{"schema":"record/v1","id":"art_01M5P4E0XJTW3G8SZQGM32CK1J","type":"article","revision":1,"etag":"\"r1.s0\"","title":"For the open LivePortrait method, how should the driving video be prepared, and can I use it commercially?","summary":"Problem: reuse a filmed face performance to animate a still portrait or video locally. Conditions: KwaiVGI/LivePortrait repo, inference.py with -s (source) and -d (driving) arguments. Method: crop the driving video to 1:1 (for example 512x512) or pass --flag_crop_driving_video; frame the head, minimise shoulder movement, and start on a frontal face with neutral expression. Transfer is facial and head motion only; it is a portrait animator, not a body or voice transfer, and it takes no audio input in the README's usage. Rights: the code is MIT licensed (Kuaishou), but the LICENSE file adds that InsightFace models are non-commercial research only and commercial users should replace InsightFace detection models. The README ethics note says synthesized results contain artifacts that may help detect deepfakes and disclaims legal responsibility. Failure modes: non-frontal starts and shoulder motion are warned against. Limitations: I did not run the code. Version/date: README fetched at st...","status":"active","body":{"text":"Problem: reuse a filmed face performance to animate a still portrait or video locally. Conditions: KwaiVGI/LivePortrait repo, inference.py with -s (source) and -d (driving) arguments. Method: crop the driving video to 1:1 (for example 512x512) or pass --flag_crop_driving_video; frame the head, minimise shoulder movement, and start on a frontal face with neutral expression. Transfer is facial and head motion only; it is a portrait animator, not a body or voice transfer, and it takes no audio input in the README's usage. Rights: the code is MIT licensed (Kuaishou), but the LICENSE file adds that InsightFace models are non-commercial research only and commercial users should replace InsightFace detection models. The README ethics note says synthesized results contain artifacts that may help detect deepfakes and disclaims legal responsibility. Failure modes: non-frontal starts and shoulder motion are warned against. Limitations: I did not run the code. Version/date: README fetched at stamp.\n\nCurator qualifications: All cited documentation excerpts located on the live pages by curator GET; no video sources.\n\nLimitations: README read raw; no execution, no quality testing. Whether swapping InsightFace detection is sufficient for a commercial pipeline is the maintainers' claim, not legal advice. 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