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concept-to-image

将任何概念、想法或描述转化为精美的静态HTML视觉效果,然后将其导出为PNG或SVG图像文件。当用户明确需要输出图像文件(PNG或SVG)时使用此技能。这包括:概念图、流程图、比较图、过程可视化、教育图表、社交媒体图形、数据可视化、海报、卡片、徽章、图标、标志草图,或者任何可以通过HTML/CSS/SVG而不是摄影AI生成实现的“给我做一个X的图片”的请求。如果用户已有HTML视觉效果并希望将其导出/转换为PNG或SVG时也触发该技能。触发短语:“创建一个...的图片”,“导出为PNG”,“另存为SVG”,“概念转图片”,“把这个变成图片”,“截图这个HTML”,“设计一个用于导出的图形”。对于在浏览器中打开的交互式HTML视觉效果,请改用static-web-artifacts-builder。

person作者: jakexiaohubgithub

Concept to Image

Creates polished visuals from concepts using HTML/CSS/SVG as a refineable intermediate, then exports to PNG or SVG.

Reference Files

| File | Purpose | | ---------------------------- | ------------------------------------------------------------------------------------ | | references/design-guide.md | Design patterns, anti-patterns, color palettes, typography choices, layout examples | | scripts/render_to_image.py | Playwright-based export script — takes HTML in, PNG or SVG out | | assets/template.html | Base HTML template with .canvas container and CSS custom properties pre-configured |

Why HTML as intermediate

HTML is the refineable layer between idea and image. Unlike direct canvas rendering, the user can see the HTML artifact, request changes ("make the title bigger", "swap the colors", "add a third column"), and only export once satisfied. This makes the workflow iterative and controllable.

Workflow

Concept → HTML artifact (view + refine) → PNG or SVG export
  1. Interpret the user's concept — determine what kind of visual best fits (diagram, infographic, card, chart, etc.)
  2. Design a self-contained HTML file using inline CSS and inline SVG — zero external dependencies
  3. Present the HTML as an artifact so the user can preview and request refinements
  4. Iterate on the HTML based on user feedback (colors, layout, content, sizing)
  5. Export to PNG and/or SVG when the user is satisfied, using scripts/render_to_image.py

Step 1: Interpret the concept

Determine the best visual format:

| User intent | Visual format | Approach | | ------------------------ | ----------------------------- | ---------------------------------- | | Explain a process/flow | Flowchart or pipeline diagram | SVG paths + boxes | | Compare items | Side-by-side or matrix | CSS Grid | | Show hierarchy | Tree or layered diagram | Nested containers + SVG connectors | | Present data | Chart or infographic | SVG shapes + data labels | | Social/marketing graphic | Card or poster | Typography-forward HTML/CSS | | Icon, logo, badge | Compact symbol | Pure SVG | | Educational concept | Annotated diagram | SVG + positioned labels |

Step 2: Design the HTML

Read references/design-guide.md for detailed design patterns and anti-patterns.

Core rules:

  • Single file, self-contained: All CSS inline in <style>, all graphics as inline <svg>. No external resources.
  • Fixed viewport: Set explicit width and height on the root container matching the intended export size. This is critical — Playwright screenshots the element at this exact size.
  • Anti-AI-slop: Avoid centered-everything layouts, purple gradients, uniform rounded corners, and Inter/system font defaults. See design guide for alternatives.
  • SVG-first for shapes: Use inline SVG for icons, connectors, shapes, and any element that should scale cleanly. CSS for layout and typography.
  • Color with intention: 3-4 hues max + neutrals. Define as CSS custom properties. Every color encodes meaning.
  • Start from the template: Use assets/template.html as the base structure.

Sizing guidelines

| Use case | Recommended size | | ---------------------- | ------------------ | | Social media graphic | 1200×630 | | Infographic (portrait) | 800×1200 | | Presentation slide | 1920×1080 | | Square post | 1080×1080 | | Icon/badge | 256×256 or 512×512 | | Wide diagram | 1600×900 |

Set the .canvas container to the chosen size. The export script captures this element.

Step 3: Present and iterate

Present the HTML file to the user. They'll see it rendered as an artifact. Common refinement requests:

  • Color/theme changes → update CSS custom properties
  • Layout adjustments → modify grid/flexbox
  • Content changes → edit text/SVG elements
  • Size changes → update .canvas dimensions

Each iteration is a quick HTML edit, not a full re-render. This is the key advantage over direct image generation.

Step 4: Export to image

Once the user is satisfied, run the export script:

python3 scripts/render_to_image.py <input.html> <output.png|.svg> [--width 1200] [--height 630] [--scale 2] [--selector ".canvas"]

Parameters

| Param | Default | Description | | ------------- | ---------- | ------------------------------------------------------- | | input | (required) | Path to HTML file | | output | (required) | Output path. Extension determines format (.png or .svg) | | --width | auto | Viewport width (overrides HTML-defined size) | | --height | auto | Viewport height (overrides HTML-defined size) | | --scale | 2 | Device scale factor for PNG (2 = retina quality) | | --selector | .canvas | CSS selector for the element to capture | | --full-page | false | Capture the full page instead of a specific element |

PNG export

Uses Playwright to launch headless Chromium and screenshot the .canvas element at the specified scale factor. Scale 2 produces retina-quality output (e.g., 1200×630 CSS pixels → 2400×1260 PNG).

SVG export

Two strategies, chosen automatically:

  1. SVG-native content: If the .canvas element contains a single root <svg>, extracts it directly as a clean SVG file. This produces a true vector SVG.
  2. HTML-based content: If the content is CSS/HTML-heavy, falls back to PNG export with a note that true SVG requires SVG-native design. The script will warn and suggest redesigning with SVG elements if vector output is needed.

Delivering the output

Present the output file to the user. Always deliver both the HTML (for future editing) and the image (final output).

Error Handling

| Error | Cause | Resolution | | ---------------------------- | ----------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------- | | playwright not found | Playwright package not installed | Run npx playwright install chromium or pip install playwright && playwright install chromium | | Browser launch failure | Headless Chromium fails to start | Verify --headless mode is supported; check available memory (Chromium needs ~200 MB) | | .canvas selector not found | HTML does not contain an element matching .canvas | Verify assets/template.html was used as the base; check the root container has class="canvas" | | Render timeout | Complex HTML takes too long to render before screenshot | Increase the timeout via --timeout flag in the script, or simplify the HTML (reduce DOM depth, inline fewer SVGs) | | SVG export falls back to PNG | .canvas element contains HTML/CSS content, not a root SVG | See SVG export section; redesign with a single root <svg> if vector output is required |

Limitations

  • Playwright + Chromium required — the export script cannot run without a working Chromium installation.
  • macOS and Linux only for headless browser export. Windows Subsystem for Linux works; native Windows Playwright may require separate setup.
  • SVG export is best-effort — complex HTML/CSS layouts fall back to PNG. True vector SVG requires a single root <svg> as the .canvas child.
  • Max viewport 4096×4096 — Chromium refuses screenshots larger than this. Use --scale to achieve higher effective resolution within this limit.
  • No animation support — exported images are static snapshots. CSS animations and JavaScript-driven transitions are frozen at their initial state.

Output Example

After a successful export, the script prints the output path and file stats:

Exported: concept-diagram.png
  Size:       2400 × 1260 px  (2× scale from 1200 × 630 canvas)
  File size:  ~180 KB
  Format:     PNG (RGBA)

Filename pattern follows whatever was passed as the output argument. Typical file sizes:

  • Simple diagrams (text + shapes): 80–200 KB
  • Dense infographics with gradients: 300–600 KB
  • Full 1920×1080 at 2× scale: 500 KB–1.5 MB

Design anti-patterns to avoid

These produce generic "AI-generated" looking output:

  • Centered everything with equal spacing
  • Purple/blue gradient backgrounds
  • Uniform border-radius on all elements
  • Generic icon libraries (use custom inline SVG)
  • System font stack without typographic intention
  • Drop shadows on everything
  • Low information density (too much whitespace)

Font handling

Since this environment has limited font access, use web-safe font stacks with intentional fallbacks:

  • Technical/mono: 'Courier New', 'Consolas', monospace
  • Clean sans: 'Helvetica Neue', 'Arial', sans-serif
  • Editorial serif: 'Georgia', 'Times New Roman', serif
  • Display: Use SVG text with custom paths for display typography when needed