# What Are the I² Visual Categories in awesome-gpt-image-2? A Complete Field Guide

> Explore the 12 I² visual categories in awesome-gpt-image-2, from UI interfaces to charts. Understand prompt template classifications for generated images.

- Repository: [苍何/awesome-gpt-image-2](https://github.com/freestylefly/awesome-gpt-image-2)
- Tags: field-guide
- Published: 2026-09-04

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**The freestylefly/awesome-gpt-image-2 repository defines thirteen I² visual categories—such as UI & Interfaces, Charts & Infographics, and History & Classical Chinese Themes—that classify every prompt template and generated image in the gallery.**

The awesome-gpt-image-2 project organizes its vast collection of GPT‑Image‑2 prompts and visual examples into a strict taxonomy called the **I² visual categories**. These categories appear in the repository’s [`README.md`](https://github.com/freestylefly/awesome-gpt-image-2/blob/main/README.md) under the “🗂️ Category Overview” section and power both the browsable documentation and the programmatic `gpt-image-2-style-library` skill.

## The 13 I² Visual Categories

Although often referenced informally as “the 12 visual categories,” the official I² taxonomy maintained in [`README.md`](https://github.com/freestylefly/awesome-gpt-image-2/blob/main/README.md) and [`data/style-library.json`](https://github.com/freestylefly/awesome-gpt-image-2/blob/main/data/style-library.json) contains **thirteen distinct classes**. Twelve cover specific visual disciplines, while the thirteenth acts as a catch‑all for experimental or mixed workflows. Every entry in the style library includes a `category` field that maps to one of the following values:

1. **UI & Interfaces** – Mobile apps, websites, dashboards, social media screenshots, and product interface mockups.

2. **Charts & Infographics** – Structured diagrams, knowledge maps, technical explainers, data visualisations, and information graphics.

3. **Posters & Typography** – Event posters, book covers, type‑driven visuals, and compositions where layout hierarchy dominates.

4. **Products & E‑commerce** – Product photography, detail pages, packaging designs, selling‑point highlights, and advertisement layouts.

5. **Brand & Logos** – Logos, identity systems, brand touchpoints, and campaign‑specific visual assets.

6. **Architecture & Spaces** – Architectural renders, interior designs, city maps, and spatial concept art.

7. **Photography & Realism** – Portraits, phone‑style photography, film‑texture emulation, and commercial‑grade realistic imagery.

8. **Illustration & Art** – Vector or raster illustrations, material experiments, decorative images, and fine‑art styles.

9. **Characters & People** – Character design sheets, pose references, character cards, and 3‑D toy renders.

10. **Scenes & Storytelling** – Storyboards, narrative scenes, livestream overlay frames, and world‑building visuals.

11. **History & Classical Chinese Themes** – Classical scrolls, historical figure portraits, traditional motifs, and poetry‑inspired visuals.

12. **Documents & Publishing** – White‑papers, technical manuals, encyclopedic plates, and multi‑page publishing layouts.

13. **Other Use Cases** – Creative experiments, mixed workflows, special one‑off tasks, and practical cases that fall outside the standard taxonomy.

Each category links to an anchored section in [`docs/gallery.md`](https://github.com/freestylefly/awesome-gpt-image-2/blob/main/docs/gallery.md) (for example, `#cat‑ui` for UI & Interfaces) where the full collection of curated examples resides.

## How to Access the Categories Programmatically

The canonical list of categories is stored in `data/style‑library.json`. Each object in the array contains a `category` property that matches one of the thirteen I² visual categories above. You can extract the unique taxonomy set in JavaScript as follows:

```javascript
// Load the style-library JSON and list all visual categories
import styleLibrary from '../data/style-library.json' assert { type: 'json' };

const categories = new Set();
styleLibrary.forEach(entry => {
  // Each entry contains a `category` field such as "UI & Interfaces"
  categories.add(entry.category);
});

console.log('I² visual categories:');
categories.forEach(cat => console.log('- ', cat));

```

Running this script prints the thirteen category names exactly as defined in the repository’s taxonomy, ensuring your automation stays synchronized with the official classification.

## Key Source Files Defining the Taxonomy

Three primary files govern the I² visual category system:

- **[`README.md`](https://github.com/freestylefly/awesome-gpt-image-2/blob/main/README.md)** – Declares the categories in the “🗂️ Category Overview” section and links to gallery anchors.
- **[`docs/gallery.md`](https://github.com/freestylefly/awesome-gpt-image-2/blob/main/docs/gallery.md)** – Hosts the anchored sections (`#cat‑ui`, `#cat‑infographic`, `#cat‑poster`, etc.) that contain the full case listings for each category.
- **`data/style‑library.json`** – Machine‑readable source that powers the project website and the **gpt‑image‑2‑style‑library** skill; every record includes a `category` field matching the I² visual categories.

## Summary

- The awesome-gpt-image-2 repository uses a formal **I² visual taxonomy** consisting of thirteen categories, despite common references to “12 categories.”
- Categories range from **UI & Interfaces** to **Documents & Publishing**, covering design, photography, illustration, and classical themes.
- The classification system is hard‑coded in [`README.md`](https://github.com/freestylefly/awesome-gpt-image-2/blob/main/README.md), documented in [`docs/gallery.md`](https://github.com/freestylefly/awesome-gpt-image-2/blob/main/docs/gallery.md), and machine‑readable in [`data/style-library.json`](https://github.com/freestylefly/awesome-gpt-image-2/blob/main/data/style-library.json).
- Developers can extract category lists programmatically by reading the `category` field from the style‑library JSON file.

## Frequently Asked Questions

### Why does the repository list thirteen visual categories instead of twelve?

The “Other Use Cases” category acts as a thirteenth bucket for experimental prompts and workflows that do not fit the standard twelve disciplines. While the project name and common shorthand sometimes imply a dozen categories, the official I² taxonomy in [`README.md`](https://github.com/freestylefly/awesome-gpt-image-2/blob/main/README.md) and [`data/style-library.json`](https://github.com/freestylefly/awesome-gpt-image-2/blob/main/data/style-library.json) explicitly includes thirteen entries to ensure comprehensive coverage.

### How do I browse images for a specific visual category?

Navigate to [`docs/gallery.md`](https://github.com/freestylefly/awesome-gpt-image-2/blob/main/docs/gallery.md) in the repository and use the anchored links provided in the README (for example, `#cat‑photography` for Photography & Realism). Each anchor jumps to a dedicated section containing curated prompt templates and generated image examples for that category.

### What is the relationship between the categories and the gpt-image-2-style-library skill?

The **gpt‑image‑2‑style‑library** skill consumes [`data/style-library.json`](https://github.com/freestylefly/awesome-gpt-image-2/blob/main/data/style-library.json) at runtime. When the skill generates or classifies images, it references the `category` field in each JSON record to apply the correct styling rules, layout constraints, and prompt modifiers associated with that I² visual category.

### Can I contribute new prompts to a specific visual category?

Yes. Contributors should add prompt entries to [`data/style-library.json`](https://github.com/freestylefly/awesome-gpt-image-2/blob/main/data/style-library.json) and ensure the `category` value matches one of the thirteen official I² visual categories. After updating the JSON, place example outputs in the corresponding anchored section of [`docs/gallery.md`](https://github.com/freestylefly/awesome-gpt-image-2/blob/main/docs/gallery.md) so the visual documentation remains synchronized with the data source.