# ajay-sainy/Wav2Lip-GFPGAN

High quality Lip sync

Repository: https://github.com/ajay-sainy/Wav2Lip-GFPGAN
Canonical: https://ross.abutalabs.com/products/wav2lip-gfpgan
Language: Python
License Family: other
Topics: deepfakes, gfpgan, wav2lip
Last push: 2024-07-30T05:00:39+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 1476, "days_push": 764, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1157, forks 279 (observed 2026-08-28T04:03:48.194402+00:00)

## What it is
A pipeline combining Wav2Lip lip-sync generation with GFPGAN face restoration to produce high-quality talking-head videos from an input video and audio track. It is provided as a Python project with a Google Colab notebook for easy use.

## Use cases
- generate a lip-synced video from audio and a face video
- improve blurry Wav2Lip output with face restoration
- create talking avatar videos for dubbing
- make deepfake-style talking head clips
- upscale and enhance faces in AI-generated videos

## When to choose
- you want one-click high-quality lip sync with face enhancement
- you want to run it in Colab without local GPU setup
- you need better visual quality than plain Wav2Lip

## When to avoid
- you need a maintained project with a license for commercial use
- you need real-time lip sync
- you want fine-grained control over each pipeline stage

## Facets
- artifact type: application
- maturity: maintenance
- function: video-processing, machine-learning, image-processing
- domain: deep-learning, artificial-intelligence, media
- platform: python, cross-platform
- tags: lip-sync, deepfakes, wav2lip, gfpgan, face-restoration, talking-head, video, gpu

## Member repositories
- ajay-sainy/Wav2Lip-GFPGAN (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:48.194402+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T06:32:01.182936+00:00, confidence not recorded.
  - readme: https://github.com/ajay-sainy/Wav2Lip-GFPGAN (fetched 2026-08-28T04:03:48.194402+00:00, sha 554037f26387)
- Data as of 2026-08-30T08:39:29.467469+00:00.