[teamai] Push 87 resource(s) from XingfenD

2026-09-10 16:10:45 +08:00
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+# Captions
+
+Before authoring: confirm the transcript came from the right Whisper model. CLI default `small.en` silently translates non-English audio — see [`../transcribe.md`](../transcribe.md) → "Language Rule" and [`transcript-handling.md`](transcript-handling.md) for the mandatory quality check.
+
+Analyze spoken content to determine caption style. If user specifies a style, use that. Otherwise, detect tone from the transcript.
+
+## Transcript Source
+
+```json
+[
+  { "id": "w0", "text": "Hello", "start": 0.0, "end": 0.5 },
+  { "id": "w1", "text": "world.", "start": 0.6, "end": 1.2 }
+]
+```
+
+`id` (`w0`, `w1`, …) is the stable reference for per-word overrides and is added by `hyperframes transcribe`. It's optional for backwards compatibility with hand-authored transcripts. See [`../transcribe.md`](../transcribe.md) → "Output Shape" for how this is produced, and [`transcript-handling.md`](transcript-handling.md) for cleanup before consumption.
+
+## Style Detection (When No Style Specified)
+
+Read the full transcript before choosing. Four dimensions:
+
+**1. Visual feel** — corporate→clean; energetic→bold; storytelling→elegant; technical→precise; social→playful.
+
+**2. Color palette** — dark+bright for energy; muted for professional; high contrast for clarity; one accent color.
+
+**3. Font mood** — heavy/condensed for impact; clean sans for modern; rounded for friendly; serif for elegance.
+
+**4. Animation character** — scale-pop for punchy; gentle fade for calm; word-by-word for emphasis; typewriter for technical.
+
+## Per-Word Styling
+
+Scan for words deserving distinct treatment:
+
+- **Brand/product names** — larger size, unique color
+- **ALL CAPS** — scale boost, flash, accent color
+- **Numbers/statistics** — bold weight, accent color
+- **Emotional keywords** — exaggerated animation (overshoot, bounce)
+- **Call-to-action** — highlight, underline, color pop
+- **Marker highlight** — for beyond-color emphasis (highlight sweep, circle, burst, scribble, sketchout), see `hyperframes-animation/rules/css-marker-patterns.md`.
+
+## Script-to-Style Mapping
+
+| Tone         | Font mood                | Animation                          | Color                       | Size    |
+| ------------ | ------------------------ | ---------------------------------- | --------------------------- | ------- |
+| Hype/launch  | Heavy condensed, 800-900 | Scale-pop, back.out(1.7), 0.1-0.2s | Bright on dark              | 72-96px |
+| Corporate    | Clean sans, 600-700      | Fade+slide, power3.out, 0.3s       | White/neutral, muted accent | 56-72px |
+| Tutorial     | Mono/clean sans, 500-600 | Typewriter/fade, 0.4-0.5s          | High contrast, minimal      | 48-64px |
+| Storytelling | Serif/elegant, 400-500   | Slow fade, power2.out, 0.5-0.6s    | Warm muted tones            | 44-56px |
+| Social       | Rounded sans, 700-800    | Bounce, elastic.out, word-by-word  | Playful, colored pills      | 56-80px |
+
+## Word Grouping
+
+- **High energy:** 2-3 words. Quick turnover.
+- **Conversational:** 3-5 words. Natural phrases.
+- **Measured/calm:** 4-6 words. Longer groups.
+
+Break on sentence boundaries, 150ms+ pauses, or max word count.
+
+## Positioning
+
+- **Landscape (1920x1080):** Bottom 80-120px, centered
+- **Portrait (1080x1920):** Lower middle ~600-700px from bottom, centered
+- Never cover the subject's face
+- `position: absolute` — never relative
+- One caption group visible at a time
+
+## Text Overflow Prevention
+
+Use `window.__hyperframes.fitTextFontSize()`:
+
+```js
+var result = window.__hyperframes.fitTextFontSize(group.text.toUpperCase(), {
+  fontFamily: "Outfit",
+  fontWeight: 900,
+  maxWidth: 1600,
+});
+el.style.fontSize = result.fontSize + "px";
+```
+
+Options: `maxWidth` (1600 landscape, 900 portrait), `baseFontSize` (78), `minFontSize` (42), `fontWeight`, `fontFamily`, `step` (2).
+
+CSS safety nets: `max-width` on container, `overflow: visible` (**not** `hidden` — hidden clips scaled emphasis words and glow effects), `position: absolute`, explicit `height`. When per-word styling uses `scale > 1.0`, compute `maxWidth = safeWidth / maxScale` to leave headroom.
+
+**Container pattern:** Full-width absolute container, centered. Do **not** use `left: 50%; transform: translateX(-50%)` — causes clipping at composition edges.
+
+## Caption Exit Guarantee
+
+Every group **must** have a hard kill after exit animation:
+
+```js
+tl.to(groupEl, { opacity: 0, scale: 0.95, duration: 0.12, ease: "power2.in" }, group.end - 0.12);
+// `tl.set` is an instant flip, not a tween — safe to set `visibility` here (core's "no animating
+// visibility" rule applies to tweens, which can't smoothly interpolate non-numeric values anyway).
+tl.set(groupEl, { opacity: 0, visibility: "hidden" }, group.end);
+```
+
+Self-lint after building timeline — place **before** `window.__timelines[id] = tl` so it runs at composition init:
+
+```js
+GROUPS.forEach(function (group, gi) {
+  var el = document.getElementById("cg-" + gi);
+  if (!el) return;
+  tl.seek(group.end + 0.01);
+  var computed = window.getComputedStyle(el);
+  if (computed.opacity !== "0" && computed.visibility !== "hidden") {
+    console.warn(
+      "[caption-lint] group " + gi + " still visible at t=" + (group.end + 0.01).toFixed(2) + "s",
+    );
+  }
+});
+tl.seek(0);
+```
+
+## Pre-Built Caption Components
+
+Before building caption styles from scratch, check the registry — 15 ready-to-use caption components cover the most common styles. Install with `npx hyperframes add <name>` and wire as a sub-composition via `data-composition-src` (see `hyperframes-registry`).
+
+```bash
+npx hyperframes catalog --tag caption-style   # list all caption components
+npx hyperframes add caption-highlight         # install a specific one
+```
+
+| Style                     | Component                    | Best for                     |
+| ------------------------- | ---------------------------- | ---------------------------- |
+| TikTok-style highlight    | `caption-highlight`          | Social, high-energy          |
+| Karaoke pill              | `caption-pill-karaoke`       | Music, lyric videos          |
+| Cinematic editorial       | `caption-editorial-emphasis` | Documentary, storytelling    |
+| Glitch / cyber            | `caption-glitch-rgb`         | Tech, gaming                 |
+| Full-screen slam          | `caption-kinetic-slam`       | Hype, announcements          |
+| Neon glow                 | `caption-neon-glow`          | Night, club, neon aesthetics |
+| Neon accent (multi-color) | `caption-neon-accent`        | Colorful, playful            |
+| Wipe reveal               | `caption-clip-wipe`          | Clean, modern                |
+| Gradient fill             | `caption-gradient-fill`      | Vibrant, eye-catching        |
+| Matrix decode             | `caption-matrix-decode`      | Sci-fi, tech reveals         |
+| Emoji pop                 | `caption-emoji-pop`          | Social, casual               |
+| Parallax layers           | `caption-parallax-layers`    | Depth, cinematic             |
+| Particle burst            | `caption-particle-burst`     | Celebration, impact keywords |
+| Lava texture              | `caption-texture`            | Bold, dramatic               |
+| Weight shift              | `caption-weight-shift`       | Elegant, typographic         |
+
+Related: `caption-blend-difference` (tagged `text` / `blend-mode`, not `caption-style`, so it won't appear under the filter above) auto-inverts text against any background via `mix-blend-mode: difference` — useful when the background is busy or unpredictable.
+
+Browse all with previews: [hyperframes.heygen.com/catalog](https://hyperframes.heygen.com/catalog)
+
+Caption components ship with transparent backgrounds — they're pure overlays. If the underlying video is bright or busy, add a contrast layer (e.g. a semi-transparent dark div) in the host composition beneath the caption sub-composition, not inside the component itself.
+
+## Further References
+
+- [`motion.md`](motion.md) — karaoke, marker effects, audio-reactive modulation, scatter exits.
+- [`transcript-handling.md`](transcript-handling.md) — input formats, quality checks, cleaning, external API fallback.
+- `hyperframes-animation/rules/css-marker-patterns.md` — marker highlighting (deterministic, fully seekable).
+
+## Constraints
+
+- Deterministic. No `Math.random()`, no `Date.now()`.
+- Sync to transcript timestamps.
+- One group visible at a time.
+- Every group must have a hard `tl.set` kill at `group.end`.
+- Fonts: the compiler auto-embeds only its **built-in mapped set** (Inter, Roboto, Montserrat, …) — for those, just declare `font-family` in CSS. Any **other** font (a brand/custom font like `TT Norms Pro`, or a non-Latin CJK/Devanagari family) is **not** auto-supplied: it needs an `@font-face` pointing at a real `.woff2` shipped with the project, or the text silently falls back to a generic font in the render. Don't assume a `font-family` you can see locally will render — the render machine is a clean headless Chrome with no installed fonts.
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+# Dynamic Caption Techniques
+
+You are here because SKILL.md told you to read this file before writing animation code. Pick your technique combination from the table below based on the energy level you detected from the transcript, then implement using standard GSAP patterns.
+
+## Technique Selection by Energy
+
+| Energy level | Highlight                             | Exit                | Cycle pattern                             |
+| ------------ | ------------------------------------- | ------------------- | ----------------------------------------- |
+| High         | Karaoke with accent glow + scale pop  | Scatter or drop     | Alternate highlight styles every 2 groups |
+| Medium-high  | Karaoke with color pop                | Scatter or collapse | Alternate every 3 groups                  |
+| Medium       | Karaoke (subtle, white only)          | Fade + slide        | Alternate every 3 groups                  |
+| Medium-low   | Karaoke (minimal scale change)        | Fade                | Single style, vary ease per group         |
+| Low          | Karaoke (warm tones, slow transition) | Collapse            | Alternate every 4 groups                  |
+
+**All energy levels use karaoke highlight as the baseline.** The difference is intensity — high energy gets accent color + glow + 15% scale pop on active words, low energy gets a gentle white shift with 3% scale.
+
+**Emphasis words always break the pattern.** When a word is flagged as emphasis (emotional keyword, ALL CAPS, brand name), give it a stronger animation than surrounding words (larger scale, accent color, overshoot ease). This creates contrast.
+
+**Marker highlight modes add a visual layer on top of karaoke.** For emphasis words that need more than color/scale, add a marker-style effect: highlight sweep, circle, burst, scribble, or sketchout. See `hyperframes-animation/rules/css-marker-patterns.md` for implementation details. Match mode to energy: burst for hype, circle for key terms, highlight for standard, scribble for subtle.
+
+## Audio-Reactive Captions (Mandatory for Music)
+
+**If the source audio is music (vocals over instrumentation, beats, any musical content), you MUST extract audio data and add audio-reactive animations.** This is not optional — music without audio reactivity looks disconnected. Even low-energy ballads get subtle bass pulse and treble glow.
+
+No special wiring is needed. The group loop already iterates over every caption group to build entrance, karaoke, and exit tweens. At that point, read the audio data for each group's time range and use it to modulate the group's animation intensity with regular GSAP tweens.
+
+```js
+// Load audio data inline (same pattern as TRANSCRIPT)
+var AUDIO = JSON.parse(audioDataJson); // { fps, totalFrames, frames: [{ bands: [...] }] }
+
+GROUPS.forEach(function (group, gi) {
+  var groupEl = document.getElementById("cg-" + gi);
+  if (!groupEl) return;
+
+  // Read peak energy for this group's time range
+  var startFrame = Math.floor(group.start * AUDIO.fps);
+  var endFrame = Math.min(Math.floor(group.end * AUDIO.fps), AUDIO.totalFrames - 1);
+  var peakBass = 0;
+  var peakTreble = 0;
+  for (var f = startFrame; f <= endFrame; f++) {
+    var frame = AUDIO.frames[f];
+    if (!frame) continue;
+    peakBass = Math.max(peakBass, frame.bands[0] || 0, frame.bands[1] || 0);
+    peakTreble = Math.max(peakTreble, frame.bands[6] || 0, frame.bands[7] || 0);
+  }
+
+  // Modulate entrance — louder groups enter bigger and glowier
+  tl.to(
+    groupEl,
+    {
+      scale: 1 + peakBass * 0.06,
+      textShadow:
+        "0 0 " + Math.round(peakTreble * 12) + "px rgba(255,255,255," + peakTreble * 0.4 + ")",
+      duration: 0.3,
+      ease: "power2.out",
+    },
+    group.start,
+  );
+
+  // Reset at exit so audio-driven values don't persist
+  tl.set(groupEl, { scale: 1, textShadow: "none" }, group.end - 0.15);
+});
+```
+
+This shapes the animation at build time, not playback time — no per-frame callbacks, no `tl.call()` loops, no async fetch timing issues. Loud groups come in with more weight and glow; quiet groups come in soft. The audio data modulates _how much_, the content determines _what_.
+
+Keep audio reactivity subtle — 3-6% scale variation and soft glow. Heavy pulsing makes text unreadable.
+
+To generate the audio data file:
+
+```bash
+python3 skills/hyperframes-creative/scripts/extract-audio-data.py audio.mp3 --fps 30 --bands 8 -o audio-data.json
+```
+
+## Combining Techniques
+
+Don't use the same highlight animation on every group — cycle through styles using the group index. Don't combine multiple competing animations on the same word at the same timestamp. Vary techniques across groups to match the content's pace changes.
+
+**Marker highlight effects** layer well with karaoke — use karaoke for the word-by-word reveal, then add a marker effect on emphasis words only. For example: karaoke highlights each word in white, but brand names get a yellow highlight sweep and stats get a red circle. Cycle marker modes across groups for visual variety.
+
+## Runtime Tools
+
+Caption motion uses standard HyperFrames runtime APIs. Use the canonical sources:
+
+- **GSAP timeline + tween syntax** — `hyperframes-animation/adapters/gsap.md` (eases, position parameter, performance)
+- **`window.__hyperframes.fitTextFontSize` / `pretext`** — `hyperframes-core/references/determinism-rules.md` → Layout Contract (overflow prevention, per-frame text measurement)
+- **Audio data extraction** — generate via `python3 skills/hyperframes-creative/scripts/extract-audio-data.py audio.mp3 --fps 30 --bands 8 -o audio-data.json`, then load inline as shown in "Audio-Reactive Captions" above
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+# Transcript Guide
+
+For the `transcribe` CLI invocation, the `.en`-translates-non-English rule, and whisper model selection, see [`../transcribe.md`](../transcribe.md). This file covers what to do with the resulting transcript when authoring captions: input formats, mandatory quality checks, cleaning code, external-API fallbacks.
+
+## Supported Input Formats
+
+The CLI auto-detects and normalizes these formats:
+
+| Format                | Extension | Source                                                                      | Word-level?       |
+| --------------------- | --------- | --------------------------------------------------------------------------- | ----------------- |
+| whisper.cpp JSON      | `.json`   | `hyperframes init --video`, `hyperframes transcribe`                        | Yes               |
+| OpenAI Whisper API    | `.json`   | `openai.audio.transcriptions.create({ timestamp_granularities: ["word"] })` | Yes               |
+| SRT subtitles         | `.srt`    | Video editors, subtitle tools, YouTube                                      | No (phrase-level) |
+| VTT subtitles         | `.vtt`    | Web players, YouTube, transcription services                                | No (phrase-level) |
+| Normalized word array | `.json`   | Pre-processed by any tool                                                   | Yes               |
+
+**Word-level timestamps produce better captions.** SRT/VTT give phrase-level timing, which works but can't do per-word animation effects.
+
+## Transcript Quality Check (Mandatory)
+
+After every transcription, **read the transcript and check for quality issues before proceeding.** Bad transcripts produce nonsensical captions. Never skip this step.
+
+### What to look for
+
+| Signal                       | Example                                | Cause                                                                        |
+| ---------------------------- | -------------------------------------- | ---------------------------------------------------------------------------- |
+| Music note tokens (`♪`, `�`) | `{ "text": "♪" }` or `{ "text": "�" }` | Whisper detected music, not speech                                           |
+| Garbled / nonsense words     | "Do a chin", "Get so gay", "huh"       | Model misheard lyrics or background noise                                    |
+| Long gaps with no words      | 20+ seconds of only `♪` tokens         | Instrumental section — expected, but high ratio means speech is being missed |
+| Repeated filler              | Many "huh", "uh", "oh" entries         | Model is hallucinating on music                                              |
+| Very short word spans        | Words with `end - start < 0.05`        | Unreliable timestamp alignment                                               |
+
+### Automatic retry rules
+
+**If more than 20% of entries are `♪`/`�` tokens, or the transcript contains obvious nonsense words, the transcription failed.** Do not proceed with the bad transcript. Instead:
+
+1. **Retry with `medium.en`** if the original used `small.en` or smaller:
+   ```bash
+   npx hyperframes transcribe audio.mp3 --model medium.en
+   ```
+2. **If `medium.en` also fails** (still >20% music tokens or garbled), tell the user the audio is too noisy for local transcription and suggest:
+   - Providing lyrics manually as an SRT/VTT file
+   - Using an external API (OpenAI or Groq Whisper — see below)
+3. **Always clean the transcript** before building captions — filter out `♪`/`�` tokens and entries where `text` is a single non-word character. Only real words should reach the caption composition.
+
+### Cleaning a transcript
+
+After transcription (even with a good model), strip non-word entries:
+
+```js
+var raw = JSON.parse(transcriptJson);
+var words = raw.filter(function (w) {
+  if (!w.text || w.text.trim().length === 0) return false;
+  if (/^[♪�\u266a\u266b\u266c\u266d\u266e\u266f]+$/.test(w.text)) return false;
+  if (/^(huh|uh|um|ah|oh)$/i.test(w.text) && w.end - w.start < 0.1) return false;
+  return true;
+});
+```
+
+For model-selection guidance by content type, see [`../transcribe.md`](../transcribe.md) → "Picking a model by content type".
+
+## Using External Transcription APIs
+
+For the best accuracy, use an external API and import the result:
+
+**OpenAI Whisper API** (recommended for quality):
+
+```bash
+# Generate with word timestamps, then import
+curl https://api.openai.com/v1/audio/transcriptions \
+  -H "Authorization: Bearer $OPENAI_API_KEY" \
+  -F file=@audio.mp3 -F model=whisper-1 \
+  -F response_format=verbose_json \
+  -F "timestamp_granularities[]=word" \
+  -o transcript-openai.json
+
+npx hyperframes transcribe transcript-openai.json
+```
+
+**Groq Whisper API** (fast, free tier available):
+
+```bash
+curl https://api.groq.com/openai/v1/audio/transcriptions \
+  -H "Authorization: Bearer $GROQ_API_KEY" \
+  -F file=@audio.mp3 -F model=whisper-large-v3 \
+  -F response_format=verbose_json \
+  -F "timestamp_granularities[]=word" \
+  -o transcript-groq.json
+
+npx hyperframes transcribe transcript-groq.json
+```
+
+## If No Transcript Exists
+
+1. Check the project root for `transcript.json`, `.srt`, or `.vtt` files.
+2. If none found, run [`../transcribe.md`](../transcribe.md) — pick the starting model from "Picking a model by content type" there.
+3. Run the quality check above. If it fails, retry with a larger model or fall back to manual lyrics / external API.