render-narrated-ugc-wardrobe-stitch

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Assemble a narrated-UGC "stitch reply" ad from a config — a single spoken VO carries a verbatim testimonial while ~30 per-cut i2v clips (one creator across ~5 wardrobes in ~3 worlds, plus product B-roll) are each trimmed to their EDL window built from the VO's Whisper word boundaries and hard-concatenated via filter_complex concat (never the demuxer, which drops audio on a duration mismatch), the VO mixed over an optional sidechain-ducked instrumental bed (−20dB, 20 to 1) so the VO stays on top, karaoke-pop captions burned on every word throughout (VEED Whisper preset, re-spelled against the locked script), a landing-page scroll rendered as FFmpeg zoompan over a Playwright PNG (not i2v), and closed on the brand's real end-card PNG — never AI-rendered text. This is the FREE deterministic assembly stage (trim-to-EDL + filter_complex concat + VO and music mix + karaoke captions + landing-page zoompan + end-card append); the VO, creator, start-frames, and clips come from create-vo-elevenlabs / create-image-gpt-im

AI & Automation 1,055 stars 194 forks Updated 3 days ago MIT

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# render-narrated-ugc-wardrobe-stitch Assemble a **narrated-UGC "stitch reply"** ad from a config: a fast-cut vertical testimonial where a single spoken VO carries a verbatim ~13-sentence reversal-hook monologue over ONE creator across ~5 wardrobe changes in ~3 micro-worlds, interspersed with product B-roll (capsule macro, unboxing, a landing-page scroll), ~30 hard cuts on the VO cadence, closing on a brand end card. This capability is the **FREE, deterministic assembly** — trim-to-EDL, hard-concat, the VO+music mix, the karaoke-pop caption burn, the landing-page zoompan, and the end-card append. `scripts/config.example.json` is the worked example (Bioma "Do NOT buy Bioma Probiotics", ~37s 1080×1920 9:16, ~30 body cuts + a ~2s end card); `scripts/PIPELINE.md` maps every config block to its source step and `scripts/README.md` documents the free assembly. ## Run This is the **FREE, deterministic** assembly stage — it spends nothing. The paid inputs are separate capabilities — the spoken VO (`create-vo-elevenlabs`) Whisper-aligned so the WORD BOUNDARIES set the cut grid; one locked creator (`create-image-gpt-image-fal` anchor + ~5 wardrobe edits chained off the anchor) + 3 world wides + per-cut start-frames (`create-image-fal` product composites); and one Veo/Seedance i2v clip per cut (`create-video-fal`). Given the VO + `vo-final.words.json` + `edl.json` + one clip per cut + a Playwright landing-page PNG + the brand end-card PNG, `render-narrated-ugc-wardrobe-stitch` trims ...

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Author
gooseworks-ai
Repository
gooseworks-ai/goose-skills
Created
4 months ago
Last Updated
3 days ago
Language
Python
License
MIT

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