Gfpgan

App in the BluixApps catalog

What it is

GFPGAN is Tencent ARC's practical face restoration algorithm — restores old, blurry, or low-resolution face photos using generative adversarial network priors. Trained on millions of high-quality face images, GFPGAN handles faces from baby to elderly with consistent quality.

The industry standard for AI face recovery — the "before/after" you've seen in viral Reddit posts comes from GFPGAN.

What it's for

  • Old photo restoration — family albums, historical archives
  • Blurry photo enhancement — social media, scanned docs
  • Low-resolution profile pictures — to high-res
  • Document face cleanup — passport photos, ID cards
  • AI-generated image fix — repair SD/Flux face artifacts

Who it's for

  • Photographers restoring old client photos
  • Family archivists digitizing/enhancing old albums
  • Document workflow teams cleaning passport/ID scans
  • AI art creators post-processing SD face artifacts
  • Marketing teams enhancing low-res legacy images

Why teams pick GFPGAN over alternatives

  • Apache 2.0 — fully open
  • Best face-specific restoration in the open-source space
  • Robust to severe degradation (blur, noise, JPEG artifacts)
  • Multiple version variants for different aesthetics
  • Integrates with Real-ESRGAN for full-image restoration
  • Used in A1111 / ComfyUI natively
  • Tencent ARC backing

Integrations

  • Gradio web UI (BluixApps custom)
  • CLI mode for batch processing
  • A1111 Extras — built-in
  • ComfyUI nodes — restoration node pack
  • Pair with: Real-ESRGAN (Real-ESRGAN for background + GFPGAN for faces = best total restoration)
  • Pair with: SD/Flux generation (ADetailer-like post-process)

Notable users & community

  • 37k+ GitHub stars
  • Tencent ARC research backing
  • Standard in commercial photo-AI products
  • Featured in viral restoration before/after posts
  • Multiple language tutorials + courses available

Tips & operations

  • Versions:
    • v1.3: gentler, preserves original character
    • v1.4: aggressive modern look (recommended for most uses)
    • v1.2 / v1.0: legacy
  • Upscale factor: 1-4× (combined with face restore)
  • VRAM: 4 GB minimum
  • Speed: 1-3 sec per photo on RTX 4090
  • Best inputs: degraded photos (blur, low-res, JPEG artifacts) — that's what GFPGAN learned to fix
  • Combine with Real-ESRGAN: --bg_upsampler realesrgan for full image enhancement
  • Batch CLI: process whole folders for archive work

What we ship in BluixApps

  • Cloned TencentARC/GFPGAN repo
  • pytorch CUDA 12.4 base
  • Custom Gradio UI with version + scale selectors
  • Persistent volumes: repo, weights (~700 MB), input, output
  • Port 7876 mapped
  • Install report at /root/bluixapps/gfpgan.txt
  • Version selection guide
  • CLI batch examples
  • Use case examples (photo archive, document scanning, AI art fix)
  • Pairing suggestions (Real-ESRGAN combo for best results)
  • GPU pre-flight check via bluixapps_ensure_nvidia_runtime
  • Backup hook covers weights + outputs
Read this app's deep dive on bluix.app ↗

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Same catalog. Scaling tenant isolation, white-label and support tier.

TierTenantsCatalogSupportWhite-labelMonthly
Stacks119 curated stacksStandard$19/moDetailDeploy
Starter10Full catalogStandard+$15–25/mo$49/moDetailDeploy
Pro25Full catalogPriority bugfix+$15–25/mo$149/moDetailDeploy
Growth100Full catalogPriority bugfix+$15–25/mo$349/moDetailDeploy
Scale500Full catalog7-day window+$15–25/mo$799/moDetailDeploy
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