The model removes background from any video with a person — we tested
with avatars because they were convenient, but anyone can bring a
talking-head clip, presenter footage, vlog, etc. Replace avatar-specific
filenames (avatar.mp4 / brandon.mp4) with neutral subject.mp4 (or
presenter.mp4 in the text-behind-subject example) and rephrase
copy that read as if avatars were the only use case.
Touches docs/guides/remove-background.mdx, hyperframes-media SKILL.md,
and hyperframes/patterns.md.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Skill (hyperframes-cli): three-pattern table (cutout-over-different-scene
vs over-its-own-source vs over-different-take) + the two non-obvious rules
(wrap video in non-timed div for opacity control, both videos data-start=0
for sync). Skill (hyperframes/patterns): worked text-behind-subject example.
Docs: --quality flag, compositing pitfalls section, quality preset table.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Adds `hyperframes remove-background` — a local-AI subcommand that mattes a
video or image with the u2net_human_seg ONNX model and emits a transparent
WebM (VP9-alpha), ProRes 4444 .mov, or RGBA PNG. Drops directly into any
composition's <video> tag — no green screen, no API keys, no upload.
Auto-picks the fastest available execution provider via onnxruntime-node:
CoreML on Apple Silicon, CUDA when HYPERFRAMES_CUDA=1, CPU otherwise.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
