← 返回
未分类

Wjs Editing Multicam

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...
用于用户有2个或多个同一事件的录像(每个都带有来自wjs-syncing-multicam的.sync.json侧车文件),想要合并成一个MP4文件...
jianshuo
未分类 clawhub v0.1.0 1 版本 100000 Key: 无需
★ 0
Stars
📥 255
下载
💾 0
安装
1
版本
#latest

概述

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

IsIs not
------
Audio-energy-driven cam switchingFace / 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 insetCrossfades / opacity transitions / sliding animations
ffmpeg concat + overlay filter rendersHyperFrames composition /
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

  1. Read each input's sidecar → list of delta_seconds[k] + overlap_in_reference[k].
  2. Extract per-cam mono PCM @ 16 kHz from the original file.
  3. Log-RMS envelope at 1 Hz frame rate (per-second).
  4. Lift each envelope into reference timeline by indexing at t_ref - delta_k; uncovered seconds become -inf so they're never picked.
  5. Audio source = the cam with the largest envelope spread (90th − 10th percentile over its covered seconds), with a small bonus for coverage fraction.
  6. Score per second: cam[k] - mean(other covered cams). Highest score = best active-speaker candidate.
  7. 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. Floor min_dwell=4, ceiling max_dwell=18.

Both force-switch if the active cam exits its coverage window mid-shot.

  1. 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

ScriptWhat it does
------
scripts/render_cuts.pyHard 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.pyHard 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-dwell floor. 8 s default for rotation is conservative; talking-heads can go to 4.

audio_source is auto-picked; override with --audio-source 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_source without 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.py on the full 75 min before tuning. Run on a 2-min slice first (ffmpeg -ss A -t 120 an 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-segment pip overrides 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-run autoedit.py to regenerate the EDL before re-rendering.

版本历史

共 1 个版本

  • v0.1.0 当前
    2026-05-21 14:49 安全 安全

安全检测

腾讯云安全 (Keen)

安全,无风险
查看报告

腾讯云安全 (Sanbu)

安全,无风险
查看报告

🔗 相关推荐

Wjs Dubbing Video

jianshuo
当用户有视频和目标语言SRT字幕文件,需要视频实际说出该语言时使用——生成时间对齐的TTS语音配音。路由依据...
★ 0 📥 272

Wjs Auditing Project

jianshuo
当用户要求审计项目问题、‘修复错误’、‘看看项目出了什么问题’、‘为什么用户的需求还没上线’、‘为什么没提交App Store’、‘为什么没新build’,或希望了解项目整体健康时使用。
★ 0 📥 272

Wjs Translating Subtitles

jianshuo
用于将一种语言的SRT(或转录文本)翻译成另一种语言,并依据标点重新分段,使字幕提示在……结束。
★ 0 📥 268