2026-07-08 08:57:50 +00:00

111 lines
2.4 KiB
Markdown

# TIFA-160
## Overview
TIFA-160 is a text-to-image benchmark with 160 carefully curated prompts designed to evaluate the faithfulness and quality of generated images using automated VQA-based evaluation.
## Task Description
- **Task Type**: Text-to-Image Generation Evaluation
- **Input**: Text prompt for image generation
- **Output**: Generated image evaluated using PickScore metric
- **Size**: 160 prompts
## Key Features
- Compact, high-quality prompt set for efficient evaluation
- Uses PickScore for human preference alignment
- Tests diverse image generation capabilities
- Supports both new generation and pre-existing image evaluation
- Reproducible evaluation pipeline
## Evaluation Notes
- Default configuration uses **0-shot** evaluation
- Primary metric: **PickScore** for human preference alignment
- Evaluates images from the **test** split
- Part of the T2V-Eval-Prompts dataset collection
## Properties
| Property | Value |
|----------|-------|
| **Benchmark Name** | `tifa160` |
| **Dataset ID** | [AI-ModelScope/T2V-Eval-Prompts](https://modelscope.cn/datasets/AI-ModelScope/T2V-Eval-Prompts/summary) |
| **Paper** | N/A |
| **Tags** | `TextToImage` |
| **Metrics** | `PickScore` |
| **Default Shots** | 0-shot |
| **Evaluation Split** | `test` |
## Data Statistics
| Metric | Value |
|--------|-------|
| Total Samples | 160 |
| Prompt Length (Mean) | 56.13 chars |
| Prompt Length (Min/Max) | 13 / 182 chars |
## Sample Example
**Subset**: `TIFA-160`
```json
{
"input": [
{
"id": "9de3e3b1",
"content": "A Christmas tree with lights and teddy bear"
}
],
"id": 0,
"group_id": 0,
"metadata": {
"prompt": "A Christmas tree with lights and teddy bear",
"category": "",
"tags": {},
"id": "TIFA160_0",
"image_path": ""
}
}
```
## Prompt Template
*No prompt template defined.*
## Usage
### Using CLI
```bash
evalscope eval \
--model YOUR_MODEL \
--api-url OPENAI_API_COMPAT_URL \
--api-key EMPTY_TOKEN \
--datasets tifa160 \
--limit 10 # Remove this line for formal evaluation
```
### Using Python
```python
from evalscope import run_task
from evalscope.config import TaskConfig
task_cfg = TaskConfig(
model='YOUR_MODEL',
api_url='OPENAI_API_COMPAT_URL',
api_key='EMPTY_TOKEN',
datasets=['tifa160'],
limit=10, # Remove this line for formal evaluation
)
run_task(task_cfg=task_cfg)
```