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Photo Composition Prompt Generator — Educational Edition

A web-based educational tool for teaching visual composition and prompt engineering for AI-assisted multi-layered image assembly, using a non-destructive, layer-based approach.

Overview

The Photo Composition Prompt Generator teaches students how to structure complex prompts for AI image generation models by decomposing multi-layered image assembly into discrete, explicit operations. Rather than writing vague requests like "combine these photos," students learn to specify each composition decision through precise parameters — subject isolation, spatial positioning, scaling, blend modes, edge control, and color adjustments.

The tool operates on a non-destructive, layer-based paradigm: uploaded images are treated as distinct layers that are composed through explicit instructions, never altered or regenerated by the AI.

Key Features

  • Multi-Image Composition — Upload 2-3 images and define their roles (background, overlay, subject)
  • Layer-Based Workflow — Non-destructive composition using the metaphor of Photoshop layers
  • Role Assignment — Define each image as main subject, background, or overlay element
  • Blend Modes — Normal, Multiply, Screen, Overlay, Soft Light, Hard Light, and more
  • Spatial Controls — Position (X/Y), scale, rotation, and opacity for each layer
  • Subject Cutout — Optional background removal before compositing
  • Edge Control — Feathering, masking, and shadow generation parameters
  • Structured Prompt Output — Generates detailed, machine-readable composition instructions
  • Final Output Settings — Resolution, format, and quality specifications

Repository Contents

File Description
index.html Landing page
photo-composition-generator_APP.html Main application
photo-composition-prompt-learning-manual.html Educational Manual (12 chapters)

Live Demo

https://gkorakakis.github.io/photo-composition-prompt-generator/

Open directly in any modern browser. No installation required.

Usage

  1. Download or clone this repository
  2. Open index.html in any modern web browser
  3. Upload 2-3 images (JPG/PNG) and define their composition roles
  4. No server, no installation, no dependencies required

Pedagogical Context

Developed for the Interactive Design course at the Department of Graphic Design and Visual Communication, University of West Attica (UNIWA).

Students learn to:

  1. Decompose complex visual compositions into discrete layer operations
  2. Specify spatial relationships, blend modes, and masking parameters explicitly
  3. Translate intuitive compositional ideas into structured, machine-readable prompts
  4. Understand the relationship between traditional compositing and AI-mediated workflows

Technical Details

  • Architecture: Single-file HTML/CSS/JavaScript (no framework dependencies)
  • Image Handling: Client-side FileReader API, no server upload
  • Browser Support: Chrome, Firefox, Safari, Edge (latest versions)
  • Responsive: Adaptive layout for desktop and tablet

Author

Georgios Korakakis Assistant Professor, Department of Graphic Design and Visual Communication School of Applied Arts and Culture, University of West Attica (UNIWA) gkorakakis@uniwa.gr

AI Disclosure

This software was developed with the assistance of Claude AI (Anthropic) as a coding aid. All pedagogical design, scientific content, composition methodology, and educational framework were conceived, validated, and supervised by the author.

Citation

Korakakis, G. (2026). Photo Composition Prompt Generator: An Educational Tool for AI-Assisted Multi-Layered Image Composition (v1.0) [Software]. Zenodo. https://doi.org/10.5281/zenodo.19474264

License

Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) https://creativecommons.org/licenses/by-nc/4.0/

Permanent Archive

https://doi.org/10.5281/zenodo.19474264


Department of Graphic Design and Visual Communication - School of Applied Arts and Culture - University of West Attica (UNIWA)

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An educational tool for teaching visual composition and prompt engineering through non-destructive, layer-based AI-assisted image assembly.

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