Wjs Editing Multicam
/install wjs-editing-multicam
wjs-editing-multicam
Combine N synced camera angles into a single rendered MP4. Decisions are audio-energy-driven only — the cam with the loudest mic each second wins. Output is hard cuts (or hard cuts plus a corner PiP).
What this skill IS — and IS NOT
| Is | Is not |
|---|---|
| Audio-energy-driven cam switching | Face / framing detection (no face_recognition, no MediaPipe) |
| Single-source audio (one cam's mic) | Multi-mic mix / per-speaker gating |
| Hard cuts, with optional PiP inset | Crossfades / opacity transitions / sliding animations |
ffmpeg concat + overlay filter renders |
HyperFrames composition / \x3Chf-clip> |
| Coverage-aware (won't pick a cam outside its sidecar window) | Frame-accurate beat alignment / VAD-edge cuts |
If you need face tracking, fade transitions, captions, or HyperFrames composition, use the hyperframes skill on top of this skill's MP4 output.
REQUIRED INPUT
Original camera files (untouched) plus their .sync.json sidecars next to them. If sources aren't synced yet, run wjs-syncing-multicam first to write the sidecars. Missing sidecar = cam assumed at delta=0, full coverage.
autoedit.py reads each sidecar for delta_seconds + overlap_in_reference, lifts the cam's audio envelope into the reference timeline, and only schedules a cam during its coverage window. render_cuts.py / render_pip.py apply ffmpeg -itsoffset per input using the EDL's deltas[] array.
When NOT to use
- One source — nothing to switch between; use video-segmentation.
- Polished NLE timeline already exists — don't fight the editor.
- Want fade transitions / overlay captions / brand title cards — run this skill first to get the cut-down MP4, then feed it into wjs-overlaying-video or hyperframes.
Pipeline
- Read each input's sidecar → list of
delta_seconds[k]+overlap_in_reference[k]. - Extract per-cam mono PCM @ 16 kHz from the original file.
- Log-RMS envelope at 1 Hz frame rate (per-second).
- Lift each envelope into reference timeline by indexing at
t_ref - delta_k; uncovered seconds become-infso they're never picked. - Audio source = the cam with the largest envelope spread (90th − 10th percentile over its covered seconds), with a small bonus for coverage fraction.
- Score per second:
cam[k] - mean(other covered cams). Highest score = best active-speaker candidate. - Editor decides EDL — two modes:
rotation(default): random dwell in [min_dwell=8,max_dwell=15] s, pick best-scoring covered cam (≠ current) at each cut.greedy: hysteresis — hold current unless another cam's lookahead-window score beats it by--switch-threshold. Floormin_dwell=4, ceilingmax_dwell=18. Both force-switch if the active cam exits its coverage window mid-shot.
- Emit EDL JSON.
EDL schema (edl.json)
{
"_about": "EDL produced by wjs-editing-multicam/autoedit.py. Times in reference timeline. Render scripts apply ffmpeg -itsoffset deltas[k] per input.",
"_help": {
"inputs": "Original media paths, in cam-index order (cam 0, cam 1, ...).",
"deltas": "Per-cam delta_seconds from each sidecar. Render uses ffmpeg -itsoffset deltas[k].",
"duration_sec": "Output duration in reference timeline.",
"audio_source": "Cam index whose audio track becomes the master. Single source — not a mix.",
"coverage": "[start, end] per cam in reference timeline.",
"edl": "List of {cam, start, end} segments. Times are reference-timeline seconds."
},
"inputs": ["cam_a.MOV", "cam_b.MOV"],
"deltas": [0.0, 12.345],
"duration_sec": 4512,
"audio_source": 0,
"coverage": [[0.0, 4512.0], [12.345, 4499.835]],
"edl": [{"cam": 0, "start": 0, "end": 13}, {"cam": 1, "start": 13, "end": 28}, ...]
}
autoedit.py writes _about + _help directly into the file so opening the JSON in any editor explains itself.
Render
| Script | What it does |
|---|---|
scripts/render_cuts.py |
Hard cuts only. concat filter graph over per-segment trim+scale+pad. Audio = audio_source cam, trimmed to first EDL row's start. |
scripts/render_pip.py |
Hard cuts + corner picture-in-picture overlay. Main cam = EDL row's cam; PiP cam picked round-robin (or via per-row pip field). PiP is scaled to --pip-width (default 480 px), placed in a configurable corner with optional white border. No fade / no opacity — solid block on/off. |
Both apply -itsoffset deltas[k] per input.
Brainstorm before running
Three real knobs to confirm with the user:
- Pacing —
--mode rotation(varied dwell, easier on the ear) vs--mode greedy(energy-following, snappier). - PiP — yes / no. If yes, which corner + width?
- Min cut length —
--min-dwellfloor. 8 s default for rotation is conservative; talking-heads can go to 4.
audio_source is auto-picked; override with --audio-source \x3Ccam-index> if the auto-pick sounds wrong on a 30 s listen.
File layout
working_dir/
cam_a.MOV # ORIGINAL, untouched
cam_a.MOV.sync.json # from wjs-syncing-multicam
cam_b.MOV # ORIGINAL, untouched
cam_b.MOV.sync.json
edl.json # from autoedit.py
multicam_render.mp4 # from render_cuts.py OR render_pip.py
Common pitfalls
- Trusting
audio_sourcewithout listening. Spread + coverage is a proxy. Always sample a 30 s clip before committing — a high-spread track can still be clipped / distorted. - Running
autoedit.pyon the full 75 min before tuning. Run on a 2-min slice first (ffmpeg -ss A -t 120an extract per cam), listen, adjust--min-dwell/--mode, then commit to full length. - Expecting face-driven framing. This skill doesn't see the video — only the audio. If one cam is well-framed but quiet, the editor won't favor it. Use
--audio-source+ per-segmentpipoverrides as the manual escape hatch. - Re-rendering when sync was wrong. EDL bakes in
deltas[]at autoedit time. If you fix the sidecars later, re-runautoedit.pyto regenerate the EDL before re-rendering.
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install wjs-editing-multicam - 安装完成后,直接呼叫该 Skill 的名称或使用
/wjs-editing-multicam触发 - 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
Wjs Editing Multicam 是什么?
Use when the user has 2+ recordings of the same event (each with a `.sync.json` sidecar from wjs-syncing-multicam) and wants them combined into a single MP4... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 67 次。
如何安装 Wjs Editing Multicam?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install wjs-editing-multicam」即可一键安装,无需额外配置。
Wjs Editing Multicam 是免费的吗?
是的,Wjs Editing Multicam 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
Wjs Editing Multicam 支持哪些平台?
Wjs Editing Multicam 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。
谁开发了 Wjs Editing Multicam?
由 Jian Shuo Wang(@jianshuo)开发并维护,当前版本 v0.1.0。