Vance Ingalls 00af29c169 fix(cli): forward --hdr through Docker render + HDR docs (#346)
## Summary

This PR ended up covering the full HDR Docker/docs follow-through plus the producer/engine work needed to make HDR still images render and regress correctly in CI.

The branch now does four things:

- forwards `--hdr` through the Docker render path in the CLI
- adds and expands HDR documentation across the docs site
- adds first-class HDR still-image support to the engine/producer pipeline
- adds targeted HDR regression coverage, including a CI-safe fallback for PNG HDR metadata detection when `ffprobe` does not expose PNG color tags

## What changed

### CLI and docs

- `hyperframes render --docker --hdr` now preserves `--hdr` when invoking the in-container CLI
- added a dedicated HDR guide and linked it from CLI, producer, engine, rendering, and common-mistakes docs
- documented HDR constraints and verification flow: HDR source requirements, MP4/H.265 Main10 output, PQ/HLG handling, Docker usage, and common SDR fallback causes

### Engine and producer HDR image support

- added `ImageElement` support to the engine composition model and parsing path
- threaded image elements through producer compilation and orchestration
- probed image sources for HDR color spaces so image-only compositions can trigger HDR output without requiring an HDR video source
- included HDR image start times in stacking queries so the layered compositor can place images correctly in z-order
- integrated HDR image compositing into the layered HDR render loop alongside native HDR video layers and SDR DOM overlays
- forced screenshot mode for HDR layered compositing where required to keep DOM/HDR layer composition deterministic
- skipped readiness waiting for natively extracted HDR videos in the engine path where it was unnecessary and could block layered HDR flows

### HDR metadata robustness

- added a fallback in `extractVideoMetadata()` to read PNG `cICP` metadata directly when `ffprobe` omits color-space fields for PNGs
- this specifically fixes CI/Docker detection for the `hdr-image-only` fixture, where the render was falling back to SDR because the PNG was not being recognized as BT.2020 PQ

### Regression coverage and fixture cleanup

- added `hdr-image-only`, a regression fixture that validates HDR still-image rendering end to end
- added `hdr-pq`, a focused HDR PQ regression fixture for the video path
- updated regression CI to run an `hdr` shard with `--sequential hdr-pq hdr-image-only`
- removed the older larger `hdr-regression/*` fixture set in favor of the smaller targeted regressions used by CI
- added the necessary fixture generation/readme material and checked-in golden outputs for the new HDR tests

## Why

The original PR description only covered the CLI flag forwarding and docs work. Since then, the branch also picked up the missing runtime support needed for HDR still images and the regression coverage to keep that path from breaking.

The practical issue this closes is:

- local host runs could pass while CI failed `hdr-image-only`
- the failure was a full-frame visual mismatch caused by SDR fallback, not unstable rendering
- root cause was PNG HDR metadata not being surfaced by `ffprobe` in the CI Docker environment
- parsing the PNG `cICP` chunk directly makes HDR detection deterministic across environments

## Test plan

### Local targeted checks

```bash
bunx oxlint packages/engine/src/utils/ffprobe.ts packages/engine/src/utils/ffprobe.test.ts
bunx oxfmt packages/engine/src/utils/ffprobe.ts packages/engine/src/utils/ffprobe.test.ts
bun --cwd packages/engine test src/utils/ffprobe.test.ts src/utils/hdr.test.ts
```

### Producer regression runs on host

```bash
bun run --cwd packages/core build:hyperframes-runtime:modular
bun --cwd packages/producer test -- --sequential --exclude-tags slow,render-compat,hdr
bun --cwd packages/producer test -- --sequential hdr-pq hdr-image-only
```

Observed result:
- `fast` shard: 7 passed, 0 failed
- `hdr` shard: 2 passed, 0 failed

### CI-equivalent Docker verification

```bash
docker build -f Dockerfile.test -t hyperframes-producer:test .

docker run --rm \
  --security-opt seccomp=unconfined \
  --shm-size=4g \
  -v "$PWD/packages/producer/tests:/app/packages/producer/tests" \
  hyperframes-producer:test \
  --sequential hdr-pq hdr-image-only
```

Observed result:
- `hdr-image-only`: passed
- `hdr-pq`: passed
- shard summary: 2 passed, 0 failed

### Specific regression fixed

Before the PNG `cICP` fallback, the Docker/CI run failed `hdr-image-only` with:

- missing `"[Render] HDR source detected — output: PQ ..."` log line
- full-frame visual mismatch across all 100 checkpoints
- PSNR ~17 on every frame, indicating a consistent SDR-vs-HDR pipeline mismatch

After the fallback, the same Docker path recognizes the PNG as HDR and the shard passes.
2026-04-20 12:16:24 -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.

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).

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/introductionQuickstart | 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.

License

Apache 2.0

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