# Text To Image Test Prompt Library

A comprehensive collection of evaluation prompts for testing text-to-image AI models across diverse parameters and use cases.

## Overview

This repository contains a structured set of test prompts designed to evaluate the capabilities of text-to-image generation models. Rather than focusing on formal evaluation metrics, these prompts are intended for end users who want to test how well a model might perform for their specific use cases.

## Purpose

- Provide a diverse set of real-world test cases for text-to-image models
- Help users evaluate model performance across different domains and requirements
- Identify strengths and weaknesses of different models
- Support informed decision-making when selecting a text-to-image model

## Test Categories

This repository includes 32 distinct test categories, with each category containing multiple prompt examples (typically 5 per file). The total collection includes approximately 160 test prompts.

Categories include:

- **Typo Handling**: Testing how models handle nonsensical text, obvious typos, and poorly written prompts
- **Marketing Collateral**: Prompts for advertisements, billboards, and other marketing materials
- **Lighting Instructions**: Testing model response to specific lighting directions
- **Graphic Design**: Evaluating capabilities for creating design assets
- **Architectural Renders**: Testing architectural visualization capabilities
- **Confusing/Conflicting Prompts**: Evaluating how models resolve ambiguous instructions
- **Character Consistency**: Testing ability to maintain character attributes
- **Stylistic Following**: Evaluating adherence to specific artistic styles
- **Logo Design**: Testing capabilities for brand identity creation
- **Emotion/Subtle Emotion**: Evaluating ability to convey emotional nuance
- **Very Specific Instructions**: Testing precision in following detailed directions
- **And many more specialized categories**

## How to Use

1. Browse the category directories to find relevant test prompts for your use case
2. Use these prompts with your text-to-image model of choice
3. Compare results across different models using the same prompts
4. Evaluate which model performs best for your specific requirements