Codeformer

App in the BluixApps catalog

What it is

CodeFormer is robust blind face restoration via codebook lookup (NeurIPS 2022) — more aggressive recovery than GFPGAN, designed for severely degraded faces. Handles AI-generated artifacts, very old photos, and other tough cases that GFPGAN struggles with.

The alternative to GFPGAN when GFPGAN isn't enough — pick by photo, try both.

What it's for

  • Severely degraded face restoration — beyond GFPGAN capability
  • Color photo restoration from B&W
  • AI-generated image face fix — SD/Flux face artifact compensation
  • Document face cleanup — passport, ID photos
  • Historical photo restoration

Who it's for

  • Photo restoration professionals (commercial / archival)
  • Document AI teams with degraded inputs
  • AI art studios fixing generation artifacts
  • Historical research teams restoring archival photos
  • Family genealogy services restoring old photos

Why teams pick CodeFormer over alternatives

  • S-Lab License — academic + commercial OK with attribution
  • More aggressive than GFPGAN — recovers from worse degradation
  • Fidelity slider — control quality vs identity preservation tradeoff
  • Robust to AI artifacts — fixes SD face issues better than GFPGAN
  • NeurIPS 2022 publication — peer-reviewed quality
  • Active maintenance + community

Integrations

  • Gradio web UI (BluixApps custom)
  • CLI mode for batch
  • A1111 Extras — alternative to GFPGAN
  • ComfyUI nodes — community wrappers
  • Pair with: Real-ESRGAN (background) + CodeFormer (faces)
  • Try both GFPGAN + CodeFormer: results vary per photo

Notable users & community

  • 17k+ GitHub stars
  • Nanyang Technological University (S-Lab) research backing
  • Featured in photo restoration tooling
  • Active community + tutorials
  • Multiple commercial restoration workflows use it

Tips & operations

  • Fidelity slider:
    • 0.0: best quality (may change identity)
    • 0.5: balanced
    • 0.7: balanced default (recommended)
    • 1.0: preserve identity (less restoration)
  • Background + face upsample: enable for full enhancement
  • VRAM: 4 GB minimum
  • Speed: 1-3 sec per photo
  • Best inputs: severely degraded (blur + noise + low-res combined)
  • CodeFormer vs GFPGAN:
    • CodeFormer: more aggressive, handles severe degradation
    • GFPGAN: gentler, preserves character better
    • Try both per photo, pick result
  • Production batch: CLI mode for archive workflows

What we ship in BluixApps

  • Cloned sczhou/CodeFormer repo
  • pytorch CUDA 12.4 base + opencv
  • Custom Gradio UI with fidelity slider + upsample toggles
  • Persistent volumes: repo, weights (~600 MB), input, output
  • Port 7877 mapped
  • Install report at /root/bluixapps/codeformer.txt
  • Fidelity guidance + use cases
  • CodeFormer vs GFPGAN comparison
  • CLI batch examples
  • Pairing suggestions (Real-ESRGAN combo for full restoration)
  • GPU pre-flight check via bluixapps_ensure_nvidia_runtime
  • Backup hook covers weights + outputs
Read this app's deep dive on bluix.app ↗

Get this app — pick a BluixApps plan

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
EnterpriseUnlimitedFull catalogPriority 7-dayBundled$1,499/moDetailDeploy

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