Vance Ingalls 80e7cd2844 perf(player): p0-1c live-playback parity test via SSIM (#401)
## Summary

Adds **scenario 06: live-playback parity** — the third and final tranche of the P0-1 perf-test buildout (`p0-1a` infra → `p0-1b` fps/scrub/drift → this).

The scenario plays the `gsap-heavy` fixture, freezes it mid-animation, screenshots the live frame, then synchronously seeks the same player back to that exact timestamp and screenshots the reference. The two PNGs are diffed with `ffmpeg -lavfi ssim` and the resulting average SSIM is emitted as `parity_ssim_min`. Baseline gate: **SSIM ≥ 0.95**.

This pins the player's two frame-production paths (the runtime's animation loop vs. `_trySyncSeek`) to each other visually, so any future drift between scrub and playback fails CI instead of silently shipping.

## Motivation

`<hyperframes-player>` produces frames two different ways:

1. **Live playback** — the runtime's animation loop advances the GSAP timeline frame-by-frame.
2. **Synchronous seek** (`_trySyncSeek`, landed in #397) — for same-origin embeds, the player calls into the iframe runtime's `seek()` directly and asks for a specific time.

These paths must agree. If they don't — different rounding, different sub-frame sampling, different state ordering — scrubbing a paused composition shows different pixels than a paused-during-playback frame at the same time. That's a class of bug that only surfaces visually, never in unit tests, and only at specific timestamps where many things are mid-flight.

`gsap-heavy` is a 10s composition with 60 tiles each running a staggered 4s out-and-back tween. At t=5.0s a large fraction of those tiles are mid-flight, so the rendered frame has many distinct, position-sensitive pixels — the worst-case input for any sub-frame disagreement. If the two paths produce identical pixels here, they'll produce identical pixels everywhere that matters.

## What changed

- **`packages/player/tests/perf/scenarios/06-parity.ts`** — new scenario (~340 lines). Owns capture, seek, screenshot, SSIM, artifact persistence, and aggregation.
- **`packages/player/tests/perf/index.ts`** — register `parity` as a scenario id, default-runs = 3, dispatch to `runParity`, include in the default scenario list.
- **`packages/player/tests/perf/perf-gate.ts`** — extend `PerfBaseline` with `paritySsimMin`.
- **`packages/player/tests/perf/baseline.json`** — `paritySsimMin: 0.95`.
- **`.github/workflows/player-perf.yml`** — add a `parity` shard (3 runs) to the matrix alongside `load` / `fps` / `scrub` / `drift`.

## How the scenario works

The hard part is making the two captures land on the *exact same timestamp* without trusting `postMessage` round-trips or arbitrary `setTimeout` settling.

1. **Install an iframe-side rAF watcher** before issuing `play()`. The watcher polls `__player.getTime()` every animation frame and, the first time `getTime() >= 5.0`, calls `__player.pause()` *from inside the same rAF tick*. `pause()` is synchronous (it calls `timeline.pause()`), so the timeline freezes at exactly that `getTime()` value with no postMessage round-trip. The watcher's Promise resolves with that frozen value as the canonical `T_actual` for the run.
2. **Confirm `isPlaying() === true`** via `frame.waitForFunction` before awaiting the watcher. Without this, the test can hang if `play()` hasn't kicked the timeline yet.
3. **Wait for paint** — two `requestAnimationFrame` ticks on the host page. The first flushes pending style/layout, the second guarantees a painted compositor commit. Same paint-settlement pattern as `packages/producer/src/parity-harness.ts`.
4. **Screenshot the live frame** — `page.screenshot({ type: "png" })`.
5. **Synchronously seek to `T_actual`** — call `el.seek(capturedTime)` on the host page. The player's public `seek()` calls `_trySyncSeek` which (same-origin) calls `__player.seek()` synchronously, so no postMessage await is needed. The runtime's deterministic `seek()` rebuilds frame state at exactly the requested time.
6. **Wait for paint** again, screenshot the reference frame.
7. **Diff with ffmpeg** — `ffmpeg -hide_banner -i reference.png -i actual.png -lavfi ssim -f null -`. ffmpeg writes per-channel + overall SSIM to stderr; we parse the `All:` value, clamp at 1.0 (ffmpeg occasionally reports 1.000001 on identical inputs), and treat it as the run's score.
8. **Persist artifacts** under `tests/perf/results/parity/run-N/` (`actual.png`, `reference.png`, `captured-time.txt`) so CI can upload them and so a failed run is locally reproducible. Directory is already gitignored via the existing `packages/player/tests/perf/results/` rule.

### Aggregation

`min()` across runs, **not** mean. We want the *worst observed* parity to pass the gate so a single bad run can't get masked by averaging. Both per-run scores and the aggregate are logged.

### Output metric

| name              | direction        | baseline             |
|-------------------|------------------|----------------------|
| `parity_ssim_min` | higher-is-better | `paritySsimMin: 0.95` |

With deterministic rendering enabled in the runner, identical pixels produce SSIM very close to 1.0; the 0.95 threshold leaves headroom for legitimate fixture-level noise (font hinting, GPU compositor variance) while still catching any real disagreement between the two paths.

## Test plan

- `bun run player:perf -- --scenarios=parity --runs=3` locally on `gsap-heavy` — passes with SSIM ≈ 0.999 across all 3 runs.
- Inspected `results/parity/run-1/actual.png` and `reference.png` side-by-side — visually identical.
- Inspected `captured-time.txt` to confirm `T_actual` lands just past 5.0s (within one frame).
- Sanity test: temporarily forced a 1-frame offset between live and reference capture; SSIM dropped well below 0.95 as expected, confirming the threshold catches real drift.
- CI: `parity` shard added alongside the existing `load` / `fps` / `scrub` / `drift` shards; same `measure`-mode / artifact-upload / aggregation flow.
- `bunx oxlint` and `bunx oxfmt --check` clean on the new scenario.

## Stack

This is the top of the perf stack:

1. #393 `perf/x-1-emit-performance-metric` — performance.measure() emission
2. #394 `perf/p1-1-share-player-styles-via-adopted-stylesheets` — adopted stylesheets
3. #395 `perf/p1-2-scope-media-mutation-observer` — scoped MutationObserver
4. #396 `perf/p1-4-coalesce-mirror-parent-media-time` — coalesce currentTime writes
5. #397 `perf/p3-1-sync-seek-same-origin` — synchronous seek path (the path this PR pins)
6. #398 `perf/p3-2-srcdoc-composition-switching` — srcdoc switching
7. #399 `perf/p0-1a-perf-test-infra` — server, runner, perf-gate, CI
8. #400 `perf/p0-1b-perf-tests-for-fps-scrub-drift` — fps / scrub / drift scenarios
9. **#401 `perf/p0-1c-live-playback-parity-test` ← you are here**

With this PR landed the perf harness covers all five proposal scenarios: `load`, `fps`, `scrub`, `drift`, `parity`.
2026-04-22 18:15:46 -07:00
2026-03-21 22:43:56 -07:00

HyperFrames

npm version npm downloads License Node.js

Write HTML. Render video. Built for agents.

HyperFrames demo — HTML code on the left transforms into a rendered video on the right

Hyperframes is an open-source video rendering framework that lets you create, preview, and render HTML-based video compositions — with first-class support for AI agents.

Quick Start

Install the HyperFrames skills, then describe the video you want:

npx skills add heygen-com/hyperframes

This teaches your agent (Claude Code, Cursor, Gemini CLI, Codex) how to write correct compositions and GSAP animations. In Claude Code, the skills register as slash commands — invoke /hyperframes to author compositions, /hyperframes-cli for CLI commands, and /gsap for animation help.

For Codex specifically, the same skills are also exposed as an OpenAI Codex plugin — sparse-install just the plugin surface:

codex plugin marketplace add heygen-com/hyperframes --sparse .codex-plugin --sparse skills --sparse assets

Try it: example prompts

Copy any of these into your agent to get started. The /hyperframes prefix loads the skill context explicitly so you get correct output the first time.

Cold start — describe what you want:

Using /hyperframes, create a 10-second product intro with a fade-in title, a background video, and background music.

Warm start — turn existing context into a video:

Take a look at this GitHub repo https://github.com/heygen-com/hyperframes and explain its uses and architecture to me using /hyperframes.

Summarize the attached PDF into a 45-second pitch video using /hyperframes.

Turn this CSV into an animated bar chart race using /hyperframes.

Format-specific:

Make a 9:16 TikTok-style hook video about [topic] using /hyperframes, with bouncy captions synced to a TTS narration.

Iterate — talk to the agent like a video editor:

Make the title 2x bigger, swap to dark mode, and add a fade-out at the end.

Add a lower third at 0:03 with my name and title.

The agent handles scaffolding, animation, and rendering. See the prompting guide for more patterns.

Option 2: Start a project manually

npx hyperframes init my-video
cd my-video
npx hyperframes preview      # preview in browser (live reload)
npx hyperframes render       # render to MP4

hyperframes init installs skills automatically, so you can hand off to your AI agent at any point.

Requirements: Node.js >= 22, FFmpeg

Why Hyperframes?

  • HTML-native — compositions are HTML files with data attributes. No React, no proprietary DSL.
  • AI-first — agents already speak HTML. The CLI is non-interactive by default, designed for agent-driven workflows.
  • Deterministic rendering — same input = identical output. Built for automated pipelines.
  • Frame Adapter pattern — bring your own animation runtime (GSAP, Lottie, CSS, Three.js).

Hyperframes vs Remotion

Hyperframes is inspired by Remotion — we used Remotion at HeyGen in production, learned a ton from it, and kept attribution comments in the source for the patterns it pioneered (Chrome launch flags, image2pipe → FFmpeg streaming, frame buffering). Both tools drive headless Chrome and both are deterministic. They differ on one decision: what the primary author writes. Remotion's bet is React components; Hyperframes' bet is HTML.

Hyperframes Remotion
Authoring HTML + CSS + GSAP React components (TSX)
Build step None; index.html plays as-is Required (bundler)
Library-clock animations (GSAP, Anime.js, Motion One) Seekable, frame-accurate Plays at wall-clock during render
Arbitrary HTML / CSS passthrough Paste and animate Rewrite as JSX
Distributed rendering Single-machine today Lambda, production-ready

Licensing: fully open source vs source-available

Hyperframes is completely open source under Apache 2.0 — an OSI-approved license. Use it commercially at any scale, with no per-render fees, no seat caps, no company-size thresholds.

Remotion is source-available, not open source. The code is on GitHub under a custom Remotion License that requires a paid company license above small-team thresholds. It's a great product with a real team behind it — but if open-source licensing matters to you (OSI compliance, redistribution rights, no per-use fees), that's a first-order decision point.

Full write-up with benchmarks, an honest list of where each tool wins, and a GSAP side-by-side: Hyperframes vs Remotion guide.

How It Works

Define your video as HTML with data attributes:

<div id="stage" data-composition-id="my-video" data-start="0" data-width="1920" data-height="1080">
  <video
    id="clip-1"
    data-start="0"
    data-duration="5"
    data-track-index="0"
    src="intro.mp4"
    muted
    playsinline
  ></video>
  <img
    id="overlay"
    class="clip"
    data-start="2"
    data-duration="3"
    data-track-index="1"
    src="logo.png"
  />
  <audio
    id="bg-music"
    data-start="0"
    data-duration="9"
    data-track-index="2"
    data-volume="0.5"
    src="music.wav"
  ></audio>
</div>

Preview instantly in the browser. Render to MP4 locally or in Docker.

Catalog

50+ ready-to-use blocks and components — social overlays, shader transitions, data visualizations, and cinematic effects:

npx hyperframes add flash-through-white   # shader transition
npx hyperframes add instagram-follow      # social overlay
npx hyperframes add data-chart            # animated chart

Browse the full catalog at hyperframes.heygen.com/catalog.

Documentation

Full documentation at hyperframes.heygen.com/introduction — Quickstart | Guides | API Reference | Catalog

Packages

Package Description
hyperframes CLI — create, preview, lint, and render compositions
@hyperframes/core Types, parsers, generators, linter, runtime, frame adapters
@hyperframes/engine Seekable page-to-video capture engine (Puppeteer + FFmpeg)
@hyperframes/producer Full rendering pipeline (capture + encode + audio mix)
@hyperframes/studio Browser-based composition editor UI
@hyperframes/player Embeddable <hyperframes-player> web component
@hyperframes/shader-transitions WebGL shader transitions for compositions

Skills

HyperFrames ships skills that teach AI agents framework-specific patterns that generic docs don't cover.

npx skills add heygen-com/hyperframes
Skill What it teaches
hyperframes HTML composition authoring, captions, TTS, audio-reactive animation, transitions
hyperframes-cli CLI commands: init, lint, preview, render, transcribe, tts, doctor
hyperframes-registry Block and component installation via hyperframes add
website-to-hyperframes Capture a URL and turn it into a video — full website-to-video pipeline
gsap GSAP animation API, timelines, easing, ScrollTrigger, plugins, React/Vue/Svelte, performance

Contributing

See CONTRIBUTING.md for guidelines.

Cloning the repo

The repo uses Git LFS for golden regression-test baselines under packages/producer/tests/**/output.mp4 (~240 MB of .mp4 files). If you're cloning the full repo for development, install Git LFS first:

# macOS
brew install git-lfs

# Ubuntu/Debian
sudo apt install git-lfs

# Windows
winget install GitHub.GitLFS
# (or install Git for Windows, which bundles Git LFS as an optional component)

# Then (once, per machine)
git lfs install

If you hit git-lfs filter-process: command not found during git clone or npx skills add heygen-com/hyperframes, install Git LFS and retry. You can also skip LFS content if you only need the source files:

GIT_LFS_SKIP_SMUDGE=1 git clone https://github.com/heygen-com/hyperframes.git

License

Apache 2.0

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Write HTML. Render video. Built for agents.
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