InsightFace Social Video Face Swap
Budget: $10 – $30 USD
I already shoot and edit short-form social media videos; what I need now is a clean, reliable face-swap pipeline that drops a chosen face into those clips for pure entertainment. InsightFace is the preferred engine, but you’re welcome to weave in Wav2Lip or FaceFusion if that improves lip sync or realism.
Here’s the flow I have in mind: I hand you a finished video (with its original audio track) plus one or more source images or a source video of the face that should appear. Your script ingests the material, applies detection, alignment, swapping and blending with InsightFace, keeps the original timing and audio intact, then renders a final MP4 that’s ready for immediate upload to TikTok, Reels and Shorts.
Deliverables
• Well-commented Python script or notebook that performs the full swap end-to-end
• One-command setup guide (conda or Docker) listing every dependency and model checkpoint
• Example output using my supplied test clip so I can compare before/after quality
Acceptance criteria
• Face stays locked to head movement with no noticeable jitter or colour mismatch
• Lip movements remain synced to the existing audio throughout the clip
• Processing time per 60-second 1080p video stays within a reasonable window on a single RTX-class GPU
If something in the workflow can be optimised or automated further, feel free to suggest it—clarity and reproducibility are more important to me than chasing marginal gains.
Here’s the flow I have in mind: I hand you a finished video (with its original audio track) plus one or more source images or a source video of the face that should appear. Your script ingests the material, applies detection, alignment, swapping and blending with InsightFace, keeps the original timing and audio intact, then renders a final MP4 that’s ready for immediate upload to TikTok, Reels and Shorts.
Deliverables
• Well-commented Python script or notebook that performs the full swap end-to-end
• One-command setup guide (conda or Docker) listing every dependency and model checkpoint
• Example output using my supplied test clip so I can compare before/after quality
Acceptance criteria
• Face stays locked to head movement with no noticeable jitter or colour mismatch
• Lip movements remain synced to the existing audio throughout the clip
• Processing time per 60-second 1080p video stays within a reasonable window on a single RTX-class GPU
If something in the workflow can be optimised or automated further, feel free to suggest it—clarity and reproducibility are more important to me than chasing marginal gains.