fill-vertical

name: fill-vertical description: Reframe a horizontal (16:9) clip to 9:16 (1080x1920) by punching in to FILL the frame — never letterbox, no blur bars. Detects scene cuts and computes ONE static crop box per shot. Clusters face signatures across all shots to find the dominant speaker (storyteller); on multi-face shots it picks the speaker by lip-activity biased toward that identity; on no-face shots it crops toward the OpenCV-saliency centroid. A non-speaking reaction/listener shot is framed LOOSER so the short never dwells hero-framed on the wrong person. Faces are framed ~45% of frame height with the eyeline on the upper third, capped at ~2x upscale. Replaces fit-vertical in the canonical chain.

fill-vertical

Punch-in 9:16 reframe. Fills 1080x1920 on every shot — the "content" look, not the blurred-letterbox "webinar" look. Runs after tighten-pace, before chunk-captions/burn-subtitles.

Usage

.claude/skills/fill-vertical/fill-vertical.sh <input> <out> \
  [target=1080x1920] [face_frac=0.45] [max_zoom=2.0] [scene_thresh=0.4] [samples=5]

• input — cut/trimmed/tightened clip (any aspect; designed for 16:9).
• out — written 1080x1920 mp4, audio stream-copied, duration unchanged, +faststart.

Contract

• In: one video file.
• Out: one 1080x1920 mp4. Audio copied from input. Duration preserved. Side artifact <out>.fillplan.json records per-shot crop boxes.
• Idempotent: if out is newer than input, exits as a cache hit.

How it works

1. ffprobe for source w/h/fps/duration.
2. Scene-cut detect via ffmpeg select=gt(scene,thresh) on a downscaled decode → shot list.
3. Per shot: sample samples frames, run MediaPipe FaceLandmarker (full lip mesh).
   • Link faces across frames by center proximity → tracks.
   • Speaker = track with max mouth-openness variance. No measurable lip motion → biggest + most-central face. Single face → trivial.
   • Crop box: chosen face ~`face_fracof frame height, eyeline on the upper third, centered on the face, clamped to source bounds, capped atmax_zoom`.
   • No face → OpenCV StaticSaliencyFineGrained; crop toward the saliency centroid, cover-zoom only (no artificial upscale).
4. Render each shot (cut → crop → scale → 1080x1920, video only), concat-demuxer join, stream-copy the original audio over the whole clip. Encodes via _lib/encode.sh (respects its VideoToolbox/thread caps — the CPU-brick fix from shorts-xv5).

Tunables

Deps

mediapipe, opencv-contrib-python, numpy (python3). FaceLandmarker model bundled at models/face_landmarker.task.

Out of scope

Continuous/tracking pan, split-screen, audio diarization, blur bars/letterbox, slide-specific handling. Other skills own segment selection, captions, titles, CTA, music.