards follow a repository through renames and transfers and count toward its current owner. Weeks run Monday to Sunday, UTC.
Mentions
பழைய blurry video-களை 4K ஆக்கலாம்.. Real-ESRGAN. Open source, free. Python வேண்டாம்னா exe-ஏ இருக்கு. உன் பழைய clip-அ try பண்ணுவியா ? xinntao/Real-ESRGAN Instagram-லும் பின்தொடருங்கள்: instagram.com
Upscayl: Enlarge Photos with AI, Locally | GitHub Repos You Should Know #014 A tiny photo, enlarged four times in each dimension with Upscayl. Repo: upscayl/upscayl Classification: Worth Knowing We tested the local engine shipped with Upscayl 2.15.0 using Upscayl Standard. The selected model files are byte-identical to Real-ESRGAN’s original realesrgan-x4plus model in its v0.2.5.0 Windows distribution. These are controlled tests: we reduced the reference photos to 160 pixels wide (cat) and 200 pixels wide (rocket), then generated actual 640- and 800-pixel-wide outputs. All before/after crops use matching framing and display size. The ordinary enlargement baseline uses bicubic interpolation. No manually retouched or fake after-images. The comparison wipes are editorial animation, not a recording of processing speed. The demonstration uses the real bundled command-line engine, not a recording of the desktop interface. The model argument shown is an excerpt, not a complete command. Upscayl needs a compatible Vulkan GPU. Our local tests ran with the existing RTX 4090 available. AI estimates details; a sharper output is not guaranteed to be more accurate or to restore the original detail. Licences: Upscayl and its backend AGPL-3.0; selected original Real-ESRGAN model BSD-3-Clause. Other models may have different terms. github.com/upscayl/upscayl/blob/v2.15.0/Real-ESRG… github.com/xinntao/Real-ESRGAN/releases/tag/v0.2.… Photo credits: Chelsea the cat by Stefan van der Walt, CC0; DSCOVR/Falcon 9 photo by SpaceX, public domain. Both distributed through scikit-image. No endorsement implied. scikit-image.org flickr.com What would you upscale? #GitHub #OpenSource #Upscayl
@hAru_mAki_ch 768出力は[Real-ESRGAN](xinntao/Real-ESRGAN)で2倍に拡大できます。元動画と同じフレームで細部を見比べて、追加CUも記録すると、画質改善にどこまでコストをかけるか判断できます。
this is the upscaling algorithm that Claude found: xinntao/real-esrgan