--- name: generative-art-deployment description: Deploy generative art projects for exhibition, web galleries, and print production. Covers rendering pipelines, resolution management, gallery hosting, and archival strategies for algorithmic artworks. Triggers on generative art deployment, art exhibition setup, or digital art publishing requests. license: MIT complexity: intermediate time_to_learn: 30min tags: - generative-art - deployment - gallery - exhibition - archival governance_phases: [build, prove] organ_affinity: [organ-ii] triggers: [user-asks-about-art-deployment, context:generative-art-exhibition, context:art-gallery, context:art-publishing] complements: [generative-art-algorithms, three-js-interactive-builder, algorithmic-art, deployment-cicd] --- # Generative Art Deployment Move generative artworks from development to exhibition, print, and archive. ## Deployment Targets | Target | Format | Resolution | Considerations | |--------|--------|-----------|----------------| | **Web gallery** | HTML/JS, WebGL | Screen (72-96 DPI) | Performance, loading time | | **Physical print** | PNG/TIFF | 300 DPI minimum | Color profiles, bleed | | **LED installation** | Video/WebGL | Panel-specific | Brightness, refresh rate | | **NFT/on-chain** | PNG/SVG/HTML | Variable | File size, determinism | | **Social media** | PNG/MP4 | Platform-specific | Compression, aspect ratio | | **Archive** | Source + renders | Maximum | Reproducibility | ## Web Gallery Deployment ### Static Gallery Structure ``` gallery/ ├── index.html # Gallery grid/navigation ├── works/ │ ├── piece-001/ │ │ ├── index.html # Full-screen viewer │ │ ├── sketch.js # Live generative code │ │ ├── thumbnail.png │ │ └── metadata.json │ └── piece-002/ │ └── ... ├── assets/ │ ├── style.css │ └── gallery.js └── catalog.json # Machine-readable catalog ``` ### Work Metadata ```json { "title": "Recursive Bloom #47", "artist": "Artist Name", "date": "2026-03-20", "medium": "Generative, p5.js", "dimensions": "3840 × 2160", "seed": 1742518400, "parameters": { "complexity": 0.7, "palette": "autumn", "iterations": 5000 }, "description": "An exploration of recursive growth patterns...", "series": "Recursive Bloom", "edition": "1/1", "tags": ["recursion", "organic", "growth"] } ``` ### Performance Optimization ```javascript // Render once, display static function setup() { const canvas = createCanvas(3840, 2160); noLoop(); // Don't animate } function draw() { randomSeed(SEED); // ... generate artwork saveCanvas('output', 'png'); } // For interactive pieces: use requestAnimationFrame // with quality degradation on low-end devices function draw() { if (frameRate() < 30) { reduceComplexity(); } } ``` ## Print Production ### Resolution Pipeline ```python def render_for_print(sketch_path: str, width_inches: float, height_inches: float, dpi: int = 300): pixel_width = int(width_inches * dpi) pixel_height = int(height_inches * dpi) # Add bleed (0.125 inches on each side) bleed = int(0.125 * dpi) total_width = pixel_width + 2 * bleed total_height = pixel_height + 2 * bleed return { "canvas_width": total_width, "canvas_height": total_height, "safe_area": { "x": bleed, "y": bleed, "width": pixel_width, "height": pixel_height, }, "dpi": dpi, "format": "TIFF", # Lossless for print "color_profile": "sRGB", # Or Adobe RGB for wide gamut } ``` ### Color Management ```python from PIL import Image, ImageCms def convert_for_print(input_path: str, output_path: str): img = Image.open(input_path) srgb_profile = ImageCms.createProfile("sRGB") # For fine art printing, embed the ICC profile img.save(output_path, "TIFF", dpi=(300, 300), icc_profile=ImageCms.ImageCmsProfile(srgb_profile).tobytes()) ``` ### Print Sizes | Size | Inches | Pixels (300 DPI) | |------|--------|-------------------| | A4 | 8.3 × 11.7 | 2490 × 3510 | | A3 | 11.7 × 16.5 | 3510 × 4950 | | A2 | 16.5 × 23.4 | 4950 × 7020 | | 24×36 poster | 24 × 36 | 7200 × 10800 | ## Rendering Pipeline ### Batch Rendering ```python import subprocess from pathlib import Path def batch_render(sketch: str, seeds: list[int], output_dir: str, width: int, height: int): Path(output_dir).mkdir(parents=True, exist_ok=True) for seed in seeds: output = f"{output_dir}/render_{seed:08d}.png" subprocess.run([ "node", sketch, "--seed", str(seed), "--width", str(width), "--height", str(height), "--output", output, ], check=True) # Render a series batch_render("sketch.js", seeds=range(1, 101), output_dir="renders/series-01", width=3840, height=2160) ``` ### Deterministic Rendering ```javascript // Ensure reproducibility: same seed = same output function setup() { const seed = parseInt(getURLParam('seed') || '42'); randomSeed(seed); noiseSeed(seed); // Record seed in metadata document.title = `Piece #${seed}`; } ``` ## Exhibition Patterns ### Installation Checklist - [ ] Hardware specs confirmed (GPU, resolution, orientation) - [ ] Autostart on boot configured - [ ] Crash recovery (watchdog/supervisor process) - [ ] No UI chrome (cursor hidden, fullscreen) - [ ] Network not required (all assets local) - [ ] Power failure recovery tested ### Kiosk Mode Setup ```bash # Linux kiosk mode #!/usr/bin/env bash xset -dpms # Disable power management xset s off # Disable screen saver unclutter -idle 0.5 & # Hide cursor chromium-browser \ --kiosk \ --disable-infobars \ --disable-session-crashed-bubble \ --noerrdialogs \ file:///home/gallery/piece/index.html ``` ## Archival Strategy ### Archive Package ``` archive/ ├── README.md # How to run this piece ├── source/ # Original source code │ ├── sketch.js │ └── package.json ├── renders/ # High-res rendered outputs │ ├── render_001.tiff │ └── render_001.png ├── metadata.json # Full metadata including parameters ├── dependencies/ # Vendored dependencies │ └── p5.min.js └── documentation/ ├── process.md # Artist statement, process notes └── screenshots/ # Exhibition documentation ``` ### Reproducibility Contract ```json { "runtime": "node 20.x + p5.js 1.9.x", "seed": 42, "canvas": "3840x2160", "parameters": {}, "checksum": "sha256:abc123...", "rendered": "2026-03-20T10:00:00Z" } ``` ## Anti-Patterns - **No seed recorded** — Every generative piece must have a reproducible seed - **Web-only renders** — Always produce high-res static renders for print/archive - **Missing metadata** — Parameters, dimensions, and creation date are essential - **No offline fallback** — Exhibition pieces must work without network - **Lossy-only archives** — Keep lossless TIFF/PNG alongside compressed versions - **Undocumented dependencies** — Vendor or lockfile all runtime dependencies --- Source attribution: luokai0 Original project: https://github.com/luokai0/ai-agent-skills-by-luo-kai/blob/main/ai-agent-skills/21-external-registries/18-organvm-skills/creative/generative-art-deployment/SKILL.md License: MIT License information: https://opensource.org/license/mit Original upstream instructions; downloaded from Mega AI Hub. ## Upstream license notice MIT License Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. # Mega AI Hub resource metadata Creator / publisher: luokai0 Original project: https://github.com/luokai0/ai-agent-skills-by-luo-kai/blob/main/ai-agent-skills/21-external-registries/18-organvm-skills/creative/generative-art-deployment/SKILL.md Attribution basis: Source repository record Fields of work: Content & Media, Design, Marketing Roles: Content Marketer, Graphic Designer, Product Designer, UX Designer, Video Producer Specialties: Design Tools: Three.Js Country applicability: Country not specified Classification basis: Source catalog labels Instruction SHA-256: 508b218510bfbcefe94d1d9ef4bf2820c1f8c7c3220fdbb83da005f712c4fe78