hyperframes-media

$28

Content type

Voice

Why

Product demo

af_heart/af_nova

Warm, professional

Tutorial / how-to

am_adam/bf_emma

Neutral, easy to follow

Marketing / promo

af_sky/am_michael

Energetic or authoritative

Documentation

bf_emma/bm_george

Clear British English, formal

Casual / social

af_heart/af_sky

Approachable, natural

Multilingual

Voice IDs encode language in the first letter: a=American English, b=British English, e=Spanish, f=French, h=Hindi, i=Italian, j=Japanese, p=Brazilian Portuguese, z=Mandarin. The CLI auto-detects the phonemizer locale from the prefix — no --lang needed when the voice matches the text.

npx hyperframes tts "La reunión empieza a las nueve" --voice ef_dora --output es.wav

npx hyperframes tts "今日はいい天気ですね" --voice jf_alpha --output ja.wav

Use --lang only to override auto-detection (stylized accents). Valid codes: en-us, en-gb, es, fr-fr, hi, it, pt-br, ja, zh. Non-English phonemization requires espeak-ng system-wide (brew install espeak-ng / apt-get install espeak-ng).

Speed

• 0.7-0.8 — tutorial, complex content, accessibility

• 1.0 — natural pace (default)

• 1.1-1.2 — intros, transitions, upbeat content

• 1.5+ — rarely appropriate; test carefully

Long Scripts

For more than a few paragraphs, write to a .txt file and pass the path. Inputs over ~5 minutes of speech may benefit from splitting into segments.

Requirements

Python 3.8+ with kokoro-onnx and soundfile (pip install kokoro-onnx soundfile). Model downloads on first use (~311 MB + ~27 MB voices, cached in ~/.cache/hyperframes/tts/).

Transcription ( transcribe )

Produce a normalized transcript.json with word-level timestamps.

npx hyperframes transcribe audio.mp3

npx hyperframes transcribe video.mp4 --model small --language es

npx hyperframes transcribe subtitles.srt          # import existing

npx hyperframes transcribe subtitles.vtt

npx hyperframes transcribe openai-response.json

Language Rule (Non-Negotiable)

**Never use .en models unless the user explicitly states the audio is English.** .en models (small.en, medium.en) translate non-English audio into English instead of transcribing it. This silently destroys the original language.

• Language known and non-English → --model small --language <code> (no .en suffix)

• Language known and English → --model small.en

• Language unknown → --model small (no .en, no --language) — whisper auto-detects

**Default model is small, not small.en.**

Model Sizes

Model

Size

Speed

When to use

tiny

75 MB

Fastest

Quick previews, testing pipeline

base

142 MB

Fast

Short clips, clear audio

small

466 MB

Moderate

Default — most content

medium

1.5 GB

Slow

Important content, noisy audio, music

large-v3

3.1 GB

Slowest

Production quality

Music with vocals: start at medium minimum; produced tracks often need manual SRT/VTT import. For caption-quality checks (mandatory after every transcription), the cleaning JS, retry rules, and the OpenAI/Groq API import path, see hyperframes/references/transcript-guide.md.

Output Shape

Compositions consume a flat array of word objects. The id field (w0, w1, ...) is added during normalization for stable references in caption overrides; it's optional for backwards compatibility.

[

  { "id": "w0", "text": "Hello", "start": 0.0, "end": 0.5 },

  { "id": "w1", "text": "world.", "start": 0.6, "end": 1.2 }

]

Background Removal ( remove-background )

Remove the background from a video or image so the subject (typically a person — avatar, presenter, talking head) sits as a transparent overlay in a composition.

npx hyperframes remove-background subject.mp4 -o transparent.webm  # default: VP9 alpha WebM

npx hyperframes remove-background subject.mp4 -o transparent.mov   # ProRes 4444 (editing)

npx hyperframes remove-background portrait.jpg -o cutout.png       # single-image cutout

npx hyperframes remove-background subject.mp4 -o subject.webm \

  --background-output plate.webm                                   # both layers in one pass

npx hyperframes remove-background subject.mp4 -o transparent.webm --device cpu

npx hyperframes remove-background --info                           # detected providers

Uses u2net_human_seg (MIT). First run downloads ~168 MB of weights to ~/.cache/hyperframes/background-removal/models/.

Layer separation ( --background-output )

Pass --background-output (or -b) to emit a second transparent video alongside the cutout: same source RGB, alpha is 255 − mask instead of mask. The cutout is the subject with a transparent background; the plate is the original surroundings with a transparent hole where the subject was.

File

Alpha is…

Use it for

-o subject.webm

The mask — subject opaque, background transparent

Foreground layer, place on top

--background-output plate.webm

Inverse — surroundings opaque, subject region transparent

Bottom layer; put text or graphics between this and the subject

Both outputs share the same --quality preset and run from a single inference pass — encode cost roughly doubles, segmentation cost stays the same. Only valid for video inputs and .webm/.mov outputs.

Hole-cut plate, not an inpainted clean plate. The subject region in plate.webm is fully transparent — composite something opaque under it to fill the hole. The single test for whether --background-output is the right tool: will anything ever be visible through the subject's silhouette where the subject used to be?

Use case

Right tool

Text/graphics between the cutout and the plate (this command's reason for existing)

Hole-cut (--background-output)

Subject onto an unrelated scene

Just subject.webm; ignore the plate

Show the room without the person, alone over no other content

Clean plate — needs an inpainter (LaMa, ProPainter, E2FGVI). Not this command.

Replace the subject with a different subject

Clean plate — same as above

If a user asks for "the room with the person removed" and intends to display it standalone, do not reach for --background-output. Tell them they need an inpainter.

Typical layered composition (the canonical hole-cut use case):

<!-- z=1 the inverse-alpha plate fills everything except the subject region -->

<video

  src="plate.webm"

  data-start="0"

  data-duration="6"

  data-track-index="0"

  muted

  playsinline

></video>

<!-- z=2 graphics / text live between the two layers -->

<h1 id="headline" style="z-index:2; ...">MAKE IT IN HYPERFRAMES</h1>

<!-- z=3 the cutout floats the subject back over the headline -->

<div class="cutout-wrap" style="position:absolute;inset:0;z-index:3">

  <video

    src="subject.webm"

    data-start="0"

    data-duration="6"

    data-track-index="1"

    muted

    playsinline

  ></video>

</div>

This is functionally equivalent to the text-behind-subject pattern below, but you don't need the original presenter.mp4 in the project — the plate replaces it. Useful when you want to ship just the two transparent layers and let the user drop arbitrary content between them.

Output Format

Format

When

.webm (VP9 + alpha)

Default. Compositions play this directly via <video>.

.mov (ProRes 4444)

Editing in DaVinci/Premiere/FCP. Large files.

.png

Single-image cutout (still subject, layered over a backdrop).

Chrome decodes VP9 alpha natively, so the .webm plugs into a composition like any other muted-autoplay video — see the hyperframes skill for the <video> track conventions.

Quality presets

--quality fast|balanced|best controls only the VP9 encoder's CRF — segmentation quality is fixed.

Preset

CRF

When

fast

30

Iterating, smaller file, looser color match

balanced

18

Default. Visually identical for most uses

best

12

Master / final delivery. Largest file, tightest match

Compositing patterns — pick the right one

The cutout webm is a re-encoded copy of the source mp4's RGB. That choice has consequences depending on what you put behind it:

Pattern

What's behind the cutout

Result

Cutout over a different scene (most common)

Static image, gradient, or unrelated video

Looks great. The cutout's RGB is the only source of the subject — no doubling, no edge halo. This is what remove-background is built for.

Cutout over its own source mp4 (text-behind-subject)

Same mp4 the cutout was generated from

Two RGB sources for the same person. At default --quality balanced (crf 18) the doubling is barely visible; at --quality fast (crf 30) you'll see a faint color shift / edge halo. Use --quality best (crf 12) for masters.

Cutout over a different take of the same person

Footage of the same subject

Will look like two separate people overlapping. Don't do this.

Text-behind-subject (headline behind a presenter):

<video

  src="presenter.mp4"

  id="bg"

  data-start="0"

  data-duration="6"

  data-track-index="0"

  muted

  playsinline

></video>

<h1 id="headline" style="z-index:2; ...">MAKE IT IN HYPERFRAMES</h1>

<div class="cutout-wrap" style="position:absolute;inset:0;z-index:3;opacity:0">

  <video

    src="presenter.webm"

    data-start="0"

    data-duration="6"

    data-track-index="1"

    muted

    playsinline

  ></video>

</div>

Two key rules:

• **Wrap the cutout video in a non-timed <div>** and animate the wrapper's opacity, not the video element's. The framework forces opacity:1 on active clips (any element with data-start/data-duration), so animating the video's opacity directly is silently overridden. The wrapper has no data-* attributes, so it's owned by your CSS/GSAP.

• **Both videos use data-start="0" and data-media-start="0"** so the framework decodes them in sync from t=0. Late-mounting the cutout (data-start=3.3) introduces a seek + warm-up that lands a frame off the base mp4 — visible as one frame of misalignment at the cut.

Then GSAP-flip the wrapper opacity at the cut: tl.set(cutoutWrap, { opacity: 1 }, 3.3).

TTS → Transcribe → Captions

When there's no pre-recorded voiceover, generate one and transcribe it back to get word-level timestamps for captions:

npx hyperframes tts script.txt --voice af_heart --output narration.wav

npx hyperframes transcribe narration.wav   # → transcript.json

Whisper extracts precise word boundaries from the generated audio, so caption timing matches delivery without hand-tuning.